Posts in this project
Pallet Tracker - 01 - Project description
Pallet Tracker - 02 - Development environment
Pallet Tracker - 03 - Application skeleton
Pallet Tracker - 04 - PSoC6 power modes and LPComp
Pallet Tracker - 05 - Evaluating power consumption
Pallet Tracker - 06 - Indoor localization
This is a small introduction of the project I would like to build in this challenge
The problem
Tracking assets in a smart factory is fundamental to know where the goods been produced are. In this challenge, I will focus on the tracking of pallets and containers that are typically placed close to a machinery that mass-produces items. When a container is full, an operator (with eventually a forklift) will move to the next stage of the production process. The knowledge about the container location inside the factory is important because can provide useful information to the manufacturing monitoring systems, and can add valuable production information to the data collected from the machineries. For example, there are scenarios where a processing station is not operational because of a problem not related to one of the monitored machines but, instead, to an external cause. The capability to track pallets may let the manufacturing monitoring system know that something is not proceeding as expected because an excessive amount of semi-finished products is located in the buffer area just before that specific station
Proposed solution
The proposed solution is based on indoor localization and tracking by means of the strength of the received signal from the nearby WiFi Access points. Use of existing WiFi infrastructure is a convenient solution because there is no need for further hardware (e.g. BLE beacons), thus making adoption of this solution easier. Each container to be tracked will be equipped with a PSoC
6S2 + AIROC Wi-Fi/Bluetooth Pioneer Kit. The board will be be able to detect when the container is lifted by reading the output of a load cell. The PSoC6 board will be normally in hibernate mode to save energy. Thanks to the low-power comparator integrated in the PSoC6, the board will wake up when a reduction in the measured strain (which means the container has been lifted) is detected. As soon as the board wakes up
- it will scan for nearby access points and will collect signal strengths
- it will the connect to the nearest access point and send signal strength data to the factory server.
The factory server runs an open source indoor localization application which, based on pre-trained WiFi fingerprint and signal strengths sent by the PSoC6 board, will calculate the container position
As a further enhancement, a vibration energy harvester will be devised. This looks a promising solution because container are typically located close to machinery that creates a lot a vibrations, than can be usefully collected to keep the battery charged
The plan
1. Analysis of the low-power modes
The most suitable power modes will be identified among the all the possible options to optimize battery usage
2. Create the application on the PSoC6
An application that reads load cell, scans for Wifi networks and sends detected RSSIs to the gateway will be implemented
3. Configure the WiFi infrastructure
In this phase, I will configure and install a WiFi infrastructure for demo purposes
4. Create the WiFi fingerprint
Data about beacons RSSI will be collected to make localization more precise
5. Test of the localization
The accuracy of the localization process will be evaluated
6. Design of the vibration energy harvester
Finally, a vibration energy harvester will be build and evaluated
The kit
I recently received the kit for the challengers
and, in the parcel, there was a nice surprise from Infineon
So thanks Element14 and Infineon for the opportunity!
