Integration of Internet of Things for Haemodialysis Water Quality Monitoring Systems

The Internet of Things (IoT) transforms healthcare by enabling real-time monitoring and predictive maintenance, especially in haemodialysis centres where water quality is essential for patient safety. This study explores the use of IoT sensors at four critical stages of the water treatment process—raw intake, pre-treatment, treatment, and post-treatment—to measure factors such as temperature, conductivity, pressure, flow, and vibration. The system helps reduce human error and supports compliance with health standards by automating data collection and allowing remote access. Compared to previous studies, this research is different in that it uses machine learning to predict water quality changes and maintenance needs, offering a forward-looking approach to system reliability. The key findings include reduced downtime, consistent water quality, and better patient outcomes. Nevertheless, challenges are still present, such as the reliance on stable internet access and potential inaccuracies in sensor calibration. Future work could address these issues by exploring offline functionalities and improving sensor accuracy. Despite these limitations, this study highlights the potential of IoT to transform haemodialysis water treatment practices, setting a new standard for safety and operational efficiency.