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In today’s fast-paced world, we are facing an escalating problem in ensuring efficacious and sustainable management of waste. This is a result of rapid increase in urbanization and industrialization. India ranks second in the world after China, in terms of population and this rising population has given way to an increase in the use of resources and ultimately resulting in a proportional increase in waste generation. The central and local governments along with the Municipal Corporations of our country have proposed numerous refinements regarding the manual management of waste. However, due to the inefficiency in the management of waste, environment and human health has begun to deteriorate. Thus, waste management has gained popularity as an issue that requires immediate attention and action. Waste segregation is the most important step in this process. This paper proposes an automated system that segregates waste into 6 categories based on norms accepted globally. This automatic waste segregator uses a modern classification method known as Convolutional Neural Networks to classify the waste into various categories. This system paves way to better recycling and reuse processes that helps in efficient waste management.
Waste segregation, Automation, Convolution Neural Networks, Recyclable waste, Non-recyclable waste
Currently, waste management is a very common term and is used to describe the series of activities from waste generation to disposal that can help sort the innumerable problems due to improper waste disposal that includes adverse effects on human health and the environment. A survey conducted in the year 2007 showed that in India alone, almost 0.14 Million ton of garbage is generated daily. Of the total Municipal Solid Waste generated in India only 83% of what is generated is collected but only 29% of the collected waste is treated and 55% of the waste produced in India is organic . The most common method of waste disposal is open dumping at landfill sites. This method has serious effects on the environment and most importantly on the lives people living close to a landfill site.
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