Multi-criteria Fuzzy Decision Support for Smart Water Conservation and Monitoring
Keywords:
Environmental monitoring, smart cities, Fuzzy inference system, Fuzzy logic, Intelligent decision support, Internet of things (IoT), Multi-criteria decision-makingAbstract
Water scarcity, deteriorating water quality, and inefficient resource utilization have become major global concerns due to rapid urbanization, industrial expansion, climate variability, and increasing population growth. Conventional water monitoring systems generally rely on fixed threshold values and deterministic decision-making approaches, which often fail to address uncertainty and ambiguity associated with environmental data. This study proposes a Multi-Criteria Fuzzy Decision Support System (MCFDSS) for intelligent water conservation and monitoring by integrating Internet of Things (IoT) sensing technologies with fuzzy logic-based decision-making. The proposed framework continuously acquires real-time information from distributed water quality and quantity sensors, including pH, turbidity, Total Dissolved Solids (TDS), water level, flow rate, and temperature. A fuzzy inference mechanism evaluates multiple conflicting criteria simultaneously to determine water quality status, conservation priority, and resource utilization recommendations under uncertain conditions. The framework further supports intelligent decision-making for reservoir management, irrigation scheduling, leakage detection, and sustainable water distribution. The proposed methodology improves decision reliability by accommodating linguistic variables and expert knowledge while reducing dependence on rigid threshold-based rules. Comparative analysis indicates enhanced decision accuracy, improved water utilization efficiency, and greater adaptability to dynamic environmental conditions. The proposed fuzzy decision support framework offers a scalable, cost-effective, and sustainable solution suitable for smart cities, agricultural irrigation systems, industrial water management, and remote rural regions where reliable water resource management is essential for long-term environmental sustainability.
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