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@article{202384,
        author = {Talha Yusufi and Prasanna Gadve and Krrish Khune and Rajsee Marjive and Mrunmayee Bedenkar},
        title = {NeatF1: An AI-Driven Civic Engagement Platform for Automated Garbage Detection, Reporting, and Gamified Community Cleanup},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {8024-8026},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202384},
        abstract = {Urban waste accumulation poses serious threats to the environment and public health. Existing municipal reporting mechanisms suffer from delayed response cycles and low citizen participation rates. This paper presents NeatF1, a civic engagement website that leverages computer vision and artificial intelligence to automate the detection of accumulated garbage from user-submitted photographs. Upon successful detection, the system geo-tags the waste location and uploads it to a public feed where users can upvote, downvote, or report the post. Users can subsequently upload video proof of cleaning the garbage and earn points upon admin/moderator approval. Contributors receive 5 points for reporting and 50 points for approved cleanup videos. A public leaderboard displays top contributors along with their social handles. The platform is community-driven; gamification ensures active participation.},
        keywords = {citizen science; civic technology; computer vision; convolutional neural networks; environmental monitoring; gamification; garbage detection; smart city.},
        month = {May},
        }