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WEARABLE COMPUTING: FROM MODELING TO IMPLEMENTATION OF WEARABLE SYSTEMS BASED ON BODY SENSOR NETWORK
Título:
WEARABLE COMPUTING: FROM MODELING TO IMPLEMENTATION OF WEARABLE SYSTEMS BASED ON BODY SENSOR NETWORK
Subtítulo:
Autor:
FORTINO, G
Editorial:
JOHN WILEY
Año de edición:
2018
ISBN:
978-1-118-86457-9
Páginas:
2018
99,95 € -10,0% 89,96 €

 

Sinopsis

This book provides the most up-to-date research and development on wearable computing, wireless body sensor networks, wearable systems integrated with mobile computing, wireless networking and cloud computing

This book has a specific focus on advanced methods for programming Body Sensor Networks (BSNs) based on the reference SPINE project. It features an on-line website (http://spine.deis.unical.it) to support readers in developing their own BSN application/systems and covers new emerging topics on BSNs such as collaborative BSNs, BSN design methods, autonomic BSNs, integration of BSNs and pervasive environments, and integration of BSNs with cloud computing. The book provides a description of real BSN prototypes with the possibility to see on-line demos and download the software to test them on specific sensor platforms and includes case studies for more practical applications.
 Provides a future roadmap by learning advanced technology and open research issues

 Gathers the background knowledge to tackle key problems, for which solutions will enhance the evolution of next-generation wearable systems

 References the SPINE web site (http://spine.deis.unical.it) that accompanies the text

 Includes SPINE case studies and span topics like human activity recognition, rehabilitation of elbow/knee, handshake detection, emotion recognition systems

Wearable Systems and Body Sensor Networks: from modeling to implementation is a great reference for systems architects, practitioners, and product developers.

Giancarlo Fortino is currently an Associate Professor of Computer Engineering (since 2006) at the Department of Electronics, Informatics and Systems (DEIS) of the University of Calabria (Unical), Rende (CS), Italy. He was recently nominated Guest Professor in Computer Engineering of Wuhan University of Technology on April, 18 2012 (the term of appointment is three years). His research interests include distributed computing and networks, wireless sensor networks, wireless body sensor networks, agent systems, agent oriented software engineering, streaming content distribution networks, distributed multimedia systems, GRID computing.

Raffaele Gravina received the B.Sc. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2004 and 2007, respectively. Here he also received the Ph.D. degree in computer engineering. He´s now a Postdoctoral research fellow at University of Calabria. His research interests are focused on high-level programming methods for WSNs, specifically Wireless Body Sensor Networks. He wrote almost 30 scientific/technical articles in the area of the proposed Book. He is co-founder of SenSysCal S.r.l., a spin-off company of the University of Calabria, and CTO of the wearable computing area of the company.

Stefano Galzarano received the B.S. and M.S. degrees both in computer engineering from the University of Calabria, Rende, Italy, in 2006 and 2009, respectively. He is currently pursuing a joint Ph.D. degree in computer engineering with University of Calabria and Technical University of Eindhoven (The Netherlands). His research interests are focused on high-level programming methods for wireless sensor networks and, specifically, novel methods and frameworks for autonomic wireless body sensor networks.



Preface

Acknowledgements

Chapter 1: Body Sensor Networks

1.1 Introduction

1.2 Background

1.3 Typical m-Health system architecture

1.4 Hardware architecture of a sensor node

1.5 Communication Medium

1.6 Power consumption considerations

1.7 Communication standards

1.8 Network Topologies

1.9 Commercial sensor node platforms

1.10 Bio-physiological signals and sensors

1.11 BSN Application domains

1.12 Summary

1.13 References

Chapter 2: BSN Programming Frameworks

2.1 Introduction

2.2 Developing BSN applications

2.2.1 Application- and platform-specific programming

2.2.2 Automatic code generation

2.2.3 Middleware-based programming

2.2.4 Programming approaches comparison

2.3 Programming abstractions

2.4 Requirements for BSN framework

2.5 BSN programming frameworks

2.5.1 Titan

2.5.2 CodeBlue

2.5.3 RehabSPOT

2.5.4 SPINE

2.5.5 SPINE2

2.5.6 C-SPINE

2.5.7 MAPS

2.5.8 DexterNet

2.6 Summary

2.7 References

Chapter 3: Signal Processing In-Node Environment

3.1 Introduction

3.2 Background

3.3 Motivations and Challenges

3.4 The SPINE Framework

3.4.1 Architecture

3.4.2 Programming perspective

3.4.3 Optional SPINE modules

3.4.4 High-Level Data Processing

3.4.5 Multi-Platform Support

3.5 Summary

3.6 References

Chapter 4: Task-oriented Programming in BSNs

4.1 Introduction

4.2 Background

4.3 Motivations and Challenges

4.3.1 Need for a platform-independent middleware

4.3.2 Challenges in designing task-oriented framework

4.4 SPINE2 overview

4.5 Task-oriented programming in SPINE2

4.6 SPINE2 node-side middleware

4.7 SPINE2 Coordinator

4.8 SPINE2 communication protocol

4.9 Developing application in SPINE2

4.10 Summary

4.11 References

Chapter 5: Autonomic Body Sensor Networks

5.1 Introduction

5.2 Background

5.3 Motivations and Challenges

5.4 State-of-the-art

5.5 SPINE-*: task-based autonomic architecture

5.6 Autonomic physical activity recognition

5.7 Summary

5.8 References

Chapter 6: Agent-oriented Body Sensor Networks

6.1 Introduction

6.2 Background

6.2.1 Agent-oriented Computing and Wireless Sensor Networks

6.2.2 Mobile Agent Platform for Sun SPOT (MAPS)

6.3 Motivations and Challenges

6.4 State-of-the-art: Description and Comparison

6.5 Agent-based Modeling and Implementation of BSNs

6.6 Engineering Agent-based BSN Applications: a Case Study

6.7 Summary

6.8 References

Chapter 7: Collaborative Body Sensor Networks

7.1 Introduction

7.2 Background

7.3 Motivations and Challenges

7.4 State-of-the-art

7.5 A reference architecture for Collaborative BSN

7.6 C-SPINE: a CBSN architecture

7.6.1 Inter-BSN Communication

7.6.2 BSN Proximity Detection

7.6.3 BSN Service Discovery

7.6.4 BSN Service Selection & Activation

7.7 Summary

7.8 References

Chapter 8: Integration of Body Sensor Networks and Building Networks

8.1 Introduction

8.2 Background

8.2.1 Building Sensor Networks and Systems

8.2.2 Building Management Framework

8.3 Motivations and Challenges

8.4 Integration Layers

8.5 State-of-the-art: Description and Comparison

8.6 An Agent-oriented Integration Gateway

8.7 Application Scenarios

8.8 Summary

8.9 References

Chapter 9: Integration of Wearable and Cloud Computing

9.1 Introduction

9.2 Background

9.2.1 Cloud Computing

9.2.2 Architectures for Sensor Stream Management

9.3 Motivations and Challenges

9.3.1 BSN Challenges

9.3.2 BSN/Cloud computing Integration Challenges

9.4 Reference Architecture for Cloud-Assisted Body Sensor Networks

9.4.1 Sensor Data Collection

9.4.2 Sensor Data Management

9.4.3 Scalable Processing Framework

9.4.4 Persistent Storage

9.4.5 Decision-Making Process

9.4.6 Open Standards and Advanced Visualization

9.4.7 Security

9.5 State-of-the-art: Description and Comparison

9.5.1 Integration of WSNs and Cloud computing

9.5.2 Integration of BSNs and Cloud computing

9.5.3 A comparison

9.6 BodyCloud: A Cloud-based Platform for Community BSN Applications

9.7 Engineering BodyCloud Applications

9.7.1 ECGaaS: Cardiac Monitoring

9.7.2 FEARaaS: Basic Fear Detection

9.7.3 REHABaaS: Remote Rehabilitation

9.7.4 ACTIVITYaaS: Community Activity Monitoring

9.8 Summary

9.9 References

Chapter 10: Development methodology for BSN systems

10.1 Introduction

10.2 Background

10.3 Motivations and Challenges

10.4 SPINE-based Design Methodology

10.4.1 A Pattern-driven Application-level Design

10.4.2 System Parameters

10.4.3 Process schema

10.5 Summary

10.6 References

Chapter 11: SPINE-based Body Sensor Networks Applications

11.1 Introduction

11.2 Background

11.3 Physical Activity Recognition

11.3.1 Related Work

11.3.2 A SPINE-Based Activity Recognition system

11.4 Step Counter

11.4.1 Related Work

11.4.2 A SPINE-based Step Counter

11.5 Emotion Recognition

11.5.1 Stress Detection

11.5.2 Fear Detection

11.6 Handshake Detection

11.6.1 Related Work

11.6.2 A SPINE-Based Handshake Detection System

11.7 Physical Rehabilitation

11.7.1 Related Work

11.7.2 SPINE Motor Rehabilitation Assistant

11.8 Summary

11.9 References

Chapter 12: SPINE at Work

12.1 Introduction

12.2 SPINE 1.x

12.2.1 How to install SPINE 1.x

12.2.2 How to use SPINE

12.2.3 How to run a simple desktop application using SPINE1.3

12.2.4 SPINE Logging capabilities

12.3 SPINE2

12.3.1 How to install SPINE2

12.3.2 How to use the SPINE2 API

12.3.3 How to run a simple application using SPINE2

Index