Low Power Environmental Image Sensors for Remote Photogrammetry.
Alpha Yaya Balde1, Emmanuel Bergeret1, Denis Cajal1
1Laboratoire de Physique de Clermont-UMR 6533 (LPC), Centre National de la Recherche Scientifique (CNRS), Université Clermont Auvergne (UCA), Avenue Aristide Briand CS 82235, CEDEX, 03101 Montluçon, France.
Sensors (Basel, Switzerland)
|October 14, 2022
Summary
This study demonstrates a low-cost 4D monitoring system for sandbars using the ESP32-Cam. The system enables studying river dynamics and vegetation interactions with years of autonomy.
Area of Science:
- Environmental monitoring
- Remote sensing technologies
- Ecological dynamics
Background:
- Sandbars are dynamic geomorphic features crucial for river ecosystems.
- Understanding river dynamics and vegetation interactions is vital for ecological management.
- Existing monitoring solutions often lack cost-effectiveness and long-term autonomy.
Purpose of the Study:
- To establish the feasibility of a 4D monitoring solution for sandbars.
- To characterize the role of vegetation in the river landscape.
- To develop a low-power, low-resolution sensor network for studying river-vegetation interactions.
Main Methods:
- Implementing a photogrammetry solution with low-resolution sensors.
- Testing various sensor configurations for image capture and data transmission.
- Analyzing the energy consumption of different operational phases (setup, capture, transmission, standby).
Main Results:
- The ESP32-Cam board successfully performed 3D reconstruction.
- UXGA (1600x1200) resolution was recommended for optimal quality and energy balance.
- A multi-node system with Wi-Fi and GSM relay achieved several years of autonomy.
Conclusions:
- A cost-effective 4D monitoring system is feasible for sandbars.
- The developed system can effectively study river-vegetation dynamics.
- The optimized system is ready for deployment on the Allier River.
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