AUTOMATIC WASTE SEGREGATOR FOR SMART CITIES USING MICRO CONTROLLER

For national and municipal governments, providing efficient and long-term waste management is becoming more challenging due to the intense increase in the quantity and variety of concrete and dangerous waste because of ongoing financial activity, population growth, and industrialization. To reduce the risk to patient and public health and safety, as well as environmental risk, waste handling, transport, and disposal must be carefully handled. Waste should be separated to maximize its economic worth. There is currently no system in place for households to separate dry, other and metallic wastes. The Automated Waste Segregator (AWS), a low-cost, user-friendly option for a household waste segregation system, is recommended in this paper so that waste can be given away for treatment. The garbage is to be divided into dry, other, and metallic waste. The AWS is equipped with sensitive sensors that can sort between dry and wet trash, and with parallel connection impedance sensing technology, metal objects can be located. Experiments using the AWS have shown promising results in separating recyclables, liquids, and dry waste. Waste management is a pervasive problem in today's world and is rising continuously with a rise in urbanization. Waste management has a vibrant part to have an ecological environment. Proper waste disposal at the dumping sites has an essential part in sorting at the base level. Increases in time and more manpower is needed in order to sort waste using the traditional process. Sorting waste can be done in various methods and forms. Analyzing and classifying the garbage using image processing can be a very productive way to process waste materials. This paper aims to analyze existing research presented studies around the globe. This will enable to determine the problems, an algorithm used and method of those cited studies. It can also assess the correct algorithm to be used in a future