Read the latest News for the PEPR AgriFutur project that are maintained on the IoT-Sensing-System at UPPA web site.
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Jan-25 Preliminary codes have been uploaded: the code for a Generic Simple Sensor Node and the code for a PoC LoRa image sensor node (LoRaCAM-AI).
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Nov-24 We created the GitHub repository for the PEPR AgriFutur project. Check contributions & activities of UPPA team project on the IoT-Sensing-System web site. AgriFutur will officially start in Feb. 1st, 2025. Stay tuned!
The Arduino sketch for the Generic Simple Sensor Node is in the Arduino folder. It is based on the code developed for the PRIMA INTEL-IRRIS project that is now extended and maintained in the context of AgriFutur.
The PoC of a LoRa image sensor (LoRaCAM-AI) based on ESP32 camera board is in the Arduino_ESP32 folder. We tested several ESP32-based camera boards. The main criterion was to have enough pins left to easily connect an SPI LoRa radio module. 3 boards offer this capabilities: Freenove ESP32-S3 WROOM, Freenove ESP32 WROVER v1.6 and XIAO ESP32-S3 Sense. The choice was finally set to the state-of-the-art XIAO ESP32-S3 Sense which has a huge developer community and enough resource to run some embedded AI processing that we want to add in the future, and all this in a quite compact format. If other boards appear on the market, the LoRa test sketch can be used to test whether the LoRa radio module you choose can be controlled by the pins on the new boards. Of course, you have to change the pin mapping and test.
For the LoRaCAM image sensor, the Tools folder contains the various software tool to test the customized image encoding approach in order to have a robust encoding scheme for efficient LoRa transmission of images.
Enjoy! C. Pham Scientific Leader for the Sensing Platform