Application of IoT for monitoring water quality Sungai Pusu case study - Kabbashi, Nassereldeen Ahmed; Hasan, Tahsin Fuad; Alam, Md. Zahangir; Saleh, T; Hassan Abdalla Hashim, Aisha; Nour, Abdurahman Hamid; Mohamad Sazaly, Muhammad Aniq Qawiem (IIUM Press, IIUM, 2024)
The availability of clean water, a critical natural resource essential for supporting diverse ecosystems, is increasingly threatened by sediment accumulation, which negatively impacts rivers, oceans, and coastal environments. During rainy seasons, excessive sediment, including clay particles known as total suspended solids (TSS), contaminates water, compromising its quality, altering its color, and driving up treatment costs. Additionally, sediment can carry pollutants that reduce water clarity, harm aquatic life, and disrupt ecosystem functions. Conventional water treatment methods—such as coagulation, flocculation, sedimentation, and filtration are commonly employed to address these challenges. However, traditional water quality monitoring relies heavily on laboratory tests that require specialized personnel, chemicals, and expertise, which may not always be adequate for timely and effective intervention. The advent of Internet of Things (IoT) technology offers a promising alternative by enabling the real-time collection of water quality data. Furthermore, integrating soft computing technology into water quality assessment presents a more efficient, rapid, and environmentally sustainable alternative to traditional laboratory-based approaches. This research utilizes an IoT device to monitor the performance of a water treatment system and gather data on its water quality indicators. Integrating IoT devices into water treatment systems enables real-time monitoring, automated control, and predictive maintenance, leading to improved efficiency, cost savings, and proactive water quality management. These technologies enable real-time monitoring and analysis, reducing the need for manual sampling and laboratory testing, which lowers labor and operational costs. Early detection and automated intervention help prevent costly repairs and environmental damage by addressing issues before they escalate. A novel IoT-based monitoring system of integrating soft computing into water quality assessment has been achieved.