India is the second largest country in the world, to its development on waste management it is still facing hindrances. According to estimations, India's major cities produce 10 million tons of waste. An organization may utilize a waste management system to dispose, reuse, prevent waste and reduce. Some of the methods for disposing of waste include recycling, incineration, composting, bioremediation, land-fills energy waste, and waste minimization. The daily schedule used by traditional waste management systems is both inefficient and expensive. The actions and procedures necessary from generated waste to disposing of waste are referred to as waste management. Waste disposal, collection, processing, and transportation are involved in this as it is waste control and monitoring. With the help of deep learning and image processing techniques, it is now possible to classify waste much more accurately and quickly than ever before. There is an essential step that needs to be performed before waste separation can take place: waste classification. Over the years many approaches have been presented, however they are inaccurate and time-consuming. Hence in order to overcome these issues, Design of an automated smart waste management system using CNN is presented in this work. This method will efficiently classify waste as organic and recyclable. Compared to conventional techniques, the presented approach will have high classification Accuracy.