A Systematic Review of Water Quality Monitoring: Technologies, Trends, Challenges, and Future Directions

Water quality monitoring is essential for sustainable environmental management and public health protection. Conventional monitoring approaches are limited by sparse spatial coverage and delayed laboratory analysis. This study presents a PRISMA-based systematic review of emerging water quality monitoring technologies, focusing on the integration of Internet of Things (IoT) sensor networks, remote sensing platforms, machine learning algorithms, and biosensor technologies. A total of 103 scientific studies published between 2020 and 2025 were analyzed. The results indicate that IoT systems enable real-time data acquisition, remote sensing provides large-scale spatial monitoring, machine learning enhances predictive modelling, and biosensors offer high sensitivity for contaminant detection. However, challenges related to data integration, sensor reliability, scalability, and infrastructure remain significant barriers. A conceptual framework for integrated monitoring systems is proposed, along with a future research roadmap. The findings provide insights into the development of intelligent and sustainable water quality monitoring systems.