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Machine Intelligence and Data Analytics for Sustainable Future Smart CitiesНазвание: Machine Intelligence and Data Analytics for Sustainable Future Smart Cities
Автор: Uttam Ghosh, Yassine Maleh
Издательство: Springer
Год: 2021
Страниц: 413
Язык: английский
Формат: pdf (true)
Размер: 15.2 MB

This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and Big Data models and techniques. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and data analytics for sustainable future smart city applications.

The subjects of the smart city and machine intelligence are the sources of many claims, hopes and fears. In concrete terms, it is a set of challenges, made up of threats and opportunities, relating to the production of cities and the management of urban services. Dealing with these challenges requires a better balance between the performance of the artificial and real expectations. Smart and sustainable cities need an intelligent infrastructure that is stable, secure, reliable and interoperable, capable of supporting a huge volume of ICT-enabled applications and services. In recent years, machine intelligence approaches have emerged as powerful computational models and have shown significant success to deal with a massive amount of data in unsupervised settings. Machine intelligence techniques influence various technologies because they offer an effective learning representation and allow the system to learn features from data without explicitly designing them. With the emerging technologies, the Internet of Things (IoT), wearable devices, cloud computing and data analytics offer the potential to acquire and process a tremendous amount of data from the physical world. Machine intelligence algorithms help efficiently leverage IoT and Big Data aspects to develop personalized services in sustainable smart cities.

More specifically, the book contains 21 chapters classified into three pivotal sections: the first part presents the role and importance of machine intelligence and data analytics techniques for sustainable future smart cities. The second part describes and analyzes various applications of machine intelligence and data analytics in smart cities, such as Internet of Things, vision systems, and healthcare in sustainable smart cities. The third part introduces the machine (ML) and Deep Learning (DL) techniques in smart cities’ surveillance and cybersecurity.

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