Project description
AI for improved wastewater treatment
The wastewater sector is undergoing a major transformation as wastewater treatment plants (WWTP) become water resource recovery facilities (WRRF). Artificial intelligence (AI) supports data exploitation to accelerate this transition as the deployment of AI-powered tools in production, compared to existing treatment technologies, is much faster. This limits AI’s full use in driving the change from WWTPs to WRRFs. The EU-funded DARROW project will design (and demonstrate in an operational environment) an innovative modular and flexible data-driven AI solution to make existing WWTPs more autonomous, energy efficient, and better prepared for their transformation into WRRFs. The initiative will exploit existing AI and data analysis techniques by reducing WRRF’s energy consumption and greenhouse gas emissions, increasing resource recovery and improving water quality.
Objective
The wastewater sector is going through a profound transformation with energy efficiency and resource recovery as key priorities in wastewater treatment plants (WWTP) and these installations started to be perceived as Water Resource Recovery Facilities (WRRF).
Under this context, the exploitation of data through artificial intelligence tools with the objective of accelerating the transition of WWTP to WRRF has not been fully addressed yet. When compared to treatment technologies, the deployment of AI-powered tools in production is much faster and, therefore, provides immediate benefits. In that sense, three main barriers have been identified in this domain: i) Mechanistic mathematical models involve complex formulations and specific terminology that are difficult to understand for plant operators; ii) WRRF are harsh environments with strong impact on the quality of data; iii) Essential information in WRRFs is limited and not continuously available.
In particular, to overcome these challenges, DARROW will build and demonstrate into an operational environment, an innovative, optimised, modular, and flexible data-driven AI solution to make existing WWTP more autonomous, more energy efficient and better prepared for their transformation into WRRF. DARROW will take advantage of existing AI & Data analysis techniques with the final objective of contributing to a greener planet by: i) Reducing energy consumption of WRRF; ii) Reducing Greenhouse Gas Emissions of WRRF; iii) Increasing Resource Recovery iv) Improving water quality.To do so, DARROW gathers the necessary experience, knowledge and resources through a multi-stakeholder approach that covers the whole value chain of the project. It consists of a multidisciplinary team of 8 entities from 4 different EU countries (Spain, Belgium, Germany and Netherlands), among which, 3 RTOs, 1 university,1 NPO, and 3 SMEs to ensure market exploitation (2 industrial companies and 1 water company).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology environmental engineering water treatment processes wastewater treatment processes
- natural sciences physical sciences astronomy planetary sciences planets
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.4 - Digital, Industry and Space
MAIN PROGRAMME
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HORIZON.2.4.5 - Artificial Intelligence and Robotics
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-IA - HORIZON Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-CL4-2021-DIGITAL-EMERGING-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20018 San Sebastian
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.