Management of water uses requests to harmonize demands and needs which are getting more and more complex and sophisticated especially with the growing urbanization. Dhaka, the capital of Bangladesh requests a larger number of services for its inhabitants and expects, at the same time, to limit investments in order to constrain the tax pressure.
Hence the need for optimization appears at various levels and requests the widespread of monitoring strategies. In parallel and during the past decades, modeling systems for hydrology, hydraulics, and water quality have been used as stand-alone products and were used in order to produce an analysis of a current situation and to generate forecasts according to different horizons. The current situation, characterized by the fast increase of monitoring devices mainly in the urban environments, requests an integration of the modeling tools into Information Systems (IS) that are now dedicated to the global management of urban environments and related services.
Hydro-metric Decisions Supports Systems (DSSs) integrate the various components and operate in a sustainable perspective. The current demand is targeting classical monitoring outputs (real-time monitoring) and request forecasts based on models (analytics) and providing sufficient information for efficient management. So accordingly, we here have developed an Intelligent IoT-based Water Quality Monitoring system that is based on M2M. The system here receives the input sensor where TOC, DOC, ORP, UV254, Turbidity, Chlorine, pH, Connectivity, Pressure connected. Where machine learning algorithm employed for predicting the Water Quality based on trained data set. The trained data set and predicted data are stored in a Cloud server for access via their mobile phone. This has resulted in a complete automated Water Quality Monitoring system employing IoT Technologies where devices communicate among themselves in predicting the Water Quality for the residential area. This proves that the water quality can be monitored automatically with no human involvement.
Water Quality monitoring is very much needed as it is consumed by residents. Traditional water quality monitoring and some of the technology-based Water Quality got a lot of challenges. In addition, there is no intelligence in existing water Quality Monitoring for analysis and prediction. Now with the advent of Machine to Machine communication (M2M) which involves devices to communicate among themselves in taking action and this can be deployed over large geographical area compared to small area as seen in previous system.