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: Hardback
Length: 157 pages
Publication date: 26 February 2022
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 proliferation of interconnected 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 intersection of 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 fundamental concepts of Machine Learning and IoT, providing a solid foundation for the subsequent chapters. It then delves into the practical applications of these technologies, showcasing how they are being used to solve real-world problems. For instance, in the healthcare sector, machine learning algorithms are employed to analyze medical images, diagnose diseases, and develop personalized treatment plans. In road safety, IoT sensors are used to monitor traffic patterns, detect accidents, and alert drivers to potential hazards.

Furthermore, the book explores the role of machine learning in enhancing the efficiency and effectiveness of agriculture by analyzing soil data, predicting crop yields, and optimizing irrigation systems. In education, IoT devices are used to provide personalized learning experiences, track student progress, and facilitate remote teaching and learning.

The book also discusses the challenges and limitations associated with the integration of Machine Learning and IoT. It highlights the need for robust security measures, data privacy, and ethical considerations to ensure the responsible and sustainable use of these technologies.

In conclusion, this book serves as a valuable resource for researchers, practitioners, and enthusiasts interested in the latest developments in Machine Learning and IoT. It provides a comprehensive and up-to-date overview of the field, covering a wide range of applications and highlighting the potential of these technologies to transform society for the better.

Weight: 436g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811650895
Edition number: 1st ed. 2022