FROM STATIC SAMPLING TO DYNAMIC INSIGHTS: THE FUTURE OF WATER QUALITY MONITORING WITH SENSORS, IOT, AND DRONES

Abstract

Traditional water quality monitoring systems face significant limitations, including labour-intensive processes, high costs, and inadequate real-time data acquisition, which lead to gaps in detecting rapid changes and contamination events. Recent advancements in sensor technology, the Internet of Things (IoT), and drones have introduced innovative solutions to address these challenges. High-sensitivity sensors, such as nano-sensors and bio-sensors, detect pollutants at trace levels. At the same time, multi-parameter platforms offer detailed insights into key indicators like turbidity, dissolved oxygen, and microbial contamination. IoT systems integrate these sensors into interconnected networks, leveraging cloud computing and artificial intelligence for real-time analysis, decision-making, and efficient monitoring. Drones with advanced sensors, including multispectral and hyperspectral cameras, provide high-resolution, spatially comprehensive data, overcoming accessibility challenges in remote and hazardous areas. These technologies collectively enable holistic and adaptive water quality monitoring frameworks. However, challenges such as high implementation costs, cybersecurity risks, and the lack of standardized protocols persist. This review critically evaluates the state of sensor technologies, IoT applications, and drone systems, highlighting their transformative potential. By addressing existing barriers and fostering interdisciplinary collaboration, these advancements pave the way for improved water resource management, environmental sustainability, and resilience against global water quality crises.