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Low Power Environmental Image Sensors for Remote Photogrammetry
This paper aims to prove the feasibility of a 4D monitoring solution (3D modeling and temporal monitoring) for the sandbar and to characterize the species’ role in the landscape. The developed solution allows studying the interaction between the river dynamics and vegetation using a network of low r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572540/ https://www.ncbi.nlm.nih.gov/pubmed/36236714 http://dx.doi.org/10.3390/s22197617 |
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author | Balde, Alpha Yaya Bergeret, Emmanuel Cajal, Denis Toumazet, Jean-Pierre |
author_facet | Balde, Alpha Yaya Bergeret, Emmanuel Cajal, Denis Toumazet, Jean-Pierre |
author_sort | Balde, Alpha Yaya |
collection | PubMed |
description | This paper aims to prove the feasibility of a 4D monitoring solution (3D modeling and temporal monitoring) for the sandbar and to characterize the species’ role in the landscape. The developed solution allows studying the interaction between the river dynamics and vegetation using a network of low resolution and low power sensors. The issues addressed concern the feasibility of implementing a photogrammetry solution using low-resolution sensors as well as the choice of the appropriate sensor and its testing according to different configurations (image capture and storage on the sensor and/or image transmission to a centralization node) and also the detailed analysis of the different phases of the process (camera initialization, image capture, network transmission and selection of the most appropriate standby mode). We reveal that the tiny, low-cost board (ESP32-Cam) can perform a 3D reconstruction and propose using the camera’s UXGA (1600, 1200) resolution because of the quality rendering and energy consumption. A multi-node scenario based on a combined Wi-Fi and GSM relay is proposed in the study showing several years of autonomy for the system. Finally, to illustrate the energy cost of the module, we have defined a study process, where we have identified and quantified one by one the different phases of operation of the card for better energy optimization (setup, camera configuration, shooting, saving on SD card, or sending by Wi-Fi). The device is now operational for deployment on the Allier River (France). |
format | Online Article Text |
id | pubmed-9572540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95725402022-10-17 Low Power Environmental Image Sensors for Remote Photogrammetry Balde, Alpha Yaya Bergeret, Emmanuel Cajal, Denis Toumazet, Jean-Pierre Sensors (Basel) Article This paper aims to prove the feasibility of a 4D monitoring solution (3D modeling and temporal monitoring) for the sandbar and to characterize the species’ role in the landscape. The developed solution allows studying the interaction between the river dynamics and vegetation using a network of low resolution and low power sensors. The issues addressed concern the feasibility of implementing a photogrammetry solution using low-resolution sensors as well as the choice of the appropriate sensor and its testing according to different configurations (image capture and storage on the sensor and/or image transmission to a centralization node) and also the detailed analysis of the different phases of the process (camera initialization, image capture, network transmission and selection of the most appropriate standby mode). We reveal that the tiny, low-cost board (ESP32-Cam) can perform a 3D reconstruction and propose using the camera’s UXGA (1600, 1200) resolution because of the quality rendering and energy consumption. A multi-node scenario based on a combined Wi-Fi and GSM relay is proposed in the study showing several years of autonomy for the system. Finally, to illustrate the energy cost of the module, we have defined a study process, where we have identified and quantified one by one the different phases of operation of the card for better energy optimization (setup, camera configuration, shooting, saving on SD card, or sending by Wi-Fi). The device is now operational for deployment on the Allier River (France). MDPI 2022-10-08 /pmc/articles/PMC9572540/ /pubmed/36236714 http://dx.doi.org/10.3390/s22197617 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Balde, Alpha Yaya Bergeret, Emmanuel Cajal, Denis Toumazet, Jean-Pierre Low Power Environmental Image Sensors for Remote Photogrammetry |
title | Low Power Environmental Image Sensors for Remote Photogrammetry |
title_full | Low Power Environmental Image Sensors for Remote Photogrammetry |
title_fullStr | Low Power Environmental Image Sensors for Remote Photogrammetry |
title_full_unstemmed | Low Power Environmental Image Sensors for Remote Photogrammetry |
title_short | Low Power Environmental Image Sensors for Remote Photogrammetry |
title_sort | low power environmental image sensors for remote photogrammetry |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572540/ https://www.ncbi.nlm.nih.gov/pubmed/36236714 http://dx.doi.org/10.3390/s22197617 |
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