Low cost, LoRa based river water level data acquisition system

被引:3
|
作者
Kabi, Jason N. [1 ]
Maina, Ciira Wa [1 ,2 ]
Mharakurwa, Edwell T. [2 ]
Mathenge, Stephen W. [2 ]
机构
[1] Dedan Kimathi Univ Technol, Ctr Data Sci & Artificial Intelligence, POB PRIVATE BAG, Nyeri 10143, Kenya
[2] Dedan Kimathi Univ Technol, Dept Elect & Elect Engn, POB,PRIVATE BAG, Nyeri 10143, Kenya
来源
HARDWAREX | 2023年 / 14卷
关键词
Water level data; Sensor node power analysis; Sensor node deployment; Wireless sensor networks;
D O I
10.1016/j.ohx.2023.e00414
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 degrada-tion 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 acqui-sition system that improves on the effectiveness, size, deployment design and data trans-mission 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 pro-grammable, low power RF module - interfaced with an ultrasonic sensor for data acquisi-tion. 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. & COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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页数:25
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