Project description
Using smartphones to catch counterfeits
Counterfeiting of manufactured goods represents a serious economic loss for industries and a health risk for customers. During the ongoing Covid-19 pandemic, counterfeit products like gloves and masks can have dangerous effects on public health. And although counterfeiting is not a new problem, there is still no solution that offers protection and reassurance to companies and customers. The EU-funded Microguard project proposes two artificial intelligence (AI)-based counterfeit detection systems that allow consumers to identify counterfeit objects with the use of a standard smartphone camera. The system uses a combination of innovative security properties including a microstructural varnish that can only be read by AI technology provided by Cypheme, a company specialised in anti-counterfeit solutions. The project will address the technical challenges of the system and prepare for commercialisation.
Objective
Counterfeiting is a crime, involving the manufacturing or distribution of goods under someone else's name, and without their permission. 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 effective solution that allows consumers to simply verify authenticity of products or for companies to effectively protect supply chains. Moreover, counterfeit goods are generally made from lower quality components that put the health and safety of consumers at risk. In these days of international emergency the news report that China has confiscated over 31 million counterfeit medical face masks that have fled the market due to the Coronavirus (COVID-19) emergency. Global retailers such as Amazon and Etsy have also reported cases.
Cypheme introduces two AI-based counterfeit detection systems that allow a consumer to determine if a product is an original branded product using only a standard smartphone camera. Microguard labels use a combination of novel security features, including a micro-structured varnish that can only be read with an artificial intelligence technology developed by Cypheme to authenticate the product. Microguard DeepTrace is an algorithm able to extract deep spectral information from printed pigments, providing a revolutionary measure of authenticity without any modification of the packaging or product. Microguard is unique in the level of security it provides and its resistance to forgery by counterfeiters. Microguard solutions have already gained market traction, trusted to protect more than €140 million worth of products. The Phase 2 project will address the technical challenges to achieve scale up and provide commercial demonstration and validation with suitable partners to facilitate full-scale market entry.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- social scienceseconomics and businessbusiness and managementcommerce
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Keywords
Programme(s)
Call for proposal
(opens in new window) H2020-EIC-SMEInst-2018-2020
See other projects for this callSub call
H2020-EIC-SMEInst-2018-2020-3
Funding Scheme
SME-2 - SME instrument phase 2Coordinator
75015 Paris
France
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.