RECS research projects
Approaching drinking water quality maintenance
Contact: Daniel Einarson, Niklas Gador, Dawit Mengistu
Drinking water quality is crucial for society, as pointed out by the Swedish Food Agency; "Water is our most important foodstuff". Therefore, it is significantly important to study the quality of the drinking water. Millions of bacterial cells inhabit drinking water treatment plants and the delivery pipes that distribute the water.
The Flow Cytometry has traditionally been used to study characteristics of blood cells. Recently, this technique has been introduced in the study of characteristics of bacteria, which improves results of analyses from several days down to ten minutes. The Flow Cytometry generates .fcs files from water samples. Each sample includes several 10 000 of rows, each row corresponding to characteristics of one possible bacterium. Furthermore, one study may contain 100 samples, putting requirements on suitable methods to deal with that amount of data.
In this project, Computer Science methods, such as Machine Learning, and Cloud Computing are used to approach the analysis of huge amounts of data representing possible bacteria at the drinking water treatment plants. To be useful in the daily operation of such treatment plants, the result has to be exposed in user friendly ways at mobile devices, putting requirements on aspects of user experiences.
Knowledge transfer partnerships (KTP)
Contact: Qinghua Wang