ArticleSensors (Basel, Switzerland)2020
A Distributed Computing Solution Based on Distributed Kalman Filter for Leak Detection in WSN-Based Water Pipeline Monitoring.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Evaluation of Green Strategies for Prolonging the Lifespan of Linear Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2024Review
- RSSI-WSDE: Wireless Sensing of Dynamic Events Based on RSSI.Sensors (Basel, Switzerland) · 2024Article
- Machine Learning Model for Leak Detection Using Water Pipeline Vibration Sensor.Sensors (Basel, Switzerland) · 2023Article
- Energy-Aware QoS MAC Protocol Based on Prioritized-Data and Multi-Hop Routing for Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2022Article
- Constructing LDPC Codes with Any Desired Girth.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
3 authors.
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Abstract
Wireless Sensor Network (WSN) applications that favor more local computations and less communication can contribute to solving the problem of high power consumption and performance issues plaguing most centralized WSN applications. In this study, we present a fully distributed solution, where leaks are detected in a water distribution network via only local collaborations between a sensor node and its close neighbors, without the need for long-distance transmissions via several hops to a centralized fusion center. A complete approach that includes the design, simulation, and physical measurements, showing how distributed computing implemented via a distributed Kalman filter improves the accuracy of leak detection and the power consumption is presented. The results from the physical implementation show that distributed data fusion increases the accuracy of leak detection while preserving WSN lifetime.
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