This paper explores location-based product authentication in a situation where only the past locations of products that flow in a supply chain are known. We transform location-based authentication into a pattern recognition problem and investigate different solutions based on machine-learning techniques. The proposed solutions are studied with computer simulations that model the flow of genuine and counterfeit products in a generic pharmaceutical supply chain. The results suggest that machine-learning techniques could be used to automatically identify suspicious products from the incomplete location information.
The 3rd International Conference on the Internet of Things (IoT2012) will include a highly selective dual-track program for technical papers, accompanied by reports on business projects from seasoned ...
Mark Weiser first proposed Pervasive Computing two decades ago and we've explored the space of his ideas in that time. It's time to explore new wild and crazy -- "hot" -- ideas! The goal of PerHot is ...
As part of their research for GS1, members of the Auto-ID Labs research network have presented a recent update at GS1's Industry and Standards Event in Brooklyn, March 2011.
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