Development of a low-cost smart monitoring and control system for water management in rural wastewater treatment.

Ethical clearance of the study 2023FEBEFREC-STD-032Water pollution is a major global problem because of increased levels of drinking water contaminants. These pollutants can cause diseases that harm both humans and animals, thereby negatively impacting the environment. The study needs to focus on a system that can detect these pollutants early enough to prevent any pollution-related damage. This research aims to provide a low-cost system that is smart in monitoring and controlling the waters for real-time water quality management. As part of this study, consider temperature, turbidity, pH, electrical conductivity (EC), total dissolved solids (TDS), and rates of water flow as the key parameters measured by the sensors. Water pollution management is possible by continuous monitoring of these parameters, issuing warning signals, and recommending measures whenever pollution is present. The system monitors water quality by connecting an Arduino to sensors. The system follows simple rules: it analyses the data to identify any issues. If it detects contamination, it can automatically introduce chemicals to enhance the water's quality. Thingspeak, a cloud platform that maintains records and updates water quality reports, receives the data wirelessly. Additionally, the If This Then That (IFTTT) system immediately sends alert messages to users' phones upon detection of contamination. The conducted research yields compelling results, demonstrating the system's ability to continuously monitor water quality and initiate necessary actions. Furthermore, remote access, integration with other IoT applications, and enhanced robustness render this IoT-based solution useful for water quality management. The present research concludes that the use of Internet of Things-based water quality monitoring systems can ensure safe drinking water, and its implementation is both simple and feasible. In a way, it promotes the cause of public health as well as environmental conversation.

本研究之伦理审查批准文号为2023FEBEFREC-STD-032。水污染因饮用水污染物水平上升而成为全球性的重大问题，这些污染物可引发损害人类与动物的疾病，从而对环境产生负面影响。研究需聚焦于一种能够早期检测污染物，以预防任何污染相关损害的系统。本研究旨在提供一种低成本、智能监控与控制水质的实时水质管理系统。作为本研究的组成部分，考虑温度、浑浊度、pH值、电导率（EC）、总溶解固体（TDS）及水流速率等传感器测量的关键参数。通过持续监测这些参数、发出警报信号以及提出应对措施，实现水污染管理。系统通过连接Arduino至传感器来监控水质。系统遵循简单规则：分析数据以识别任何问题。若检测到污染，系统可自动添加化学物质以提升水质。Thingspeak，一云平台，负责维护记录并更新水质报告，通过无线方式接收数据。此外，If This Then That (IFTTT)系统在检测到污染时即刻向用户手机发送警报信息。所进行的研究取得了引人注目的成果，证明了系统持续监控水质并启动必要行动的能力。此外，远程访问、与其他物联网应用的集成以及增强的鲁棒性使基于物联网的水质管理解决方案变得有用。当前研究得出结论，基于物联网的水质监测系统可确保饮用水安全，其实施既简单又可行。从某种意义上讲，它促进了公共卫生事业及环境保护的进程。