  To protect the environment from trash pollution, especially in societies, and
to take strict action against the red-handed people who throws the trash. As
modern societies are developing and these societies need a modern solution to
make the environment clean. Artificial intelligence (AI) evolution, especially
in Deep Learning, gives an excellent opportunity to develop real-time trash
detection using CCTV cameras. The inclusion of this project is real-time trash
detection using a deep model of Convolutional Neural Network (CNN). It is used
to obtain eight classes mask, tissue papers, shoppers, boxes, automobile parts,
pampers, bottles, and juices boxes. After detecting the trash, the camera
records the video of that person for ten seconds who throw trash in society.
The challenging part of this paper is preparing a complex custom dataset that
took too much time. The dataset consists of more than 2100 images. The CNN
model was created, labeled, and trained. The detection time accuracy and
average mean precision (mAP) benchmark both models' performance. In
experimental phase the mAP performance and accuracy of the improved CNN model
was superior in all aspects. The model is used on a CCTV camera to detect trash
in real-time.
