Energy Consumption Reduction in Wireless Sensor Network-Based Water Pipeline Monitoring Systems via Energy Conservation Techniques

Valery Nkemeni (), Fabien Mieyeville and Pierre Tsafack
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Valery Nkemeni: Laboratory of Electrical Engineering and Computing, University of Buea, Buea P.O. Box 63, Cameroon
Fabien Mieyeville: University de Lyon, Université Claude Bernard Lyon 1, Ecole Centrale de Lyon, INSA Lyon, CNRS, Ampère, F-69621 Villeurbanne, France
Pierre Tsafack: Laboratory of Electrical Engineering and Computing, University of Buea, Buea P.O. Box 63, Cameroon

Future Internet, 2023, vol. 15, issue 12, 1-22

Abstract: In wireless sensor network-based water pipeline monitoring (WWPM) systems, a vital requirement emerges: the achievement of low energy consumption. This primary goal arises from the fundamental necessity to ensure the sustained operability of sensor nodes over extended durations, all without the need for frequent battery replacement. Given that sensor nodes in such applications are typically battery-powered and often physically inaccessible, maximizing energy efficiency by minimizing unnecessary energy consumption is of vital importance. This paper presents an experimental study that investigates the impact of a hybrid technique, incorporating distributed computing, hierarchical sensing, and duty cycling, on the energy consumption of a sensor node in prolonging the lifespan of a WWPM system. A custom sensor node is designed using the ESP32 MCU and nRF24L01+ transceiver. Hierarchical sensing is implemented through the use of LSM9DS1 and ADXL344 accelerometers, distributed computing through the implementation of a distributed Kalman filter, and duty cycling through the implementation of interrupt-enabled sleep/wakeup functionality. The experimental results reveal that combining distributed computing, hierarchical sensing and duty cycling reduces energy consumption by a factor of eight compared to the lone implementation of distributed computing.

Keywords: wireless sensor network-based water pipeline monitoring; green wireless sensor networks; energy conservation techniques; distributed computing; hierarchical sensing; duty cycling (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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