This academic article appeared in MDPI’s Electronics journal in April 2021. The report presents an in-depth literature survey of machine learning methods as an optimization tool for regular wireless sensor networks and Internet of Things (WSN-IoT) nodes deployed in smart city applications. The survey results indicate that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications.
Keywords: Access Controls, Architecture/Engineering, Artificial Intelligence (AI), Communications, Control & Monitoring Equipment/Sensors, Energy Efficiency/Management, Internet of Things (IoT), Post-COVID-19, Protocols/Standards, Renewable Energy, Smart Cities, Smart Grid, Training

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