Smart Garbage Collection Management System for Karnataka Using Machine Learning


Authors : Srushti T.; Swarnalatha

Volume/Issue : Volume 10 - 2025, Issue 8 - August


Google Scholar : https://tinyurl.com/5hdr5vmb

Scribd : https://tinyurl.com/4a8wat3h

DOI : https://doi.org/10.38124/ijisrt/25aug928

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Abstract : This project introduces a Smart Garbage Collection and Complaint Management System built using python and the Streamlit framework, tailored for municipalities in Karnataka. The system combined GPS-based tracking, data analytics, and active citizen participation to tackle the challenges of urban waste management. Citizens can easily register and log in to report complaints with location details, monitor the progress of their requests, and access area-wise cleanliness ratings. In addition, they receive useful waste classification insights and seasonal tips encourage eco-friendly practices. For municipal administrators, the platform provides a secure, role-based system to handle complaints, monitor dustbin status, evaluate area cleanliness, and manage staff activities. Features such as worker assignment, shift scheduling, salary management, and instant notifications help improve coordination and accountability. A dedicated notification system also ensures smooth communication between municipal authorities and ground-level workers. Moreover, real-time vehicle tracking, waste analytics, and cleanliness metrics give administrators a complete overview of sanitation activities across the city. By bridging the gap between citizens and municipal authorities, this system not only improves transparency and operational efficiency but also fosters greater community involvement in keeping cities clean. Ultimately, it supports the vision of “Clean Karnataka, Green Karnataka” and serves as a scalable framework that can be adapted for other cities to promote sustainable and smart urban waste management.

Keywords : Smart City, Waste Management, Streamlit, Complaint Tracking, Vehicle GPS, Citizen Feedback, Urban Cleanliness.

References :

  1. Python Software Foundation. Python Language Reference, version 3.x. Available at: https://www.python.org
  2. Streamlit Inc. Streamlit Documentation. Available at: https://docs.streamlit.io
  3. Pandas Development Team. Pandas: Python Data Analysis Library. Available at: https://pandas.pydata.org
  4. Folium Developers. Folium: Python Data, Leaflet.js Maps. Available at: https://python-visualization.github.io/folium
  5. Balamurugan, D., & Priya, R. (2020). Waste Classification using Machine Learning Techniques. Proceedings of the International Conference on Sustainable Computing and Communication Systems, 112–118.
  6. Government of India. Swachh Bharat Mission Guidelines. Ministry of Housing and Urban Affairs, 2019.

This project introduces a Smart Garbage Collection and Complaint Management System built using python and the Streamlit framework, tailored for municipalities in Karnataka. The system combined GPS-based tracking, data analytics, and active citizen participation to tackle the challenges of urban waste management. Citizens can easily register and log in to report complaints with location details, monitor the progress of their requests, and access area-wise cleanliness ratings. In addition, they receive useful waste classification insights and seasonal tips encourage eco-friendly practices. For municipal administrators, the platform provides a secure, role-based system to handle complaints, monitor dustbin status, evaluate area cleanliness, and manage staff activities. Features such as worker assignment, shift scheduling, salary management, and instant notifications help improve coordination and accountability. A dedicated notification system also ensures smooth communication between municipal authorities and ground-level workers. Moreover, real-time vehicle tracking, waste analytics, and cleanliness metrics give administrators a complete overview of sanitation activities across the city. By bridging the gap between citizens and municipal authorities, this system not only improves transparency and operational efficiency but also fosters greater community involvement in keeping cities clean. Ultimately, it supports the vision of “Clean Karnataka, Green Karnataka” and serves as a scalable framework that can be adapted for other cities to promote sustainable and smart urban waste management.

Keywords : Smart City, Waste Management, Streamlit, Complaint Tracking, Vehicle GPS, Citizen Feedback, Urban Cleanliness.

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Paper Submission Last Date
30 - November - 2025

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