A Systematic Review of Machine Learning Approaches for Trash Classification

In the fast-moving environment everyone handles different types of trash. A common man to large industries produces trash and it is accumulating everywhere. Recycling the trashes to reduce the source product requirement necessities huge manual work which reduces the recycle conversion efficiency. Since the manual worker needs to pick up the trash and categorize the trash into the respective category will take more time and also it is a tedious process. Instead of manual sorting for recycling, automatic trash classification systems are used These systems classify the trashes based on their texture, material, and natural characteristics. Various hardware and software modules are incorporated into the trash classification process. This study presents a systematic literature review of different trash classification systems and discusses the features of existing systems. Based on the analysis, a detailed summary is presented in the last part of the research work which will help the research community to develop efficient trash classification systems.