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@article{209110,
        author = {Namrathaa Vaishnavi Shetty and Sangeetha and Bindu and Joshna Grace Pinto and Savan Shetty},
        title = {Blockchain-Assisted Decentralized Roommate Matching with Verifiable Consent and Tamper-Proof Trust Mechanisms},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {712-722},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209110},
        abstract = {This paper presents a blockchain-assisted decentralized roommate matching platform designed to provide intelligent compatibility analysis, secure consent management, and trustworthy roommate interactions. The proposed system combines a React-based web interface, a Spring Boot backend, a MySQL database, a Python-based machine learning module, and Ethereum smart contracts to provide an integrated roommate matching workflow. Users can create profiles and specify lifestyle preferences such as sleep schedule, food habits, cleanliness level, smoking and drinking preferences, work type, budget, and personality characteristics. These preference attributes are processed and converted into suitable numerical representations for compatibility analysis using the K-Nearest Neighbors (KNN) algorithm. The KNN model identifies users with similar lifestyle characteristics and generates a compatibility score to recommend suitable roommate matches. In addition to intelligent matching, the platform incorporates blockchain technology to provide verifiable consent between matched users. Once a user sends a roommate request and the other user accepts it, the consent transaction is recorded through a Solidity-based smart contract on the Ethereum blockchain, with the transaction hash and timestamp providing a verifiable record of the agreement. Conventional user information, preferences, matching results, and feedback are maintained through the application database, while blockchain is utilized for consent-related records requiring tamper-resistant verification. The system also provides user authentication, profile management, roommate recommendations, consent management, and feedback mechanisms through a unified web interface. By integrating machine learning-based compatibility prediction with blockchain-based consent verification, the proposed platform aims to improve the transparency, reliability, and trustworthiness of roommate matching compared with conventional preference-based matching approaches.},
        keywords = {Blockchain, K-Nearest Neighbors, roommate matching, machine learning, smart contracts, Ethereum, compatibility prediction, verifiable consent, trust management, decentralized application.},
        month = {October},
        }