The problem
Sport exercises can generate significant stress for human body. It may be difficult for many to realize where is their limit. There is a high risk of going over the limit. At the same time it may be not very efficient to perform workout far below the limit. How should we approach finding a personalized sweet spot for training? Sensor data from training, and especially from stress tests, can provide very valuable information about condition of critical organs like heart, lungs. This information can help improve sport performance by adjusting training workload or or by helping identify and possibly prevent potential problems.
Modern wearable devices collect a lot of data, but these data sets are typically available only in a form of a summary after exercise is completed or in a form of a snapshot, which is not so simple to share with a trusted parties in real-time.
Concept
The idea of my Bio Highway project is continuously capture bio telemetry from sport enthusiasts and feed it to trusted parties, like your trainer or friend, over secured channels to get real-time actionable feedback or encouragements.
The idea of the project came after listening to Peter Attia podcast with Eric Topol and reading Eric's book Deep Medicine.
The name of the project came after listening to Confluent Streaming Audio podcast "Paving a Data Highway with Kafka Connect ft. Liz Bennett".
Target Solution
PSoC 6 WiFi-BT Pioneer Kit (CY8CKIT-062-WIFI-BT) will collect data from sensors, communicate it securely to AWS IoT platform. AWS IoT platform will securely manage and connect wearable device to AWS cloud to analyze and securely share vital data, which can help make actionable decisions in real-time.
Project Plan
- Follow Getting started with AWS IoT Core
- Follow free eLearning course IoT Edge Computing: Amazon FreeRTOS Primer
- Install and test build tool-chain with a demo project by following Getting Started with Amazon FreeRTOS and PSoC62 + 43xxx
- Test device on-boarding and provisioning with AWS IoT
- Procure heart rate monitoring sensor
- Research options of sending time-series data over MQTT in real-time
- Define MQTT topic structure
- Define MQTT events model
- Integrate electronic components
- Expand demo code functionality to capture heart rate monitoring sensor telemetry
- Expand functionality to capture accelerometer sensor telemetry
- Publish telemetry over MQTT
- Create routing rules on Rule Engine
- Store data in S3 bucket
- Visualize and explore data using QuickSight
- Build feedback UI
- Create driver to display feedback on the wearable display
- Create edge processing on PSOC
- Use Device Shadow to configure rules on PSOC
- Perform end-to-end test
- Analyze AWS costs
- Record demo
- Refine final Block Diagrams
- Refine list of BOM
- Publish project assets on the project Github repo
Key components of the solution
My initial plan is to use the following components in the solution.
• Wearable device
○ Heart rate monitoring sensor AD8232 (or similar)
○ PSoC 6 WiFi-BT Pioneer Kit (CY8CKIT-062-WIFI-BT)
Analog Front End
ADC
WiFi
BLE system
Accelerometer
Display
○ Amazon FreeRTOS
Bootloader
OTA Agent
MQTT Agent
Secure Storage
Edge processing
Device Shadow
• AWS IoT
○ AWS IoT Device Management
○ Device Gateway
Device authentication and authorization (Amazon Cognito)
○ Communication and integration
MQTT Broker
Message routing
○ Rules Engine
○ AWS S3 bucket
○ User IAM, authentication and authorization (Amazon Cognito)
○ Analytics dashboard (Amazon QuickSight or CloudWatch Anomaly Detection)
○ Feedback component
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