Author: IOTSS_Admin

Posted on

Increased collaborations and synergies with INDICATIC AIP of Panama!

In Dec. 1st, 2025, taking advantage of the visit of Pr Philippe Aniorté, Director of INDICATIC AIP, the National Institute for Advanced Reasearch in Information and Communication Technologies of Panama, Pr Congduc Pham and Pr Philippe Aniorté signed 2 Letter of Intent (LOI) to increase collaborations and synergies between the 2 research teams. The first LOI establishes a Research & Development collaboration on wireless smart sensors technologies development and deployment targeting agroecological application domains. This will be realized in the context of the AgriFutur flagship project of the PEPR Program. The second LOI establishes a collaboration for capacity-building and upscaling research capacities and encouragement of multidisciplinary studies in the context of the Erasmus+ RADIO project. In particular, INDICATIC AIP researchers will contribute to presentations, keynotes and lectures in the Intensive Study Program (ISP) that is developed at UPPA for RADIO.

Posted on

INTEL-IRRIS & AgriFutur will be presented in Panama!

Prof. C. Pham, who coordinatd the PRIMA INTEL-IRRIS project and who is leading the IoT sensor activities in AgriFutur, has been invited by the French Embassy in Panama, to present the methodology, the results and lessons learnt when building & deploying cost-effective sensors at a scientific France-Panama event co-organized by the French Ambassy on innovation for sustainable agriculture. Download the presented slides in .pdf.

The event was located at Ciudad del Saber, Panama City. The invitation of Prof C. Pham was the result of a collaboration since June 2023 with INDICATIC AIP directed by Prof. P. Aniorté. A big thank you to the French Embassy team in Panama for this exciting event with an incredible program and more than 1000 participants!

Watch the recorded video on YouTube (for the whole video, click here), otherwise, click below to jump to the presentation from Prof. C. Pham.

Posted on

LoRaCAM-AI for AgriFutur: first PoC is promising!

Integration of LoRaCAM-AI is almost at its final stage with the low power mode validated! Get all the explanations, diagrams, code and software tool to test the LoRaCAM-AI on the GitHub.

Next step is to embed AI processing on the captured image to implement some image recognition tasks. The objective is to have a generic low power camera that can be trained for various applications in agroecology.

In this video, the LED on the XIAO ESP32-S3 Sense will blink as follows: (1) after power up and an image is ready for encoding and transmission, the LED will slowly blink twice; (2) each time a packet has been successfully transmitted the LED will blink once; (3) when all packets have been transmitted, the LED will again slowly blink twice. The power will be managed by an external Arduino Pro Mini which LED will blink as follows: (1) after power on, and after each wake up, the LED will blink 5 times fast; (2) each time that the activity pin from the ESP32 goes below the defined activity threshold, the LED will blink once; (3) when the activity pin has been below the activity threshold for at least 2s, the LED will slowly blink 4 times, indicating that the power to the ESP32 is going to be cut. This is when the Arduino Pro Mini will go in deep sleep for typically 1 hour.

Posted on

Contributions to PEPR AgriFutur are on a GitHub

During the whole December 2024 month, we tested various ESP32 camera board to finally select the XIAO ESP32-S3 Sense board! The main criterion was to have enough pins left to 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 `XIAO ESP32-S3 Sense` which has a huge developer community and enough resource to run embedded AI processing that we want to add in the future in a quite compact format.

We released on the PEPR AgriFutur GitHub a PoC of a smart image sensor device based on XIAO ESP32-S3 Sense with an OV2640 camera capable of periodically capturing and transmitting with LoRa radio a small size image, typically 128×128, in a robust encoding image format. Proper casing for outdoor deployment will follow.