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.

本研究的伦理审查编号：2023FEBEFREC-STD-032
水污染因饮用水污染物浓度升高而成为全球重大问题。这些污染物可引发危害人类与动物健康的疾病，进而对环境产生负面影响。本研究需聚焦于一套能够及早检测污染物、以预防污染相关损害的系统。本研究旨在提供一套低成本的智能水监测与控制系统，用于实时水质管理。
作为研究的一部分，传感器测量的关键参数包括温度、浊度、pH值、电导率（EC）、总溶解固体（TDS）及水流速率。通过持续监测这些参数、发出预警信号并在污染发生时推荐应对措施，可实现水污染管理。
该系统通过将Arduino与传感器连接来监测水质。系统遵循简单规则：分析数据以识别问题；若检测到污染，可自动投放化学药剂以改善水质。云平台Thingspeak通过无线方式接收数据，负责维护记录并更新水质报告。此外，If This Then That（IFTTT）系统在检测到污染时会立即向用户手机发送警报信息。
研究结果令人信服，证明该系统能够持续监测水质并启动必要措施。此外，远程访问、与其他物联网（Internet of Things）应用的集成及增强的鲁棒性，使这套基于物联网的解决方案在水质管理中具有实用价值。
本研究结论表明，采用基于物联网的水质监测系统可确保饮用水安全，且其实施简单可行。从某种意义上说，它既促进公共卫生事业，也推动环境保护。