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“From wastewater analysis to cartoon case mapping”: This phrase could sum up the innovative idea of the Sewers4COVID team, which won first prize in the internationally renowned pan-European #EuvsVirusHackathon competition.
“It was the result of a team of people who have worked together for many years and that is why we were able to find an effective solution in such a short time,” Maria Papadopoulou, professor at the National Technical University of Athens, told APE-MPE. The Sewers4COVID team also included the University of Thessaly, the Dutch KWR Institute, the Spanish Eurecat and the University of Exeter of Great Britain.
But how did you come up with this idea? “The area in which we operate is water management and, in general, the most efficient management of resources, be it water, energy or land. In this context, we knew that there are studies by microbiologists who detected the virus in samples of sewage, “explains the Greek professor.
“By launching these studies, which are available to the scientific community, we thought we could build a ‘smart’ system based on the findings at the entrance to the wastewater treatment plant that will tell us in which areas there are people who have been sick , but without symptoms, “he adds.
In essence, it is an electronic platform that uses artificial intelligence methods to track the course of the virus in wastewater and therefore detect cases in near real time.
This program was developed in a pilot phase. “In order to apply it in practice, we will need funds and, of course, virus detection data in wastewater. The richer this data is, the better the platform will be able to function as an early warning system against corona or threats from similar health, “says Maria Papadopoulou.
For his part, the Rector of NTUA, Andreas Bountouvis, points out in APE-MPE that “the high distinction of the Greek team in EUvsVirusHackathon, with the participation of NTUA, through the professor of the School of Agronomy and Topographic Engineering, Mr. Maria Papadopoulou, the serious problem of COVID-19 impact prevention at the city level, by monitoring the city sewer network. “
The Rector of Metsoveio also explains that Sewers4COVID is based on machine learning techniques, which are offered for very wide applications in the treatment of pandemics. Finally, it recalls the recent success of two NTUA research teams from the School of Electrical and Computer Engineering, with the SMARTY intelligent system based on artificial intelligence methods, and supports decision-making combined with the detection of patients with 19-C and the tele-paradigm detection. .
