International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI Driven On-Demand Garbage Collection for Smart Cities |
|---|---|
| ABSTRACT | Traditional garbage collection systems operate with fixed schedules, often causing overflowing bins or unnecessary pickups, which lead to inefficient resource utilization and public health issues. This project aims to revolutionize urban waste management by leveraging Artificial Intelligence to create a dynamic, on-demand garbage collection system. Citizens report garbage-related issues via a digital dashboard. The data feeds into an AI-powered backend that classifies waste using image recognition and optimizes waste collection routes, dispatching trucks efficiently based on real-time demand. The proposed system enhances urban cleanliness, reduces operational costs, and promotes sustainable practices. |
| TITLE | |
| AUTHOR | SAMPADA MHASKE, POOJA BHASKAR, SUYASH NARSALE, SHRIKANT BALE, VARAD YEOLA, DR. VISHVAS KALUNGE, PROF. NAMDEO KEDARE |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311022 |
| pdf/22_AI Driven On-Demand Garbage Collection for Smart Cities.pdf | |
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