• DR R N DEVENDRA KUMAR
• DEEPADHARSHINI S
• HAMSHIKA P
• DEEPIKA K

The global waste challenge brought on by the world's rapid population growth is addressed by the "WASTE CLASSIFICATION SYSTEM UTILIZING SEQUENTIAL CONVOLUTION NEURAL NETWORK" project. It uses deep learning algorithms to classify waste materials automatically, including aluminum, plastic, paper, glass, cloth, iron, and vegetable waste. An easy-to use user interface provides useful reuse recommendations. Waste management is streamlined by the system's automation, which lowers operating costs and encourages sustainable habits. It is in line with the current waste management approach, which emphasizes the importance of technology in tackling environmental concerns, and requires little human participation. This creative method seeks to promote appropriate recycling and disposal habits for a more sustainable future while also helping to manage waste in a cleaner, more economical, and efficient manner.

Waste classification, CNN, Deep learning, Adam optimizer, Waste reuse, User interface.

"WASTE CLASSIFICATION SYSTEM UTILIZING SEQUENTIAL CONVOLUTIONAL NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.f68-f73, March-2024, Available :http://www.jetir.org/papers/JETIR2403511.pdf

"WASTE CLASSIFICATION SYSTEM UTILIZING SEQUENTIAL CONVOLUTIONAL NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppf68-f73, March-2024, Available at : http://www.jetir.org/papers/JETIR2403511.pdf