Automated trash detection system using image processing

Abstract

In this modern world any type of detection is an important task. The reason is that in this 20th century anything can be easily found through detection. Among the several types of identification, trash detection is one of the best tasks. Through trash detection, we can easily find what kind of trash or unused items are present in our environment. Through detection, we can also protect our environment from pollution very easily because through detection, we can easily tell what kind of trash service has what kind of impact on our environment and how we can take steps against this pollution. Trash products may now be strictly found and categorized by trash detection systems by using advanced sensors, machine learning algorithms, as well as computer vision techniques. These intellectual technologies act as protectors as our cities spread, making sure that responsible trash management and better-informed decision-making pave the way for a future that is greener. Although various models have been used for trash Detection, YOLO v5 and YOLO v6 perform well. One of the reasons is that we know that in trash detection we always deal with real life or real time data and the YOLO model works very well for real life data. This model provides us with a balance between accuracy and speed and creates them useful for applications. Finally, we can say that using technology we can easily keep the trash objects in separate categories and by using any type of complex category we can clean our environment and find any type of unused things around us. As a result, environment meets the genuine use Artificial intelligence.