Smart Image-Based Detection and Reporting of Unclean Public Spaces Using CNN

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Authors: K Swetha, M. Shanmugathai, B Saratha, B Muthu Krishna Vinayagam
Cited by: 0

Abstract

The rate of increasing cleanliness issues has been considered as a biggest problem in today’s modern scenario. The issue has created a serious impact on the overall well-being of many citizens in both rural and urban areas. The traditional checking of cleanliness methods needs manual checking, which results in poor progress and no effective methodology. Since India is a vast country, checking each place manually is an impossible act. To overcome these drawbacks, we have introduced a software solution that uses CNN to automatically detect and report unclean public places. In regard to this, the system uses an Android mobile to take pictures of public areas. So, this would be simpler, and there is no special equipment needed. Here, these photos are fed into a CNN model that uses the patterns to identify trash. The system generates a report with the photo, GPS location, and time details when it detects a dirty area. The municipal authorities can receive the report directly. The system keeps these records for a while, so the authorities can track the patterns and identify problems in cleanliness maintenance. As per this project, mobile data collection and CNN analysis are combined regarding urban cleanliness management. This can be a very efficient solution for cities. It reduces human work and improves detection. Further, this system helps in quick action for the maintenance of clean and healthier cities. When a person uploads a photo, they will get some rewards. This will make the work more efficient. By this approach, we can conclude that if this is made as a daily technology, then it becomes easier to solve practical problems in city management.

Fields of Study & Subjects

Advanced Neural Network Applications Infrastructure Maintenance and Monitoring Waste Management and Recycling

Publication details

Journal / source
International Research Journal on Advanced Engineering Hub (IRJAEH)
Volume
4
Issue
02
Pages
466–473
Publication date
13 February 2026
Language
EN