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IoT Sensor-Based Activity Recognition: Human Activity Recognition de Md Atiqur Rahman Ahad

IoT Sensor-Based Activity Recognition: Human Activity Recognition: Intelligent Systems Reference Library, cartea 173

Autor Md Atiqur Rahman Ahad, Anindya Das Antar, Masud Ahmed
en Limba Engleză Hardback – 31 iul 2020
This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things. 

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Specificații

ISBN-13: 9783030513788
ISBN-10: 3030513785
Ilustrații: XXXIV, 189 p. 63 illus., 52 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Cham, Switzerland

Cuprins

Introduction on Sensor-based Human Activity Analysis: Background.- Basic Structure for Human Activity Recognition Systems: Preprocessing and Segmentation.

Textul de pe ultima copertă

This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things.

Caracteristici

Highlights recent research in the field of Human Activity Recognition (HAR) based on sensors Presents a comprehensive study and addresses various aspects of human activity recognition based on wearable, environmental, and smartphone sensors Includes a list of sensing devices, sensors, and applications that can be used for collecting activity data Provides a comprehensive analysis of ca. 80 benchmark datasets, which includes information on sensors, attributes, activity classes, etc., and sums up several types of sensor-based daily activities, medical activities, fitness activities, device usage, fall detection, and hand gesture data