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AI-Assisted Waste Reporting and Community Cleanup Platform
Subject area: Science,Engineering and Technology · Area of research: SmartCity Applications
Abstract
The AI-Assisted Waste Reporting and Community Cleanup Platform, developed under the initiative "Madurai Smart Clean", is a full-stack cross-platform mobile application designed to bridge the gap between citizens, municipal authorities, volunteers, and administrators for efficient urban waste management. Built using React Native (Expo) on the frontend and Python Flask on the backend with a MySQL relational database, the system provides role-based access control for four distinct user groups. Citizens can report geo-tagged waste via a dedicated reporting screen, track the status of their submissions, and raise emergency sanitation requests. Municipal authorities review and resolve complaints through a dedicated dashboard and maintain a cleanup history for transparency. Volunteers participate in community-driven cleanup events through the Volunteer Hub, register vehicles for waste collection, and are rewarded through a gamified leaderboard system. Administrators oversee the entire platform, manage escalations, allocate emergency funds, and coordinate logistics. Additional modules include a real-time waste hotspot map powered by React Native Maps, an Awareness Center for hygiene education, a donation gateway titled Help Madurai for community funding, and a dedicated emergency fund management interface. The backend is structured through nine Flask API blueprints covering authentication, complaints, authority review, administration, volunteer coordination, awareness, fund management, emergency routing, and location services. Experimental evaluation across key functional modules demonstrates high accuracy and reliability, validating the platform as a scalable, community-driven solution for urban cleanliness management.
Keywords
Urban Waste Management, Crowdsourced Reporting, Geo-Tagged Volunteer Hub, Emergency Management, Leaderboard, Community Cleanup.
References
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How to cite this paper
@article{1715486,
author = {Vasantha Kumar S, M. Asan Nainar},
title = {AI-Assisted Waste Reporting and Community Cleanup Platform},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {2357-2365},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715486.pdf},
abstract = {The AI-Assisted Waste Reporting and Community Cleanup Platform, developed under the initiative "Madurai Smart Clean", is a full-stack cross-platform mobile application designed to bridge the gap between citizens, municipal authorities, volunteers, and administrators for efficient urban waste management. Built using React Native (Expo) on the frontend and Python Flask on the backend with a MySQL relational database, the system provides role-based access control for four distinct user groups. Citizens can report geo-tagged waste via a dedicated reporting screen, track the status of their submissions, and raise emergency sanitation requests. Municipal authorities review and resolve complaints through a dedicated dashboard and maintain a cleanup history for transparency. Volunteers participate in community-driven cleanup events through the Volunteer Hub, register vehicles for waste collection, and are rewarded through a gamified leaderboard system. Administrators oversee the entire platform, manage escalations, allocate emergency funds, and coordinate logistics. Additional modules include a real-time waste hotspot map powered by React Native Maps, an Awareness Center for hygiene education, a donation gateway titled Help Madurai for community funding, and a dedicated emergency fund management interface. The backend is structured through nine Flask API blueprints covering authentication, complaints, authority review, administration, volunteer coordination, awareness, fund management, emergency routing, and location services. Experimental evaluation across key functional modules demonstrates high accuracy and reliability, validating the platform as a scalable, community-driven solution for urban cleanliness management.},
keywords = {Urban Waste Management, Crowdsourced Reporting, Geo-Tagged Volunteer Hub, Emergency Management, Leaderboard, Community Cleanup.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715486}
}