AI-Assisted Waste Reporting and Community Cleanup Platform

The AI-Assisted Waste Reporting and Community Cleanup Platform, developed under the initiative "Madurai Smart Clean", is a full-stack crossplatform mobile application designed to bridge the gap between citizens, municipal authorities, volunt eers, and administrators for efficient urban waste manag ement. Built using React Nati ve (Ex po) on the fro ntend an d Python Flask on the backend with a MySQL relational databa se, the system provides role-b ased access control for four distinct user groups. Citize ns can report geotagged wa ste via a dedicated reporting screen, track the status of their submissions, and raise emergency san itation requests. Municipal authorities revi ew and resolve complaints through a dedicated dashboard and maintain a cleanu p histo ry 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. Admini strat ors oversee the entire platform, manage es calations, allocate emergency funds, and coordinate logistics. Additional m odules includ e 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 eme rgency fund management interface. The backend is structured through nine F lask API blueprints coverin g a uthentication, complaints, authority review, administration, volunteer coordination, awareness, fund manag ement, emergency routing, and location services. Experimental evaluat ion across key functional modules demonstrates high accuracy and reliability, validating the platform as a scalable, community-driven solution for urban cleanliness management.

Authors

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-03-26
DOI
https://doi.org/10.64388/irev9i9-1715486
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Assisted Waste Reporting and Community Cleanup Platform

M. Asan Nainar, Vasantha Kumar S
Iconic Research and Engineering Journals
Municipal Solid Waste Management
article

AI-Assisted Waste Reporting and Community Cleanup Platform

M. Asan Nainar, Vasantha Kumar S
article en

Abstract

The AI-Assisted Waste Reporting and Community Cleanup Platform, developed under the initiative "Madurai Smart Clean", is a full-stack crossplatform mobile application designed to bridge the gap between citizens, municipal authorities, volunt eers, and administrators for efficient urban waste manag ement. Built using React Nati ve (Ex po) on the fro ntend an d Python Flask on the backend with a MySQL relational databa se, the system provides role-b ased access control for four distinct user groups. Citize ns can report geotagged wa ste via a dedicated reporting screen, track the status of their submissions, and raise emergency san itation requests. Municipal authorities revi ew and resolve complaints through a dedicated dashboard and maintain a cleanu p histo ry 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. Admini strat ors oversee the entire platform, manage es calations, allocate emergency funds, and coordinate logistics. Additional m odules includ e 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 eme rgency fund management interface. The backend is structured through nine F lask API blueprints coverin g a uthentication, complaints, authority review, administration, volunteer coordination, awareness, fund manag ement, emergency routing, and location services. Experimental evaluat ion across key functional modules demonstrates high accuracy and reliability, validating the platform as a scalable, community-driven solution for urban cleanliness management.

Iconic Research and Engineering JournalsVol. 9(9)
Openalex Percentile: Top 5%
Municipal Solid Waste Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.