Medicine Detection System using BLOCKCHAIN & AI
Basireddy Sarika & Sinde Madhumitha
Students, Department of Emerging Technologies (CSE-AI&ML),
Mahatma Gandhi Institute of Technology, Hyderabad, Telangana – 500 075 bsarika_csm235a6602@mgit.ac.in smadhumitha_csm235a6607@mgit.ac.in
Guides: Mr.M.Sunil Kumar, Assistant Professor and Ms.Karuna Verma,Assistant Professor Department of Emerging Technologies,
Mahatma Gandhi Institute of Technology, Hyderabad, Telangana – 500 075
Abstract - The increasing prevalence of counterfeit and substandard medicines poses a significant threat to pub- lic health, especially in developing regions. Patients often lack reliable mechanisms to verify the authenticity of medicines, leading to serious health risks and loss of trust in healthcare systems. To address this challenge, this pa- per proposes Med-Detect, an intelligent medicine au- thentication system that leverages Artificial Intelligence and blockchain technology to identify and prevent the circulation of fake drugs.
The proposed system is implemented as a full-stack web application, consisting of a user-friendly frontend, a backend for processing verification requests, and a data- base to store medicine-related information such as batch numbers, manufacturer details, and packaging data. When a user scans or inputs medicine details, the system analyzes the data using machine learning algorithms to determine authenticity. Verified records are securely stored in a blockchain-based ledger to ensure data integ- rity, transparency, and traceability across the supply chain.
Additionally, the system incorporates a feedback module that allows users to report suspicious medicines, enabling manufacturers to improve product quality and regula- tory monitoring. The integration of AI ensures accurate detection, while blockchain prevents data tampering and enhances trust among stakeholders.
This approach enhances patient safety, enables real-time medicine verification, and improves supply chain trans- parency. It ensures users can quickly identify genuine and counterfeit medicines with ease. Future enhance- ments include mobile application support and
integration with global drug databases. Multilingual fea- tures can further improve accessibility and scalability of the system.
Keywords: Artificial Intelligence (AI), Machine Learn- ing–based Classification, Fake Medicine Detection, Blockchain-enabled Drug Traceability, Healthcare Data Security, Counterfeit Drug Prevention, Supply Chain Transparency, Smart Healthcare Technologies, and Data Integrity Management.
