Titlebook: Machine Learning Techniques for Smart City Applications: Trends and Solutions; D. Jude Hemanth Book 2022 The Editor(s) (if applicable) and

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Convolution Neural Network Scheme for Detection of Electricity Theft in Smart Grids,te as 0.948 and recall as 1 for ETD, and an overall accuracy of 92.16% was obtained. The performance analysis of the proposed model has been discussed and also been compared with the existing methodologies for ETD.

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Helping Hand: A GMM-Based Real-Time Assistive Device for Disabled Using Hand Gestures,tion and hand shape deformation as the disabled person may not always give a clear view of any shown gesture. The recognition of hand gesture is carried out by comparing the extracted features with the most likely used pre-stored features used by the disabled and elderly like the need for food, wate

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DriveSense: Adaptive System for Driving Behaviour Analysis and Ranking,of Gas Pedal, Light Status and Indicators (turn-light signal). Using these observations, machine-learning models are trained to perform real-time high-accuracy driving behaviour monitoring. Abnormal driving errors centre on human mindsets; as such a national ranking system ‘DriveScore’ has been inco

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Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles, urban traffic in emerging countries. For this purpose, 3 datasets with more than 2.5 million annotated objects are introduced using video sequences captured from UAVs from different views. An analysis of detection ability is carried out by considering traditional methods (prior to deep learning det

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Tracking Everyone and Everything in Smart Cities with an ANN Driven Smart Antenna, and corrected if there is a failure as in the case of emergency systems. This chapter discusses the application of AI in the physical layer in addressing connectivity issues of IoT in the wide area network and cellular systems landscape. The chapter address the connectivity of wireless systems of l

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