Connected Sensors, Innovative Sensor Deployment and Intelligent Data Analysis for Online Water Quality Monitoring

Abstract

The sensor technology for water quality monitoring (WQM) has improved during recent years. The cost-effective sensorised tools that can autonomously measure the essential physical -chemical and biological (PCB) variables are now readily available and are being deployed on buoys, boats and ships. Yet, there is a disconnect between the data quality, data gathering and data analysis due to the lack of standardized approaches for data collection and processing, spatio-temporal variation of key parameters in water bodies and new contaminants. Such gaps can be bridged with a network of multiparametric sensor systems deployed in water bodies using autonomous vehicles such as marine robots and aerial vehicles to broaden the data coverage in space and time. Further, intelligent algorithms (e. g. artificial intelligence (AI)) could be employed for standardised data analysis and forecasting. This paper presents a comprehensive review of the sensors, deployment and analysis technologies for WQM. A network of networked water bodies could enhance the global data intercomparability and enable WQM at global scale to address global challenges related to food (e.g., aqua/agriculture), drinking water, and health (e.g., water borne diseases).