Garbage Collection and Segregation using Computer Vision

This research study intends to upgrade waste management with the integration of computer vision technology. This innovative system is designed to enhance the efficiency of garbage collection and segregation processes. BY utilizing advanced computer vision algorithms, the proposed system can identify and categorize various types of waste in real-time. By automated these tasks, the proposed solution aims to reduce human intervention in waste management, ensuring a more streamlined and effective process. The computer vision-based approach enables precise identification, leading to improved recycled rates and minimized environmental impact. Key features of the system include the ability to distinguish between recyclable and non- recyclable materials, promoting sustainable waste disposal practices. Additionally, the implementation includes a user-friendly interface for monitored and managed the collected data, facilitated better decision-making for waste management authorities. This research study intends to contribute to a cleaner environment by optimizing the garbage collection and segregation workflow. The utilization of computer vision not only enhances the speed and accuracy of waste identification but also establishes a foundation for smart and eco-friendly urban waste management systems.