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Towards Improving the Resilience of the Urban Water Cycle through the implementation of digital tools based on Machine Learning models and Water Regeneration Technologies. (DIGI4WATER)

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Towards Improving the Resilience of the Urban Water Cycle through the implementation of digital tools based on Machine Learning models and Water Regeneration Technologies. (DIGI4WATER)
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Towards Improving the Resilience of the Urban Water Cycle through the implementation of digital tools based on Machine Learning models and Water Regeneration Technologies. (DIGI4WATER)
Start date: 1 January, 2022
End date: 31 December, 2024
Code: TED2021-129969B-C31

Participants

Functional Units “Water treatment” and “Environmental analysis”

Contacts

I. Oller (isabel.oller@psa.es)

I. Polo (inmaculada.polo@psa.es)

Funds:

Ministry of Science and Innovation. Call 2021 – “Ecological Transition and Digital Transition Projects”.(TED2021-129969B-C31)

Current Situation:

In progress

Summary

The main objective of DIGIT4WATER is to create the bases for the implementation of a decision and technology design support tool based on machine learning models. Such models will be fed by an open database on physicochemical characteristics of raw MWWTP influent and effluent, as well as advanced regeneration tertiary treatments tested at laboratory and pilot plant scale for compliance with the new European regulation (EU 2020/741) on water reuse. Special attention will be paid to the elimination of ARB & ARGs as well as the DBPs prevention commonly produced in conventional disinfection processes. A Decision Support Tool (DST) and an Early-Warning System (EWS) will be also designed based on the models developed. The main objective of the DST is to design advanced tertiary treatment techniques for water treatment facilities, selecting the most adequate parameters. The EWS is intended to create alarms when the quality of reclaimed water is below the minimum legal and sanitary requirements depending on the final reuse purposes.

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