Publications Repository - Gdańsk University of Technology

In this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern, such as hospitals, schools, and so on. The proposed spectroscopy method supported with machine learning for real-time detection of infectious agents will eliminate the need for time-consuming processes, which contribute to reducing costs. The spectra in range 220–750 nm were used for the study. We achieve accuracy of our prediction model up to 68% with using only absorption spectrophotometer and machine learning. The use of such a set makes the method universal, due to the possibility of using many different detectors.

Authors

• mgr inż. Patryk Sokołowski link open in new tab ,
• Kacper Cierpiak link open in new tab ,
• prof. dr hab. inż. Małgorzata Szczerska link open in new tab ,
• dr inż. Maciej Wróbel link open in new tab ,
• prof. dr hab. inż. Aneta Łuczkiewicz link open in new tab ,
• dr hab. inż. Sylwia Fudala-Książek link open in new tab ,
• dr inż. Paweł Wityk link open in new tab