Water supply monitoring system with self-powered LoRa based wireless sensor system powered by solar and hydroelectric energy harvester

•Proposal for development of a self-powered, energy-efficient device for water supply monitoring system which can operate long time using batteries power-driven by hybrid energy harvesting system.•Study and estimation of energy requisite on the water supply monitoring device for continuous operation...

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Bibliographic Details
Published in:Computer standards and interfaces 2022-08, Vol.82, p.103630, Article 103630
Main Authors: Bathre, Mukesh, Das, Pradipta Kumar
Format: Article
Language:English
Subjects:
Algorithms
Energy harvesting
Energy storage
Hybrid energy harvester
Hydro-Electric Energy
Life span
LoRa
Monitoring
Power consumption
Power management
Real time
Self-powered
Sensors
Sleep
Solar Energy
Water levels
Water supply
Water supply monitoring system
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Summary:•Proposal for development of a self-powered, energy-efficient device for water supply monitoring system which can operate long time using batteries power-driven by hybrid energy harvesting system.•Study and estimation of energy requisite on the water supply monitoring device for continuous operations like sensing, processing and communication.•Integration of different devices such as Micro-controller, ultrasonic Sensor, solenoid Valve, battery charging Module, DC-DC convertor and lora transceiver. The main highlight of this paper is to provide a self-powered, sustainable and long-life solution for sensor systems for water monitoring in real-time. The problem under consideration has been resolved by deploying a Solar-Hydroelectric hybrid energy harvesting model with a new sleep-wakeup algorithm. The proposed model collects the data of water level in the tank and battery status at real-time. As the battery has a limited power supply and cannot run for long life, the proposed hybrid harvesting model harvests and store energy into the battery for maximizing the lifespan of the sensor system, and a sleep-wakeup algorithm with dynamic active time reduces the power consumption of the system to 21 mW and increase the lifespan of the system up to 432 h on battery support. Results obtained from the simulation and experiment that the proposed model is superior to other existing algorithms in terms of different parameters.
ISSN:0920-5489
1872-7018
DOI:10.1016/j.csi.2022.103630