Vision based Intelligent Garbage Collection and Sorting System

摘要

Waste disposal has become a vital environmental challenge due to the world’s population expansion, especially in developing countries where timely collection and efficient garbage segregation are major issues. Insufficient segregation techniques lead to the disposal of recyclables in addition to regular trash, which lowers recycling rates and produces dangerous situations. Groundwater contamination and environmental damage can result from the production of harmful chemicals and gases, such as methane, from mixed waste. Numerous technological approaches, including intelligent trash cans and self-contained robots capable of identifying, gathering, and organizing rubbish on their own, have been put forth to solve this issue.To enhance garbage disposal, the Vision-Based Intelligent Garbage Collection and Sorting System provides an innovative automated solution. The system incorporates a Raspberry Pi, servo motors, a camera, ultrasonic sensors, and a GSM module to optimize the processes of garbage identification, sorting, and segregation. Using ultrasonic sensors, the device initially finds waste within a predetermined range. After the waste is identified, a camera takes a picture of it, which the Raspberry Pi uses machine learning techniques to process. Based on visual cues including shape, texture, and color, these algorithms are trained to classify waste into groups like plastic, metal, paper, or biological components.Accurate segregation is ensured by servo motors controlling a mechanical arm to direct waste into the proper bins after sorting. In addition, the system uses ultrasonic sensors to continuously check garbage levels and, when bins are almost full, immediately notifies waste management staff via a GSM module. This reduces the requirement for manual sorting management during overflow prevention, timely collection, and overall cleanliness and hygiene environments.