The water resource is an essential field of economic growth, social progress, and environmental integrity. A novel solution is offered to meet water needs, distribution, and IoT-based quality management requirements. With technological growth, this paper presents an IoT-enabled Water Resource Management and Distribution Monitoring System (IWRM-DMS) using sensors, gauge meters, flow meters, ultrasonic sensors, motors to implement in rural cities. Thus, research proposes that the IWRM-DMS establish the rural demand for water and the water supply system to minimize water demand. The system proposed includes different sensors, such as the water flow sensor, the pH sensor, the water pressure valve, the flow meters, and ultrasound sensors. This water system has been developed, which addresses the demand for domestic water in the village. Machine Intelligence has been designed for demand prediction in the decision support system. The simulation results confirm the applicability of the proposed framework in real-time environments. The proposed IWRM-DMS has been proposed to analyse the water quality to ensure water distribution in a rural area to achieve less MAPE (21.41%) and RMSE(15.12%), improve efficiency (96.93%), Reliability (98.24%), enhance prediction (95.29%)), the overall performance (97.34%), moisture content ratio (7.4%), cost-effectiveness ratio (95.7%) when compared to other popular methods.

水资源是经济增长、社会进步和环境完整性的重要领域。提供了一种新颖的解决方案来满足用水需求、分配和基于物联网的质量管理要求。随着技术的发展，本文提出了一种基于物联网的水资源管理和分配监测系统 (IWRM-DMS)，该系统使用传感器、仪表、流量计、超声波传感器、电机在农村城市实施。因此，研究建议 IWRM-DMS 建立农村用水需求和供水系统，以最大限度地减少用水需求。所提出的系统包括不同的传感器，例如水流量传感器、pH 传感器、水压阀、流量计和超声波传感器。这个供水系统已经开发出来，解决了村里对生活用水的需求。机器智能专为决策支持系统中的需求预测而设计。仿真结果证实了所提出的框架在实时环境中的适用性。提议的 IWRM-DMS 已被提议用于分析水质以确保农村地区的配水以实现更少的 MAPE（21.41%）和 RMSE（15.12%），提高效率（96.93%），可靠性（98.24%），提高预测 (95.29%))、整体性能 (97.34%)、含水率 (7.4%)、成本效益比 (95.7%) 与其他流行方法相比。