9783032092403 - Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection: Algorithms, Frameworks, and Applications for Sustainable Healthcare (Signals an... (12 resultados)

Hardcover. Condición: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condición: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condición: new. Hardcover. This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condición: New.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications.

Hardcover. Condición: Brand New. 150 pages. 9.25x6.10x9.49 inches. In Stock.

Condición: new. Questo è un articolo print on demand.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.Presents smart technologies for sustainable health monitoring and care targeted for the elderly;Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD);Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications. 146 pp. Englisch.

Buch. Condición: Neu. Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection | Algorithms, Frameworks, and Applications for Sustainable Healthcare | Suparna Biswas | Buch | xx | Englisch | 2026 | Springer | EAN 9783032092403 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Introduction.- Introduction to Human Activity Recognition, Fall Monitoring and Detection, Health monitoring.- Fundamental concepts.- Machine Learning in Human Activity Recognition using Smartphone Sensors.- Deep Learning in Human Activity Recognition using Smartphone Sensors.- Machine Learning in Fall Detection System.- Sensor Fusion based HAR for Disease Monitoring and Prediction.- Design, Development, Deployment Strategies.- Conclusion.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 168 pp. Englisch.

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.