Smart Waste Management System Using Machine Learning
Parimala Devi M, A Priyanka, Sanjay Nesan, B Shubiksha, V Gowrishankar, T. Sathya · 2025
The rapid growth of urbanization and industrial development has resulted in a substantial rise in solid waste production, leading to serious environmental and public health concerns. Conventional waste segregation techniques are largely manual, labor-intensive, and inefficient, often causing improper disposal and increased pollution. To overcome these challenges, this project introduces an intelligent waste management system that utilizes Machine Learning and embedded technologies to automate the sorting and classification of waste.A webcam captures live images of waste materials, which are then processed using OpenCV methods including noise filtering and feature detection. These processed images are classified by a Convolutional Neural Network (CNN) into categories such as biodegradable, non-biodegradable, and recyclable. The ESP8266 microcontroller acts as the core component of the system, handling communication between various sensors, actuators, and cloud-based services.Based on the classification results from the CNN model, the controller activates stepper and servo motors to channel the waste into appropriate bins. Additionally, the system supports remote monitoring through IoT connectivity, enabling real-time data access and control. With its compact structure, energy efficiency, and potential for scalability, this solution is well-suited for implementation in smart cities and modern infrastructures. By automating waste segregation, the system reduces human effort and promotes environmentally responsible waste handling practices.