Abstract
Deep learning (DL), machine learning (ML), computer vision, and Internet of things (IoT) have played a significant role in innovation of new intelligent and smart systems having digital eyes and brains. These modern systems are capable of taking their decisions on their own. Earlier systems designed were only using one technology but think about the modern IoT systems having the power of computer vision, deep learning, and AI. Our proposed work tends to combine the power of DL and IoT to propose a unique waste segregation technique that comes with the least sensors and fast decision-making capability with easy installation. It easily separates organic, recyclable, and electronic waste, thus making it eco-friendly and contributing toward a greener environment. Our major contribution is the waste dataset which contains waste belonging to three categories organic, recyclable, and electronic waste along with the novel IoT-enabled smart dustbin which uses cloud technology and is power efficient.
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Divakar, S., Bhattacharjee, A., Priyadarshini, R. (2022). An IoT-Based Smart Garbage Segregation System Using Deep Learning. In: Dahal, K., Giri, D., Neogy, S., Dutta, S., Kumar, S. (eds) Internet of Things and Its Applications. Lecture Notes in Electrical Engineering, vol 825. Springer, Singapore. https://doi.org/10.1007/978-981-16-7637-6_12
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DOI: https://doi.org/10.1007/978-981-16-7637-6_12
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