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E-grāmata: Smart Sensors Networks: Communication Technologies and Intelligent Applications

Edited by (Associate Professor, Aletheia University, Taiwan), Edited by (Professor, Tunghai University, Taiwan), Edited by (Full Professor of Computer Science, Universitat Politčcnica de Catalunya (UPC), Barcelona, Spain)
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Smart Sensors Networks: Communication Technologies and Intelligent Applications explores the latest sensor and sensor networks techniques and applications.

Smart Sensors Networks shows how networked wireless sensors are used to monitor and gather intelligence from our surrounding environment. It provides a systematic look at the unique characteristics of wireless sensor networks through their usage in a broad range of areas, including elderly healthcare, energy consumption, industrial automation, intelligent transportation systems, smart homes and cities, and more.

The book shows how sensor-networks work and how they are applied to monitor our surrounding environment. It explores the most important aspects of modern sensors technologies, providing insights on the newest technologies and systems for operating them. Smart Sensors Networks contributes to the growing portfolio of possible techniques and strategies for implementing effective sensor-related solutions, serving as an entry point for understanding the fundamental differences between the various sensor technologies and their use in for different scenarios.

  • Numerous specific use-cases throughout show practical applications of concepts
  • Contributions from leading experts around the around globe
  • Collects in one place for researchers and practitioners the last thinking on an emerging topic
  • Addresses the security and privacy issues inherent in sensor deployment

Papildus informācija

Shows what sensors networks are, how they work, and why they are valuable for numerous scientific and technological applications
Contributors xiii
About the Editors xvii
Foreword xix
Preface xxi
Acknowledgments xxvii
PART 1 IoT AND NETWORK COMMUNICATION SYSTEMS
Chapter 1 IoT Technologies: State of the Art and a Software Development Framework
3(16)
Takahiro Inui
Masaki Kohana
Shusuke Okamoto
Masaru Kamada
1.1 Introduction
3(1)
1.2 Current Status of IoT
3(4)
1.2.1 Example of IoT Devices
4(1)
1.2.2 Standardization Trend
5(1)
1.2.3 IoT Technologies
6(1)
1.3 IoT Securities
7(1)
1.4 A Software Framework for IoT
8(8)
1.4.1 Overview of the Software Framework
8(1)
1.4.2 Islay
9(2)
1.4.3 Raspberry Pi and a Linux Scheduler
11(2)
1.4.4 Improvement of the Dynamic Timer
13(3)
1.5 Conclusions
16(3)
References
16(1)
Acronyms and Glossary
17(2)
Chapter 2 Increasing Effective Transmissions Using Smart Antenna Systems
19(34)
Li-Ling Hung
Sheng-Han Wu
2.1 Introduction
19(1)
2.2 Background and Literature Review
20(1)
2.3 Problem under Study and Its Statement
21(9)
2.3.1 Network Assumptions
22(3)
2.3.2 Problem Formulation
25(3)
2.3.3 Objectives
28(2)
2.4 The Proposed Approach
30(13)
2.4.1 Defining the Clusters in the Concerned Environment
30(1)
2.4.2 Determining the Routing Paths for Each Transmission Pair
31(7)
2.4.3 Schedule Parallel Transmissions Pairs
38(5)
2.5 Implementation
43(2)
2.6 Evaluation
45(3)
2.6.1 Routing Evaluations
45(2)
2.6.2 Scheduling Evaluations
47(1)
2.7 Conclusions
48(1)
2.8 Future Works and Challenges
49(4)
References
50(1)
Acronyms and Glossary
51(2)
Chapter 3 A DTN-Based Multi-hop Network for Disaster Information Transmission
53(14)
Shinya Kitada
Goshi Sato
Yoshitaka Shibata
3.1 Introduction
53(1)
3.2 Related Works
54(1)
3.3 The Proposed System
54(3)
3.4 Network Protocol
57(3)
3.4.1 System Architecture
59(1)
3.5 Prototype System and Performance
60(4)
3.5.1 Performance Evaluation and Discussions
61(3)
3.6 Conclusions
64(3)
Acknowledgment
65(1)
References
65(1)
Acronyms and Glossary
65(2)
Chapter 4 Intelligent Energy Management for Environmental Monitoring Systems
67(30)
Petr Musilek
Michal Prauzek
Pavel Kramer
James Rodway
Tomas Barton
4.1 Introduction
67(1)
4.2 Environmental Monitoring Systems
68(3)
4.2.1 Structure of Environmental Monitoring Systems
68(1)
4.2.2 Sensors for Environmental Monitoring
69(2)
4.3 Power Supplies for Terrestrial Environmental Monitoring Systems
71(4)
4.3.1 Components of Power Supplies
72(1)
4.3.2 Energy Harvesting Systems
73(2)
4.4 Energy Management Strategies
75(4)
4.4.1 Power Management Techniques
75(3)
4.4.2 From Techniques to Strategies
78(1)
4.5 Computational Intelligence in EMS Energy Management
79(8)
4.5.1 Pressure-Based Forecasting of Solar Energy Availability
80(1)
4.5.2 Energy Management in EMS Using Fuzzy Control
81(2)
4.5.3 In-node Data Compression
83(2)
4.5.4 Entropy-Based Clustering Hierarchy
85(2)
4.6 Conclusions and Future Work
87(10)
References
89(4)
Acronyms and Glossary
93(4)
PART 2 DATA STREAMING, PROCESSING, AND ANALYSIS
Chapter 5 Smart Sensor Data Stream Delivery Technologies
97(26)
Tomoya Kawakami
Yoshimasa Ishi
Tomoki Yoshihisa
Yuuichi Teranishi
5.1 Introduction
97(1)
5.2 P2P-Based Technologies
98(10)
5.2.1 Addressed Problems
98(3)
5.2.2 Load Distribution Method
101(2)
5.2.3 Evaluation
103(5)
5.3 Technologies on the Cloud
108(11)
5.3.1 Addressed Problems
108(2)
5.3.2 Load Distribution Method
110(2)
5.3.3 Node Assignment and Construction of Delivery Paths
112(3)
5.3.4 Evaluation
115(4)
5.4 Discussion
119(1)
5.5 Conclusion
120(3)
Acknowledgments
120(1)
References
121(1)
Acronyms and Glossary
122(1)
Chapter 6 Scalable Processing of Massive Traffic Datasets
123(20)
Sergio Di Martino
Simon Kwoczek
Wolfgang Nejdl
6.1 Introduction
123(1)
6.2 Background and State of the Art
124(1)
6.3 The Problem Description
125(3)
6.3.1 The Data Sources
126(1)
6.3.2 Description of the Use Cases
127(1)
6.4 The Proposed Architecture
128(3)
6.4.1 The Import Component
128(2)
6.4.2 The Access Component
130(1)
6.4.3 The Database Representation Component
130(1)
6.5 The Databases
131(5)
6.5.1 The Relational Database Model
131(1)
6.5.2 The NoSQL Data Management Model
132(4)
6.6 Preliminary Experimental Results
136(2)
6.6.1 Performance of Data Insertion
136(1)
6.6.2 Data Extraction Performance
137(1)
6.7 Conclusions and Lesson Learned
138(5)
Acknowledgments
139(1)
References
139(1)
Acronyms and Glossary
140(3)
Chapter 7 Bounded Error Data Compression and Aggregation in Wireless Sensor Networks
143(16)
Ray-I Chang
Meng-Han Li
Polon Chuang
Jeng-Wei Lin
7.1 Introduction
143(1)
7.2 Background and Literature Review
144(2)
7.3 The Proposed Approach
146(4)
7.4 Performance Evaluation
150(4)
7.5 Conclusion and Future Works
154(5)
References
155(2)
Acronyms and Glossary
157(2)
Chapter 8 Application of Data Analysis in Wellness and Health Sensor Network Environment
159(30)
Jian-hua Yeh
Wei-ting Chen
8.1 Introduction
159(2)
8.1.1 Background
159(1)
8.1.2 Problem Statement
160(1)
8.1.3 Research Contributions
161(1)
8.1.4 Article Outline
161(1)
8.2 Literature Review
161(6)
8.2.1 Introduction
161(1)
8.2.2 Definition of Health Care
162(1)
8.2.3 Wellness and Health Sensor Network Systems
163(1)
8.2.4 Components of WHSNS
163(3)
8.2.5 Review of Methodologies on Health Analysis and Prediction
166(1)
8.2.6 Advantages and Current Limitations of the WHSNS
166(1)
8.3 Deployment of the Wellness and Health Sensor Network Systems
167(7)
8.3.1 Introduction
167(1)
8.3.2 Brief Description of WHSNS
168(1)
8.3.3 Application of WHSNS in Wellness and Health Sensing
169(2)
8.3.4 Network Communication of WHSNS
171(1)
8.3.5 Topological Architecture of WHSNS
171(1)
8.3.6 Integration and Analysis of Real-Time Heterogeneous Sensor Data
171(2)
8.3.7 The Software System Used to Obtain Sensor Data
173(1)
8.3.8 Other Demands
173(1)
8.3.9 Summary
173(1)
8.4 Case Study: Application of WHSNS in Health Analysis and Prediction
174(8)
8.4.1 Introduction
174(1)
8.4.2 Health Analysis and Prediction-Oriented System Design
175(3)
8.4.3 How to Use Health Analysis and Prediction to Check the Physical Health of Care Recipients
178(1)
8.4.4 Optimization Procedure
179(2)
8.4.5 System Installation
181(1)
8.5 Conclusion and Future Works
182(7)
References
183(1)
Acronyms and Glossary
184(5)
PART 3 HEALTHCARE APPLICATIONS
Chapter 9 Electronic Health System: Sensors Emerging and Intelligent Technology Approach
189(16)
Heru Susanto
9.1 Introduction
189(1)
9.2 Literature Review
190(3)
9.2.1 The Role of ICT for Intelligent Apps of Health System
190(2)
9.2.2 ICT Impacts for Intelligent Apps of Health System
192(1)
9.3 Discussion
193(7)
9.3.1 ICT Emerging Technology
193(1)
9.3.2 The Intelligent Sensors Apps
194(4)
9.3.3 Usability of Intelligent Sensors Apps
198(2)
9.4 Conclusion
200(5)
References
201(1)
Acronyms and Glossary
202(3)
Chapter 10 Fall Detection and Motion Classification by Using Decision Tree on Mobile Phone
205(34)
Fang-Yie Leu
Chia-Yin Ko
Yi-Chen Lin
Heru Susanto
Hsin-Chun Yu
10.1 Introduction
205(1)
10.2 Background
206(2)
10.3 Problem Definition
208(3)
10.3.1 Research Methods
208(2)
10.3.2 Signal Processing
210(1)
10.4 Proposal Approach
211(4)
10.4.1 Features of Six Falling Movements
211(1)
10.4.2 Classifiers
211(3)
10.4.3 Our Classification Tool
214(1)
10.5 Evaluation
215(19)
10.5.1 Ceiling Effect
215(1)
10.5.2 Evaluation Criteria
216(3)
10.5.3 Signal Analysis
219(15)
10.6 Conclusions and Discussion
234(1)
10.7 Future Studies
234(5)
References
235(2)
Acronyms and Glossary
237(2)
Chapter 11 Approaching Hardware Solutions for Massive E-Health Sensor Data Analysis
239(22)
Mario Barbareschi
Sara Romano
Antonino Mazzeo
11.1 Introduction
239(3)
11.2 Related Work
242(1)
11.3 Architectural Overview
243(9)
11.3.1 High Performance Decision Tree Prediction
246(1)
11.3.2 Implementing a Fully Parallel DT Predictor
247(1)
11.3.3 Considerations on Area Occupancy and Time
248(3)
11.3.4 Low Area Decision Tree Prediction
251(1)
11.4 Preliminary Approach Evaluation
252(2)
11.4.1 High Performance Architecture
252(1)
11.4.2 Low Overhead Architecture
252(2)
11.5 Conclusion
254(7)
References
256(2)
Acronyms and Glossary
258(3)
Chapter 12 A Method for Estimating Stress and Relaxed States Using a Pulse Sensor for QOL Visualization
261(32)
Sayaka Akiyama
Yuka Kato
12.1 Introduction
261(2)
12.2 Literature Review
263(2)
12.2.1 Method Using Subjective Data
263(1)
12.2.2 Method Using Sensing Data
264(1)
12.2.3 Method Using Vital Information
264(1)
12.3 QOL Visualization System
265(1)
12.4 Problem Definition
266(1)
12.5 The Proposed Approach
267(6)
12.5.1 Overview
267(1)
12.5.2 Calculating LF/HF
268(3)
12.5.3 Calculating SRV
271(2)
12.6 Implementation
273(2)
12.7 Evaluation
275(8)
12.7.1 Experimental Conditions
275(1)
12.7.2 Experimental Results
276(7)
12.8 Conclusions
283(1)
12.9 Future Works and Challenges
284(9)
Appendix 12.A AR Model
285(1)
12.A.1 Determining the Order
286(1)
12.A.2 Estimating the Parameters
286(1)
References
287(2)
Acronyms and Glossary
289(4)
PART 4 LIVING LAB --- EVERYDAY ACTIVITIES
Chapter 13 Proximity-Based Service: An Advanced Way of Extending Human Proximity Awareness
293(16)
Akihiro Fujihara
13.1 Introduction
293(2)
13.2 Proximity-Based Services
295(1)
13.3 Proximity Beacon System for Indoor Route Guidance
296(5)
13.3.1 About Memory Space for Recording Beacon Detections
297(1)
13.3.2 A System of Beacon Modules for Indoor Route Guidance
297(1)
13.3.3 An Algorithm for Route Guidance
298(3)
13.4 Evaluation
301(1)
13.5 Application
302(1)
13.6 Conclusion
303(6)
Acknowledgments
305(1)
References
305(1)
Acronyms and Glossary
306(3)
Chapter 14 WiFi Tracking of Pedestrian Behavior
309(30)
Andreea-Cristina Petre
Cristian Chilipirea
Mitra Baratchi
Ciprian Dobre
Maarten van Steen
14.1 Introduction
309(1)
14.2 Principles of WiFi Tracking
310(7)
14.2.1 WiFi Scanners: Technical Background
311(1)
14.2.2 Common Issues
312(2)
14.2.3 Alternatives
314(3)
14.3 Handling Raw Sensory Input
317(10)
14.3.1 The 802.11 Protocol Family
318(3)
14.3.2 Filtering Data at the Scanners
321(2)
14.3.3 Filtering Data After Centralization at Server
323(1)
14.3.4 Resulting Data Set
324(3)
14.4 Data Analysis
327(2)
14.5 Toward Large-Scale Crowd-Tracking Systems
329(5)
14.6 Conclusions
334(5)
References
334(2)
Acronyms and Glossary
336(3)
Chapter 15 The Life Management Platform Achieves Data Protection and Safe Sharing
339(22)
Hideyuki Shimizu
Hisashi Sakamoto
Tohru Miyazaki
Masayoshi Kai
15.1 Introduction
339(2)
15.2 Life Management Platform
341(6)
15.2.1 Overview
341(1)
15.2.2 Comparison with Other IoT Platforms
342(1)
15.2.3 The Function of Life Management Platform
343(4)
15.3 Life Management Service
347(9)
15.3.1 Background of Model Case
347(2)
15.3.2 Life Management Services for the Expansion of Healthy Life Expectancy
349(7)
15.4 Conclusion
356(1)
15.5 Future Works and Challenges
357(4)
References
358(1)
Acronyms and Glossary
359(2)
Index 361
Fatos Xhafa, PhD in Computer Science, is Full Professor at the Technical University of Catalonia (UPC), Barcelona, Spain. He has held various tenured and visiting professorship positions. He was a Visiting Professor at the University of Surrey, UK (2019/2020), Visiting Professor at the Birkbeck College, University of London, UK (2009/2010) and a Research Associate at Drexel University, Philadelphia, USA (2004/2005). He was a Distinguished Guest Professor at Hubei University of Technology, China, for the duration of three years (2016-2019). Prof. Xhafa has widely published in peer reviewed international journals, conferences/workshops, book chapters, edited books and proceedings in the field (H-index 55). He has been awarded teaching and research merits by the Spanish Ministry of Science and Education, by IEEE conferences and best paper awards. Prof. Xhafa has an extensive editorial service. He is founder and Editor-In-Chief of Internet of Things - Journal - Elsevier (Scopus and Clarivate WoS Science Citation Index) and of International Journal of Grid and Utility Computing, (Emerging Sources Citation Index), and AE/EB Member of several indexed Int'l Journals. Prof. Xhafa is a member of IEEE Communications Society, IEEE Systems, Man & Cybernetics Society and Founder Member of Emerging Technical Subcommittee of Internet of Things. His research interests include IoT and Cloud-to-thing continuum computing, massive data processing and collective intelligence, optimization, security and trustworthy computing and machine learning, among others. He can be reached at fatos@cs.upc.edu. Please visit also http://www.cs.upc.edu/~fatos/ and at http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos Fang-Yie Leu is Professor of Computer Science at TungHai University in Taiwan. His research interests include wireless communication, network security, grid applications, and natural language processing. Li-Ling Hung is Associate Professor of Computer Science and Information Engineering at Aletheia University in Taiwan. Her research interests include vehicular ad hoc networks, wireless sensor networks, and cyber-physical systems.
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