GreenSort: A Vision-Centric Robotic System for Smart Waste Collection and Environmental Protection using SSD MobileNet V2 and the TACO Dataset

As part of sustainability, care for the environment is necessary to ensure health of everyone. Sadly, pollution and particularly stray waste have turned out to be a major problem for humans and wildlife. All the litter, which is not properly disposed, adds to the destruction of the environment. This research discusses a new solution to this problem: a trash picking robot. The proposed robot uses a visual collection system to detect and collect nearby trash, making it a great tool for multi-area cleaning. Robotics has changed our lives in many ways, saving time, money, and helping in many areas. This robot is designed to analyse the size, shape, and position of items to accurately, pick them up and transfer them to different types of waste classification. The implementation begins by identifying pollution problems and exploring existing solutions. Multiclass segregation of different types of wastes using SSD MobileNet V2 on TACO Dataset is performed. The TensorFlow model provides an accuracy of 96%. Ultimately, the goal is to show that technology plays an important role in keeping our world clean and green.