Abstract
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.
Acknowledgments
This paper is part of the research programme “Hydropolis: urban development and water infrastructure—towards innovative decentralized urban water management”. The programme is co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the operational programme “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF). Research Funding Programme: THALES invested in knowledge society through the European Social Fund. The work presented is part of Action 7: “Distributed, cooperative infrastructure management”.
Notes
Presented at CEST2015—14th International Conference on Environmental Science and Technology, Rhodes, Greece, 3–5 September 2015