An ontology framework for decentralized water management and analytics using wireless sensor networks

The implementation of decentralized water management (DWM) systems as a mainstream practice is impeded by the knowledge gaps on their actual performance in a range of development types and settings. On the other hand, wireless sensor networks (WSN) provide a capable platform for low cost, high performance and real-time monitoring. By bringing together the strengths of WSN technology and distributed, reactive, knowledge management and representation, implemented as a dual-layer ontology framework, this work provides a holistic approach to the management of DWM systems. Low-level real-time knowledge such as sensor observations (water consumption, water quality and soil quality) is represented directly in the ontology while high-level knowledge, e.g. about scheduling precision irrigation and about meeting grey water demand in the household, is inferred through low-level knowledge by means of rule-based reasoning. Ultimately, the proposed system aims to: control the grey water reuse process, detect and react to any failures and unusual events (e.g. floods, bursts, pump failures), analyze and improve the efficiency of water reuse, and predict the optimal time for maintenance, thus improving system availability.