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Real-Time CCTV Based Garbage Detection for Modern Societies using Deep Convolutional Neural Network with Person-Identification.

Authors :
Raza, Syed Muhammad
Hassan, Syed Ghazi
Hassan, Syed Ali
Soo Young Shin
Source :
Journal of Information & Communication Convergence Engineering; Jun2024, Vol. 22 Issue 2, p109-120, 12p
Publication Year :
2024

Abstract

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22348255
Volume :
22
Issue :
2
Database :
Complementary Index
Journal :
Journal of Information & Communication Convergence Engineering
Publication Type :
Academic Journal
Accession number :
178141922
Full Text :
https://doi.org/10.56977/jicce.2024.22.2.109