The main goal of the project is to develop a secure, transparent system for identifying counterfeit products by scanning barcodes and verifying their authenticity through a blockchain ledger. The project responds to widespread issues in sectors such as pharmaceuticals, electronics, and luxury goods where fake products can cause financial loss and health risks. Using barcode scanning, each product’s unique identifier can be matched to a blockchain-stored record, ensuring its legitimacy. Blockchain provides immutability and traceability, allowing secure verification across supply chains. Optionally, machine learning models may be included to detect fraud patterns. By the end of the project, students will deliver a functioning application that can scan a barcode, verify product legitimacy via blockchain, and provide a secure user interface.
The project is structured into a twelve-week schedule involving progressive tasks. In the initial weeks, students will learn the foundational concepts of blockchain and barcode technologies, including Ethereum, Polygon, Hyperledger, and libraries like ZXing or Google’s Barcode API. They will download and configure open-source tools and gather relevant datasets. Midway through the project, students will focus on building the application’s core framework, incorporating modules for scanning barcodes and validating data against blockchain records. This includes smart contract development and data integrity testing. As the project continues, the application will be refined, tested, and optimized for performance. In the final phase, students will complete documentation and present their project as a team. While advanced machine learning and ERP/logistics integration are outside the project’s scope, students are encouraged to explore basic fraud detection logic if time permits.
