Fully Automated Telemetry System for Underground Water LIDAR Sensor
This study aims to develop a wireless telemetry system for the LIDAR sensor, complementing the existing Remote Real-time Groundwater Level and Quality Sensor System used in the Philippines. The proposed setup utilizes a Garmin LIDAR-Lite v3HP sensor, an Arduino Uno microcontroller, and a sim800 and...
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Archīum Ateneo
2023
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Online Access: | https://archium.ateneo.edu/ecce-faculty-pubs/157 https://doi.org/10.1109/IoTaIS60147.2023.10346073 |
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ph-ateneo-arc.ecce-faculty-pubs-11512024-04-01T06:47:12Z Fully Automated Telemetry System for Underground Water LIDAR Sensor Demetria, Delvin Dei A. Medina, Gabriel Alfonso Voltaire J. Guico, Ma. Leonora Kwong, John Chris Galicia, Jan Kevin A Retirado, Mark Glenn F This study aims to develop a wireless telemetry system for the LIDAR sensor, complementing the existing Remote Real-time Groundwater Level and Quality Sensor System used in the Philippines. The proposed setup utilizes a Garmin LIDAR-Lite v3HP sensor, an Arduino Uno microcontroller, and a sim800 and GPRS module for data transmission to an IoT analytics platform. The energy system comprises four 6.4V solar panels, a Li-Ion 603048 Pack 3.7V 900mAh battery, and the DFRobot DFR0559 5V Solar Power Manager. Initial testing shows accurate depth readings from the LIDAR sensor with a margin of error within 10%. By enabling remote monitoring, this system can contribute to better groundwater management and conservation efforts. 2023-01-01T08:00:00Z text https://archium.ateneo.edu/ecce-faculty-pubs/157 https://doi.org/10.1109/IoTaIS60147.2023.10346073 Electronics, Computer, and Communications Engineering Faculty Publications Archīum Ateneo ground water level LIDAR water sensor Computer Sciences Digital Communications and Networking Electrical and Computer Engineering Engineering Physical Sciences and Mathematics Robotics |
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ground water level LIDAR water sensor Computer Sciences Digital Communications and Networking Electrical and Computer Engineering Engineering Physical Sciences and Mathematics Robotics |
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ground water level LIDAR water sensor Computer Sciences Digital Communications and Networking Electrical and Computer Engineering Engineering Physical Sciences and Mathematics Robotics Demetria, Delvin Dei A. Medina, Gabriel Alfonso Voltaire J. Guico, Ma. Leonora Kwong, John Chris Galicia, Jan Kevin A Retirado, Mark Glenn F Fully Automated Telemetry System for Underground Water LIDAR Sensor |
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This study aims to develop a wireless telemetry system for the LIDAR sensor, complementing the existing Remote Real-time Groundwater Level and Quality Sensor System used in the Philippines. The proposed setup utilizes a Garmin LIDAR-Lite v3HP sensor, an Arduino Uno microcontroller, and a sim800 and GPRS module for data transmission to an IoT analytics platform. The energy system comprises four 6.4V solar panels, a Li-Ion 603048 Pack 3.7V 900mAh battery, and the DFRobot DFR0559 5V Solar Power Manager. Initial testing shows accurate depth readings from the LIDAR sensor with a margin of error within 10%. By enabling remote monitoring, this system can contribute to better groundwater management and conservation efforts. |
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text |
author |
Demetria, Delvin Dei A. Medina, Gabriel Alfonso Voltaire J. Guico, Ma. Leonora Kwong, John Chris Galicia, Jan Kevin A Retirado, Mark Glenn F |
author_facet |
Demetria, Delvin Dei A. Medina, Gabriel Alfonso Voltaire J. Guico, Ma. Leonora Kwong, John Chris Galicia, Jan Kevin A Retirado, Mark Glenn F |
author_sort |
Demetria, Delvin Dei A. |
title |
Fully Automated Telemetry System for Underground Water LIDAR Sensor |
title_short |
Fully Automated Telemetry System for Underground Water LIDAR Sensor |
title_full |
Fully Automated Telemetry System for Underground Water LIDAR Sensor |
title_fullStr |
Fully Automated Telemetry System for Underground Water LIDAR Sensor |
title_full_unstemmed |
Fully Automated Telemetry System for Underground Water LIDAR Sensor |
title_sort |
fully automated telemetry system for underground water lidar sensor |
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Archīum Ateneo |
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2023 |
url |
https://archium.ateneo.edu/ecce-faculty-pubs/157 https://doi.org/10.1109/IoTaIS60147.2023.10346073 |
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