Automata Bin

Waste management and segregation is one of the most essential components of the sanitary process but the people are still unaware about the types of wastes and its method of disposal. To ensure the masses gets awareness as well as the garbage gets segregated and disposed correctly. This work focuses on designing a smart IoT based dustbin which scans the image of the garbage in real-time and compare it with the pre-defined data on the system. Then, it is classified into different categories by utilizing a combination of computer vision and an image classification machine learning algorithm based on Tensor Flow library together. The real time image of the trash is compiled by the ML model using OpenCV library. This model works by cross referencing the given data to the labelled dataset of the model. Since this model utilizes labelled data for classification the results produced will be more accurate compared to other such methods. The model is trained using 100 epochs and hence results in more accurate results. The segregation of waste at the initial step can reduce the burden on the garbage collectors, improves the recycling rate and promotes sustainability.