Nature-inspired search method for IoT-based water leakage location detection system

Abstract

Detecting water leakage and reporting the leakage timely is one of the challenges faced by water distributing companies in developing nations. This paper employs a nature-inspired search method for optimal location search to water leakage sources for Ghana Water and Sewage Services Company. The nature-inspired method aid in mapping IoT-edge computing devices used by the water and sewage workers, especially in the cities and urban areas, to find and locate leaked pipelines. Once, a water and sewage worker receive a trigger from any location that there are leakages, the algorithm generates the location data which automatically processes the distance, geographic location, and direction. In this paper, a nature-inspired algorithm based on the behaviour of a Kestrel bird was used as the mapping function. The developed algorithm was tested and evaluated using pre-defined and random locations based on their latitudes and longitudinal data. The proposed algorithm was evaluated against BAT algorithm. Findings from the data indicated that the proposed KSA used as mapping function, was successful in providing the optimal distance after receiving water leakage geographic location data from IoT edge computing devices.