Machine Learning and Internet of Things for Societal Issues

This book highlights recent advances in Machine Learning and IoT, discussing their applications in solving societal issues and providing useful insights for various users. It emphasizes the interconnectedness of smart devices and the use of machine learning models for data analysis and prediction in various sectors.

Format: Paperback / softback
Length: 157 pages
Publication date: 27 February 2023
Publisher: Springer Verlag, Singapore

This book delves into the latest advancements in Machine Learning and IoT, exploring their applications in addressing societal challenges and improving the lives of individuals. With the increasing interconnectedness of smart devices, the vast amounts of data generated are being analyzed and processed using machine learning models for tasks such as prediction, classification, and decision-making. These intelligent techniques have found applications in various sectors, including healthcare, road safety, agriculture, and education, revolutionizing the way we meet human needs.

This comprehensive contributed book brings together chapters that cover various aspects of the IoT domain, ranging from protocols to applications. It provides a current and comprehensive overview of the state-of-the-art in the connection between computational intelligence, machine learning, and IoT. By exploring these topics, the book aims to empower readers with the knowledge and tools necessary to leverage the power of these technologies in their respective fields.

The book begins by introducing the fundamentals of Machine Learning and IoT, providing a solid foundation for the subsequent chapters. It then delves into the application of machine learning in IoT, including topics such as data mining, pattern recognition, and predictive analytics. The authors showcase real-world examples and case studies to illustrate the practical implications of these technologies, highlighting their potential to improve efficiency, accuracy, and sustainability in various industries.

Furthermore, the book explores the role of IoT in enabling machine learning. It discusses the challenges and opportunities associated with integrating machine learning algorithms with IoT devices, such as data privacy, security, and energy consumption. The authors propose solutions and strategies to address these challenges, ensuring that the benefits of machine learning are fully realized while minimizing the associated risks.

In conclusion, this book is a valuable resource for researchers, practitioners, and students interested in Machine Learning and IoT. It provides a comprehensive and up-to-date overview of the latest advancements in these fields, covering a wide range of topics and applications. By leveraging the power of machine learning and IoT, we can unlock new possibilities for innovation, efficiency, and sustainability, shaping a better future for society.

Weight: 279g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811650925
Edition number: 1st ed. 2022