Project description
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.
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 (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health scienceshealth sciencespublic health
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologymaterials engineering
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
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Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
75015 PARIS
France
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.