Deepening Sustainability: Waste Segregation Through Advanced Deep Learning Techniques

This paper introduces an innovative waste management solution through the creation of a Smart Dustbin equipped with advanced computer vision technology for real-time image recognition and analysis. The primary objective of this system is to transform conventional waste disposal methods by automating the segregation process, thereby fostering more efficient recycling practices. The Smart Dustbin integrates sensors and cameras to identify and categorize various types of waste, such as glass, batteries, paper, plastic, and kitchen waste. The incorporation of Computer Vision technology in this Smart Dustbin holds great promise, boasting a commendable accuracy of 94% in its predictive model. This technology promises to contribute significantly to a sustainable and eco-friendly waste management ecosystem. By automating waste segregation, the system alleviates the reliance on manual labor, reduces the likelihood of human error, and encourages streamlined recycling practices, ultimately fostering a cleaner and more environmentally conscious society. The implementation of this innovative approach represents a pivotal step toward a more sustainable and efficient waste management paradigm.