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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Smart City Traffic Patterns Prediction Using Machine Learning,es, the strain generated by traffic jams, sleep, and workouts induced by time spent in traffic. Since motorists cannot see the entire traffic system, the urban traffic system must be anticipated in order to sensitize residents about their mobility choices and the subsequent impact on the environment

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Learning Analytics for Smart Classroom System in a University Campus,n the class. LA is thus being incorporated in different educational settings such as in smart classrooms where students’ behaviour and performance are observed and analyzed. This chapter presents LA in a smart classroom using predictive models to assess formative assessment, attendance, and behaviou

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SysML-Based Design of Autonomous Multi-robot Cyber-Physical System Using Smart IoT Modules: A Case world via sensors and actuators in a feedback loop. Indeed, CPS systems became available everywhere, such as the team of autonomous mobile robots with prescribed tasks and missions. This chapter proposes a detailed architectural model-based design for a cyber-physical system of autonomous multi-diff

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Vulnerabilities and Ethical Issues in Machine Learning for Smart City Applications,logy, however, brings with it new concerns and obstacles. Many aspects of smart cities rely on data transfer, storage and learning technology and cyber-security issues have an impact on how they operate. First part of this chapter is focused on different aspects of vulnerabilities of machine learnin