Project description
New sensors to maintain good water quality
The food industry is notorious for the vast amounts of water it consumes. For instance, washing in the fruit and vegetable sector accounts for 50 % of water use. While optimising water consumption is crucial, ensuring the quality of the water used to wash and process food products is just as important. The EU-funded FOODWATERH2020 project is developing a fully automated and compact solution for monitoring water quality to protect consumers from harmful bacteria like E. coli, salmonella and listeria. It uses special sensors combined with an embodied artificial intelligence software based on deep learning technology. Not only will this solution recover up to 99 % of food process water, it will also remove up to 99 % of water contaminants.
Objective
Every year in Europe, 3,6 Gm3 of fresh water is used for the food industry. This represent a cost of up to 14,5 G€/year considering both cost of fresh water and water disposal. Depending on the water quality used to wash and process food products, harmful bacteria (e.g. E.Coli Salmonella, Listeria) can be rapidly contaminate food and expose consumers to serious illnesses. On the other side, around 88 Mtons of food waste are generated annually in Europe with associated costs estimated at 143G€ and carbon footprint of 170Mt of CO2. Current solutions for water recycling are either using old technics such as settling ponds (80% of the market) or recycling industrial systems (20% of the market). They show several important inconvenient such as high ground footprint, low water recovery rate, low contaminant removal rate, high energy consumption, non-automatized system, etc. FOODWATERH2020 is the first fully automatized and compact solution which monitor constantly the water quality thanks to its highly precise multi sensors combined with an embodied IA software based on Deep Learning Technology which allow to: 1) recover up to 99% of food process water, 2) Reduce up to 10 times current costs of food process water (down to 0,40-0,80€/m3), 3) Remove up to 99% of water contaminant such as non-systemic pesticides (from food surface), pathogens, clay and sand, 4) provide a 100% reliability on food safety by always respecting food standards and eliminating food returns to our clients, 5) increase up to 54% the shelf life of food products, 6) Reduce by 30-35% the energy footprint compared to current compact solutions and 7) Reduce the ground footprint up to 20 times compare to ponding systems. VAM WaterTech B.V. (Nederland) is a well-established engineering SME founded in 1995 with an annual turnover of 5,9 M€ (in 2018 – forecasting 6,6M€ for 2019), 19,5 FTE employees and with an orderbook full until April 2020.
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 waste management waste treatment processes recycling
- natural sciences earth and related environmental sciences hydrology
- engineering and technology other engineering and technologies food technology food safety
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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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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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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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.
SME-1 - SME instrument phase 1
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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) H2020-EIC-SMEInst-2018-2020
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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.
4454 AC BORSSELE
Netherlands
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.