An IoT Intensive AI-integrated System for Optimized Surface Water Quality Profiling

Abstract

Surface water is heavily exposed to contamination as this is the ubiquitous source for the majority of water needs. This situation is exaggerated by excessive population, heavy industrialization, rapid urbanization, and ad-hoc monitoring. Comprehensive measurement and knowledge extraction of surface water pollution is therefore pivotal for ensuring safe and hygienic water use. However, current process of surface water quality profiling involves laboratory-based manual sample collection and testing, which is tardy, expensive, error-prone, and untraceable. This paper, therefore presents the design and development of an IoT integrated water quality profiling system that possesses a novel plug-and-play physical layer for the sensor actuation, and an AI powered fog computing based cloud application layer for remote water quality parameter measurement and data acquisition, remote data logging, monitoring and control, with data analytic for critical reasoning and decision making