The increasing amount of waste in landfill has created a serious environmental problem which demands a more reliable solution in handling the collection of wastes. To this date, recycling is one of the solutions to manage the waste as it collects and processes recyclable materials into new products instead of throwing the trash to the landfill. However, the consciousness of recycling in our society is still devastatingly lower than expected as people are faced with many challenges that impede them to recycle. One of the challenges is to segregate the waste according to its group. People are still having difficulty to clearly distinguish recyclable materials due to the lack of recycling knowledge. Thus, this paper aims to develop a system that can separate the waste automatically and channel them to the proper bins. To do that, a camera is used to capture the image of the waste. Then, image classification using deep learning model is used to classify different types of wastes. The developed model is then embedded in Raspberry Pi and a servo motor is used to direct the waste to the respective bins for real-world implementation. Experimental results show that the proposed system can identify the categories of waste within the accuracy of 77–85%. This system is expected to deliver the importance of recycling and cultivate recycling practices to the public and finally reduced waste generation on land.
