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@article{205664,
        author = {Atiya Rafique Dabir and Dr. Gayatri Hegde and Sushrut Valsangkar and Shreya Bangar and Pratham Shinde and Dr. Nusrat Parveen},
        title = {StreetCart: An AI-Enabled GPS-Based Real-Time Street Vendor Tracking System Using Location-Based Services},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {7528-7535},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205664},
        abstract = {Street vendors play a crucial role in the economy, yet many of them lack a virtual presence. Consequently, customers may find it hard to identify street vendors or receive any useful information from them, limiting business opportunities for both sides. Therefore, we decided to create StreetCart, which is an artificial intelligence-based mobile application that allows users to identify nearby vendors with the help of GPS. This application is developed in Kotlin for Android. As a backend, Firebase provides services like authentication, database operations, and push notifications. This system operates with two main parties – vendors who may share their location and some personal data and users who want to find certain vendors within a limited radius. Moreover, the system utilizes the K-Nearest Neighbors algorithm, allowing the app to suggest possible vendors near a person's location based on the preferences of a user. Hence, the application increases the accessibility of street vendors, improves their presence in the network, and gives small vendors access to digital technologies.},
        keywords = {Street Vendors, Location-Based Services, Firebase, Vendor Discovery, Artificial Intelligence, Recommendation System, KNN, Digital Inclusion},
        month = {June},
        }