Adaptive Monitoring of Fluvial Water Quality using WSNs

In the context of smart cities, the control of environmental quality plays an increasingly important role attending to the growth in the population and consumption indices. As river waters are a fundamental resource for the population (consumption and leisure), this paper aims to explore a system for analyzing and monitoring river water quality in real-time. To this end, the use of an adaptive Wireless Sensor Network (WSN) is explored, taking river beaches along the Cávado River in Portugal as a case study.The approach adopted to implement this network involves having, in zones identified as being at risk, sensors that will measure a variety of physical-chemical, microbiological parameters and other substances considered by the Ministry of Environment as indicators of pollution. In addition, on the surrounding river beaches, Sinks (or Base Stations) will send requests to the sensors for obtaining their readings. The adaptive capacity of the adopted control algorithms allows that whenever an anomaly in the read values is detected, the frequency of the sensor readings increases in order to monitor more closely the location where the anomaly was detected. The platform used for the implementation, reconfiguration and monitoring of the communication algorithms adopted was CupCarbon, which integrates the OSM (OpenStreetMaps) API and Google Maps, which allows the development of a prototype based on real locations.