Grigorios Kyritsakas

Research Project: Understanding Drinking Water Quality Through Enhanced Analytics

Water companies are taking thousands monitoring samples per year from customers' taps, Service Reservoirs outlets and Water Treatment Works to measure various water parameters. Thus, enormous datasets containing thousands of measurements are created and which are stored and generally not used, except in investigations of failures that are very rare.

Therefore, the aim of this research, as its title suggests, is to investigate, with the use of Machine Learning techniques, what useful information these databases might contain regarding the water quality parameters and characteristics and their correlation with water deterioration in Drinking Water Distribution Systems.