WASTO-An Integration of Machine Learning and IOT Based Approach for Segregation of Waste

The ongoing challenges in waste management, intensified by the rapid expansion of urban populations and insufficient infrastructure, require innovative solutions. Traditional methods, such as manual waste segregation and infrequent collection, are proving inadequate in addressing the complexities of modern waste management, resulting in environmental harm and inefficient resource use. This paper presents Wasto, a cuttingedge system that integrates Machine Learning (ML) and the Internet of Things (IoT) to enhance waste management processes. The system automates waste segregation and optimizes collection routes, leading to significant improvements in both efficiency and sustainability. Wasto utilizes ML algorithms for precise waste categorization, while IoT-enabled sensors in smart bins monitor real-time waste levels, facilitating timely and efficient waste collection. This solution not only mitigates the environmental impact of waste but also contributes to the development of smart cities. Through the implementation of Wasto, we aim to provide an adaptable and effective approach to the challenges posed by urban waste management, promoting a cleaner and more sustainable future.