Efficient waste management is a serious concern in today’s world. The rapid accumulation of plastic waste on both land and sea has become a global environmental issue. Plastics are synthesized using non-renewable fossil fuels and decompose only at a slow pace. With landfills becoming scarce for plastic disposal, recycling becomes significant for handling waste plastics. Polyethylene Terephthalate(PET) plastic stands out as valuable, with the highest scrap value among various plastic waste types, due to its cost-effectiveness and eco-friendly characteristics. The performance and excellence of recycling processes significantly depend on the precision and purity of sorting methods. Consequently, sorting waste plastics is vital in various waste management techniques. This paper explores diverse deep learning(DL) strategies for identifying and sorting plastics, drawing from existing literature.