Project description DEENESFRITPL The first artificial intelligence capable of detecting counterfeit products The trade in counterfeit and pirated goods is booming. It’s a major challenge in an innovation-driven global economy, threatening sustainable business models based on intellectual property and patenting. It is claimed that counterfeit products and in particular counterfeit medicine kill more people than malaria. In the EU, counterfeited and pirated products account for about 5 % of imports. The EU-funded Microguard project will bring to market a counterfeit detection system that requires only a mobile telephone’s camera. The system, which is the first of it's kind to be released, uses an artificial intelligence capable of analysing the microstructure of printed materials and spotting any tiny mistakes made by counterfeiters. Show the project objective Hide the project objective Objective Counterfeiting is a crime, involving the manufacturing or distribution of goods under someone else's name, and without their permission. Counterfeit goods are generally made from cheap and lower quality component that put the health and safety of consumers at risk.According to an International Chamber of Commerce the total value of counterfeit and pirated goods globally is around €1.77 trillion. Each year EU companies lose €83 billion in sales due to counterfeited products. Although the counterfeiting has been a problem for decades, there is no solution yet for it fighting at consumer level. Cypheme introduces a counterfeit detection system that allows a consumer to determine if a product is an original branded product using only a cell phone camera. The system uses a micro structured varnish that can only be read with a neural network technology developed by Cypheme to authenticate the product. The system can be applied directly on the product, making it harder for counterfeiters to copy. During the feasibility assessment, a minimum viable product will be defined, a go-to-market strategy and a supply chain will be established, as well as further development plan will be drafted. Within the overall innovation project, Cypheme aims to adapt the varnish application to metal, glass and plastic and upscale the neural recognition software; optimize the user interface for brand owners and consumers; perform a quality demonstration and validation of the system at different goods. Fields of science medical and health scienceshealth sciencespublic healthengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensorsengineering and technologymaterials engineeringengineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phonesnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-SMEInst-2018-2020-1 Funding Scheme SME-1 - SME instrument phase 1 Coordinator CYPHEME Net EU contribution € 50 000,00 Address Rue bargue 27 75015 Paris France See on map Region Ile-de-France Ile-de-France Paris Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 21 429,00
