https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kitBoard detailsen-USTelligent Community 12https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kitWed, 06 Mar 2024 19:22:29 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsCurrent Revision posted to Boards by e14-publisher on 3/6/2024 7:22:29 PM<br /> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022b/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai" data-e14adj="t">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-0f380" data-at-label="PRODUCT_POPUP_OPEN"href="https://referral.element14.com/OrderCodeView?nsku=87AK5105&COM=e14c-noscript&CMP=e14c-noscript&osetc=e14-noscript-tracking-loss" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('0f380'));" data-farnell="" data-newark="87AK5105" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="" data-avnetema="" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png" data-e14adj="t"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank" data-e14adj="t">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png" data-e14adj="t"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" data-e14adj="t">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank" data-e14adj="t">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" data-e14adj="t">Hardware User Guide</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">User Manual/Guide</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147094?ICID=imx8-datasheet-widget" data-e14adj="t">Linux Yocto User Manual</a> </div> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147483?ICID=imx8-datasheet-widget" data-e14adj="t">Linux Yocto Development Guide V1.0</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Out of Box Image</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/149000" data-e14adj="t">Yocto Out of Box Image</a> </div> </div> </div> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/18Tue, 06 Feb 2024 09:27:56 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 18 posted to Boards by e14-publisher on 2/6/2024 9:27:56 AM<br /> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022b/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai" data-e14adj="t">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-64e84" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('64e84'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="" data-avnetema="" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png" data-e14adj="t"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank" data-e14adj="t">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png" data-e14adj="t"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" data-e14adj="t">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank" data-e14adj="t">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" data-e14adj="t">Hardware User Guide</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">User Manual/Guide</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147094?ICID=imx8-datasheet-widget" data-e14adj="t">Linux Yocto User Manual</a> </div> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147483?ICID=imx8-datasheet-widget" data-e14adj="t">Linux Yocto Development Guide V1.0</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Out of Box Image</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/149000" data-e14adj="t">Yocto Out of Box Image</a> </div> </div> </div> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/17Wed, 19 Apr 2023 15:02:54 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 17 posted to Boards by e14-publisher on 4/19/2023 3:02:54 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022b/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-94133" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('94133'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" target="_blank">Hardware User Guide</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">User Manual/Guide</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147094?ICID=imx8-datasheet-widget" target="_blank">Linux Yocto User Manual</a> </div> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147483?ICID=imx8-datasheet-widget" target="_blank">Linux Yocto Development Guide V1.0</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/16Mon, 09 Jan 2023 17:07:04 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 16 posted to Boards by e14-publisher on 1/9/2023 5:07:04 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022b/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-31ce2" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('31ce2'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" target="_blank">Hardware User Guide</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">User Manual/Guide</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/147094?ICID=imx8-datasheet-widget" target="_blank">Linux Yocto User Manual</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/15Fri, 11 Nov 2022 21:41:41 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 15 posted to Boards by e14-publisher on 11/11/2022 9:41:41 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022b/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-9aed0" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('9aed0'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" target="_blank">Hardware User Guide</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/14Wed, 13 Jul 2022 13:57:21 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 14 posted to Boards by e14-publisher on 7/13/2022 1:57:21 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-5e8f6" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('5e8f6'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" target="_blank">Hardware User Guide</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/13Thu, 09 Jun 2022 15:09:35 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 13 posted to Boards by e14-publisher on 6/9/2022 3:09:35 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-6e670" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('6e670'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=imx8-datasheet-widget" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Hardware Guides</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145983?ICID=imx8-datasheet-widget" target="_blank">Hardware User Guide v1.3</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/12Thu, 09 Jun 2022 15:04:19 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 12 posted to Boards by e14-publisher on 6/9/2022 3:04:19 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-dcfb5" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('dcfb5'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/11Thu, 09 Jun 2022 14:52:18 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 11 posted to Boards by e14-publisher on 6/9/2022 2:52:18 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-597b1" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('597b1'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Image</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/10Thu, 09 Jun 2022 14:48:52 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 10 posted to Boards by e14-publisher on 6/9/2022 2:48:52 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-bca15" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('bca15'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Image</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Board Support Package</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T&amp;CMP=GL-Avnet-E14-cross-sell" target="_blank">Yocto Source File</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/9Thu, 09 Jun 2022 14:43:41 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 9 posted to Boards by e14-publisher on 6/9/2022 2:43:41 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-feeb0" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('feeb0'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><center><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T" target="_blank">Yocto Image</a></center></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/8Thu, 09 Jun 2022 14:40:52 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 8 posted to Boards by e14-publisher on 6/9/2022 2:40:52 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-0e876" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('0e876'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a><br /><a href="https://www.avnet.com/wps/wcm/connect/onesite/dd79b2bd-4216-4b50-9ee5-1a6a655e706c/Edge-AI-Kit-Yocto.zip?MOD=AJPERES&amp;CVID=nWznc7T&amp;CVID=nWznc7T" target="_blank">Yocto Image</a></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/7Thu, 02 Jun 2022 16:40:34 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 7 posted to Boards by e14-publisher on 6/2/2022 4:40:34 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-mt4"> <a class="e14-button e14-button--secondary xs-inline-block" href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai">Support Forum</a> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-ace86" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('ace86'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/6Fri, 27 May 2022 15:34:54 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 6 posted to Boards by e14-publisher on 5/27/2022 3:34:54 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> <a href="/products/devtools/avnetboardscommunity/avnetboard-forums/f/i-mx-8m-edge-ai"><div class="e14-button e14-button--secondary xs-inline-block">Support Forum</div></a> </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-e219b" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('e219b'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/5Mon, 31 Jan 2022 15:19:49 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 5 posted to Boards by e14-publisher on 1/31/2022 3:19:49 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-72e17" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('72e17'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="i.MX 8m Angle View" /></a></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/4Mon, 31 Jan 2022 15:17:35 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 4 posted to Boards by e14-publisher on 1/31/2022 3:17:35 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> </div> </div> <div class="xs-w20"><img alt="image" style="max-height:160px;" src="/e14/assets/main/2022/BGimx8EdgePlus.png" /></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-48e11" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('48e11'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <p class="xs-pt1"><strong>Click on the images to enlarge</strong></p> <div class="xs-flex xs-flex-wrap xs-mb3"> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Angle View</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_angle4.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_angle4.png" class="product-page-thumbnail" alt="iMX 8m angle" /></a></div> </div> <div class="xs-border rounded xs-mr4 xs-mb3 xs-overflow-hidden"> <div class="fill-gray-whisper text-e14-blue xs-py2 xs-px2 bold xs-border-bottom">Camera Adapter</div> <div class="xs-p2"><a class="e14-glowmodal-img" href="/e14/assets/main/2022/imx8EdgePlus_CameraAdpt.png"><img loading="lazy" src="/e14/assets/main/2022/THimx8EdgePlus_CameraAdpt.png" class="product-page-thumbnail" alt="Camera Adapter" /></a></div> </div> </div> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40°C to +85°C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/3Thu, 27 Jan 2022 16:07:47 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 3 posted to Boards by e14-publisher on 1/27/2022 4:07:47 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> </div> </div> <div class="xs-w20"></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-7b2c1" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('7b2c1'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40&deg;C to +85&deg;C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> <h3 class="toc-item xs-pb2 xs-border-bottom">Technical Documents</h3> <div class="xs-mb4 xs-px2"> <h4 class="xs-my2 xs-pb1 xs-border-bottom">Product Brief</h4> <div class="xs-my1 xs-text-5"> <i class="fal fa-file"></i> <a href="/products/devtools/avnetboardscommunity/m/files/145052?ICID=" target="_blank">Product Brief</a> </div> </div> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/2Thu, 27 Jan 2022 15:50:15 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 2 posted to Boards by e14-publisher on 1/27/2022 3:50:15 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> </div> </div> <div class="xs-w20"></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-a7c50" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('a7c50'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> <h4 class="bold">Target Applications</h4> <ul> <li>Artificial Intelligence</li> <li>Machine Learning</li> <li>Add-on Sensor IoT/Cloud Connectivity</li> <li>Embedded Computing</li> <li>Industrial Robotics</li> <li>Wired Industrial Networking using Gigabit Ethernet (IEEE 1588, 1x with TSN)</li> <li>Wireless Communications using Wi-Fi/Bluetooth/NFC</li> <li>Entry level i.MX 8M Plus Development Environment</li> <li>Training, Prototyping, and Proof-of-concept Demo Platform</li> <li>Production Ready, Available for Mass-production</li> </ul> <h4 class="bold">Features</h4> <ul> <li>Quad Core Arm Cortex-A53 ARM Applications Processor</li> <li>2GB (up to 4GB options available) LPDDR4 Memory</li> </ul><strong>(inline ECC)</strong> <ul><li>16GB (up to 256GB option available) eMMC 5.1</li> </ul><strong>Flash Storage</strong> <ul><li>64Mb QSPI Flash (option available)</li> <li> Delkin 16GB MicroSD Card + Adapter</li> <li>Yocto Linux BSP Available for Download</li> <li>Wi-Fi/Bluetooth/NFC Module (option available)</li> <li>HDMI 2.0 up to 4K (3840x2160@30FPS)</li> <li>2 x LVDS Display Panel Support</li> <li>Two ON Semiconductor AR1335 IAS Camera Modules</li> <li>ON Semiconductor AP1302 ISP</li> <li>Dual MIPI-CSI Host Interfaces</li> <li>1x USB 3.0, 1x USB 2.0 Type A ports</li> <li>Machine Learning Accelerator (2.3 TOPS)</li> <li>Image Sensor Processor 12MP@30fps</li> <li>146mm x 80mm Form Factor</li> <li>40&deg;C to +85&deg;C Industrial Temperature Rated</li> </ul> <p><strong>New eIQ capabilities are added on a regular basis as the underlying model libraries and tools evolve over time.</strong></p> <h4 class="bold">Kit includes</h4> <ul> <li>Avnet i.MX 8M Plus SMARC SOM</li> <li>Avnet EP5 SMARC Carrier</li> <li>Dual Image Sensor Adapter and Cable</li> <li>10.1 Inch Touch Display and Cables</li> <li>Standard Heat Sink Thermal Management Solution</li> <li>12V Power Supply</li> <li>Quick Start Instruction Card</li> </ul> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div> https://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit/revision/1Thu, 27 Jan 2022 15:38:37 GMT93d5dcb4-84c2-446f-b2cb-99731719e767:454ac469-f9ec-4b47-94a5-c81e6be1fe99e14-publisherhttps://community.element14.com/products/devtools/avnetboardscommunity/w/boards/27449/avnet-i-mx-8m-plus-edge-ai-kit#commentsRevision 1 posted to Boards by e14-publisher on 1/27/2022 3:38:37 PM<br /> <div class="xs-hide"> <script>e14.meta.page.devtools={"id": 31, "type": "product-page"};</script> </div> <div id="product-page-content"> <div class="xs-flex"> <div class="xs-w80 xs-mr3"> <div class="xs-text-4">Welcome to <span style="font-size:26px;color:#555;line-height:28px;">Avnet i.MX 8M Plus Edge AI Kit</span></div> <div class="xs-my3">The Avnet i.MX 8M Plus Edge AI Kit consists of a SMARC System-on-Module(SOM) and an Industrial Carrier board bundled together with a dual camera adapter to provide a complete embedded computing system for prototyping new industrial systems and evaluating the capabilities of the NXP i.MX 8M device family. </div> <div class="xs-mt4"> </div> </div> <div class="xs-w20"></div> </div> <div class="xs-flex xs-flex-wrap xs-mt3 xs-pb3"> <div class="xs-my2 xs-mr4"> <button class="e14-product-link fill-grey-lighter xs-inline-block pill xs-mt1 xs-border-green xs-pt05 xs-pb05 xs-pl2 xs-pr05 bold xs-text-6" id="e14-product-link-f3a00" data-at-label="PRODUCT_POPUP_OPEN"href="javascript:void(0)" onclick="event.preventDefault();e14.func.displayProduct(e14.meta.user.country, this, 'embedded-link', e14.func.getProductLinkJSON('f3a00'));" data-farnell="" data-newark="" data-comoverride="" data-cmpoverride="" data-cpc="" data-avnetemea="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetema="AES-IMX8MPLUS-AI-DEV-KIT-G" data-avnetasia="" data-at-areainteracted="design-center" data-at-type="click" data-at-link-type="button">8M Plus Edge<div class="pill xs-inline-block xs-border-lighter fill-green text-white xs-p1 xs-ml3 e14_shopping-cart-far-sml">Buy Now</div></button> </div> </div> <h3 class="xs-pb2 xs-border-bottom">Technical Specification</h3> <p>The high-performance NPU of the i.MX 8M Plus processor allows machine learning and Artificial Intelligence implementations with heavy compute demands to be pushed from the cloud down to the edge where low latency response can be critical for achieving end application goals.</p> <p>System designers can simply design their own carrier card, plug-in the Avnet SMARC SOM, and start their application development with proven i.MX 8M Plus hardware. Available with NXP 14nm FinFET technology to allow high computing, graphics, and image processing performance at very low power consumption and combined with a high degree of functional integration device, the Avnet SMARC SOM enables designers to build industrial, medical, retail, and other embedded vision applications with confidence and ease. The integrated Neural Network Accelerator provides up to 2.25TOPS for boosting AI applications at the edge (without High Performance CPU/GPU) enabling emerging applications like Access Control based on Face Recognition to become more easily deployed without complete reliance upon cloud computing resources.</p> <p>When combining this development kit with the NXP eIQ<span class="emoticon" data-url="https://community.element14.com/cfs-file/__key/system/emoji/2122.svg" title="Tm">&#x2122;</span> Machine Learning Software Development Environment, many options for Inference Engines, Vision Libraries, and ML workflow can be used to quickly deploy applications needing the following types of model capabilities:</p> <ul> <li>Classification</li> <li>Object Detection</li> <li>Face Recognition</li> <li>Sequence Analysis</li> </ul> </div> <div style="clear:both;"></div> <div style="font-size: 90%;">Tags: 8m_Plus_Edge_AI_Kit, i.mx, 8m_Plus_Edge, 8m_Plus_Edge_AI</div>