Abstract: Water quality testing is an inevitable part of environmental monitoring. There are various parameters that affect the quality of water in the environment that can be physical, chemical or biological. Physical properties of water quality are temperature and turbidity. Chemical properties of water include parameters such as pH and dissolved oxygen. Biological parameters of water quality include algae and phytoplankton. Various papers suggest various methods for measuring the quality of water even though some are theoretical methods. For example the quality of water can be measured with the help of solar power or wireless sensor network. Depending up on the parameters monitored the accuracy of the result produced by each method may vary. This increases the scope of this topic since it consist of machine learning and data mining applications. In the suggested method, there are two components- hardware and software. Hardware component is used to collect data from various water bodies. Data collected from each water body will be saved to the database with the corresponding location. Software component is a mobile application through which users gets information about the quality of water in their surrounding area.
Keywords: Image processing, Water born diseases, Water quality monitoring, Machine Learning
| DOI: 10.17148/IJARCCE.2020.9104