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Low cost, LoRa based river water level data acquisition system
In recent years, climate change and catchment degradation have negatively affected stage patterns in rivers which in turn have affected the availability of enough water for various ecosystems. To realize and quantify the effects of climate change and catchment degradation on rivers, water level moni...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050633/ https://www.ncbi.nlm.nih.gov/pubmed/37008535 http://dx.doi.org/10.1016/j.ohx.2023.e00414 |
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author | Kabi, Jason N. wa Maina, Ciira Mharakurwa, Edwell T. Mathenge, Stephen W. |
author_facet | Kabi, Jason N. wa Maina, Ciira Mharakurwa, Edwell T. Mathenge, Stephen W. |
author_sort | Kabi, Jason N. |
collection | PubMed |
description | In recent years, climate change and catchment degradation have negatively affected stage patterns in rivers which in turn have affected the availability of enough water for various ecosystems. To realize and quantify the effects of climate change and catchment degradation on rivers, water level monitoring is essential. Various effective infrastructures for river water level monitoring that have been developed and deployed in developing countries over the years, are often bulky, complex and expensive to build and maintain. Additionally, most are not equipped with communication hardware components which can enable wireless data transmission. This paper presents a river water level data acquisition system that improves on the effectiveness, size, deployment design and data transmission capabilities of systems being utilized. The main component of the system is a river water level sensor node. The node is based on the MultiTech mDot – an ARM-Mbed programmable, low power RF module – interfaced with an ultrasonic sensor for data acquisition. The data is transmitted via LoRaWAN and stored on servers. The quality of the stored raw data is controlled using various outlier detection and prediction machine learning models. Simplified firmware and easy to connect hardware make the sensor node design easy to develop. The developed sensor nodes were deployed along River Muringato in Nyeri, Kenya for a period of 18 months for continuous data collection. The results obtained showed that the developed system can practically and accurately obtain data that can be useful for analysis of river catchment areas. |
format | Online Article Text |
id | pubmed-10050633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100506332023-03-30 Low cost, LoRa based river water level data acquisition system Kabi, Jason N. wa Maina, Ciira Mharakurwa, Edwell T. Mathenge, Stephen W. HardwareX Hardware Article In recent years, climate change and catchment degradation have negatively affected stage patterns in rivers which in turn have affected the availability of enough water for various ecosystems. To realize and quantify the effects of climate change and catchment degradation on rivers, water level monitoring is essential. Various effective infrastructures for river water level monitoring that have been developed and deployed in developing countries over the years, are often bulky, complex and expensive to build and maintain. Additionally, most are not equipped with communication hardware components which can enable wireless data transmission. This paper presents a river water level data acquisition system that improves on the effectiveness, size, deployment design and data transmission capabilities of systems being utilized. The main component of the system is a river water level sensor node. The node is based on the MultiTech mDot – an ARM-Mbed programmable, low power RF module – interfaced with an ultrasonic sensor for data acquisition. The data is transmitted via LoRaWAN and stored on servers. The quality of the stored raw data is controlled using various outlier detection and prediction machine learning models. Simplified firmware and easy to connect hardware make the sensor node design easy to develop. The developed sensor nodes were deployed along River Muringato in Nyeri, Kenya for a period of 18 months for continuous data collection. The results obtained showed that the developed system can practically and accurately obtain data that can be useful for analysis of river catchment areas. Elsevier 2023-03-17 /pmc/articles/PMC10050633/ /pubmed/37008535 http://dx.doi.org/10.1016/j.ohx.2023.e00414 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Hardware Article Kabi, Jason N. wa Maina, Ciira Mharakurwa, Edwell T. Mathenge, Stephen W. Low cost, LoRa based river water level data acquisition system |
title | Low cost, LoRa based river water level data acquisition system |
title_full | Low cost, LoRa based river water level data acquisition system |
title_fullStr | Low cost, LoRa based river water level data acquisition system |
title_full_unstemmed | Low cost, LoRa based river water level data acquisition system |
title_short | Low cost, LoRa based river water level data acquisition system |
title_sort | low cost, lora based river water level data acquisition system |
topic | Hardware Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050633/ https://www.ncbi.nlm.nih.gov/pubmed/37008535 http://dx.doi.org/10.1016/j.ohx.2023.e00414 |
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