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E-raamat: IoT Technologies in Smart-Cities: From sensors to big data, security and trust

Edited by (Near East University in Nicosia, Cyprus), Edited by (King Saud University (KSU), College of Computer and Information Sciences, Saudi Arabia)
  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 28-May-2020
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785618703
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IoT Technologies in Smart-Cities: From sensors to big data, security and trustSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 28-May-2020
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785618703
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Smart City and sensing platforms are considered some of the most significant topics in the Internet of Things (IoT). Sensors are at the heart of the IoT, and their development is a key issue if such concepts are to achieve their full potential.

This book addresses the major challenges in realizing smart city and sensing platforms in the era of the IoT and the Cloud. Challenges vary from cost and energy efficiency to availability and service quality. To tackle these challenges, sensors must meet certain expectations and requirements such as size constraints, manufacturing costs and resistance to environmental factors.

This book focuses on both the design and implementation aspects for smart city and sensing applications that are enabled and supported by IoT paradigms. Attention is also given to data delivery approaches and performance aspects.



This book focuses on both the design and implementation aspects for smart city and sensing applications that are enabled and supported by IoT paradigms. Attention is also given to data delivery approaches and performance aspects.

About the editors xi
Foreword and outline xiii
1 Access control approaches for smart cities
1(40)
Nuray Baltaci Akhuseyinoglu
James Joshi
1.1 Introduction
1(2)
1.2 Smart cities
3(7)
1.2.1 What is a smart city?
3(1)
1.2.2 Smart city applications
4(1)
1.2.3 Key enabling technologies for smart cities
5(5)
1.3 Security and privacy challenges
10(4)
1.3.1 Unique characteristics of smart city applications
10(1)
1.3.2 Privacy
11(1)
1.3.3 Secure interoperation
12(1)
1.3.4 Insider attacks
12(1)
1.3.5 Trust management
13(1)
1.4 AC approaches for smart cities
14(20)
1.4.1 AC models
14(3)
1.4.2 AC models and frameworks for smart city and smart city applications
17(4)
1.4.3 AC models and frameworks for secure interoperation
21(6)
1.4.4 Trust-based AC models and frameworks
27(4)
1.4.5 AC models and frameworks for insider threats
31(3)
1.5 Future research directions and perspectives
34(1)
1.6 Conclusions
34(7)
Acknowledgment
35(1)
References
35(6)
2 Impact of Internet of Things in smart cities
41(22)
Bhawana Rudra
2.1 Introduction
41(1)
2.2 Smart city
42(1)
2.3 IoT technologies for smart cities
42(3)
2.4 Smart city: IoT applications
45(5)
2.4.1 Smart infrastructure
45(2)
2.4.2 Smart building and properties
47(1)
2.4.3 Smart industrial environment
48(1)
2.4.4 Smart city services
48(1)
2.4.5 Smart energy management
49(1)
2.4.6 Smart water and weather management
49(1)
2.4.7 Smart waste management
50(1)
2.5 Applications: world wide
50(4)
2.5.1 International-use cases
50(2)
2.5.2 National-use cases
52(2)
2.6 Challenges and future directions
54(1)
2.7 Conclusion
55(8)
References
55(8)
3 IoT-based smart water
63(20)
Hitesh Mohapatra
Amiya Kumar Rath
3.1 Smart city
63(5)
3.1.1 IoT in traditional city
65(1)
3.1.2 Myths about smart cities
66(2)
3.1.3 IoT for communication in smart cities
68(1)
3.2 Smart water
68(2)
3.3 SW challenges
70(2)
3.3.1 Asset maintenance
71(1)
3.3.2 Leakage maintenance
71(1)
3.3.3 SW metering maintenance
71(1)
3.3.4 Challenges
72(1)
3.4 Proposed structure for SW
72(2)
3.5 IoT as solution
74(4)
3.5.1 IoT in asset maintenance and leakage detection
75(1)
3.5.2 IoT in SW metering
76(1)
3.5.3 IoT in SW bottle
76(1)
3.5.4 IoT in SW distribution network
76(1)
3.5.5 IoT in SW irrigation
77(1)
3.5.6 IoT in remote controlling of SW assets
77(1)
3.5.7 IoT for SW pricing or revenue generation
77(1)
3.5.8 IoT for smart billing for SW
77(1)
3.5.9 IoT for measuring deep water quality
78(1)
3.5.10 IoT for predicting water-based natural calamities
78(1)
3.6 Lessons
78(1)
3.7 Conclusion
79(4)
References
79(4)
4 Contiki-OS IoT data analytics
83(22)
Muhammad Rafiq
Ghazala Rafiq
Hafiz Muhammad Raza ur Rehman
Yousaf Bin Zikria
Sung Won Kim
Gyu Sang Choi
4.1 Introduction
84(1)
4.2 ContikiOS
85(3)
4.3 Contiki-OS message structures
88(2)
4.4 Mathematical formulas for required statistics
90(2)
4.5 Proposed algorithms
92(4)
4.6 Results and discussion
96(6)
4.7 Conclusion
102(3)
References
102(3)
5 Analysis of the safety of the Internet of Things in the mesh
105(26)
Mikolaj Leszczuk
5.1 Introduction
105(2)
5.2 Security of the IoT
107(2)
5.2.1 X.509
107(1)
5.2.2 Open Trust Protocol
108(1)
5.3 Safety aspects in the IEEE 802.15.4 standard
109(2)
5.4 Technical guidelines for securely transferring information between selected IoT mesh points
111(3)
5.4.1 Networking modes
111(2)
5.4.2 Types of communication
113(1)
5.5 Security of the implementation of the mesh IoT
114(9)
5.5.1 Bluetooth mesh networking
115(2)
5.5.2 Disruption-tolerant mesh network
117(1)
5.5.3 ELIoT Pro
117(1)
5.5.4 LoRa
118(2)
5.5.5 Thread
120(1)
5.5.6 Z-Wave
120(1)
5.5.7 Zigbee
121(2)
5.6 Comparison of security aspects in different networks
123(1)
5.7 Summary
124(7)
References
124(7)
6 Design of smart urban drainage systems using evolutionary decision tree model
131(20)
Mir Jafar Sadegh Safari
Ali Danandeh Mehr
6.1 Introduction
131(4)
6.1.1 Overview of drainage systems design criteria
133(2)
6.1.2 Overview of machine learning application in drainage systems design
135(1)
6.2 Materials and methods
135(9)
6.2.1 Experimental data
135(1)
6.2.2 Data preparation
136(1)
6.2.3 Performance indices
136(1)
6.2.4 Decision tree
137(1)
6.2.5 GP model
138(2)
6.2.6 Hybrid EDT model
140(1)
6.2.7 Comparison of models
141(2)
6.2.8 IoT applications in drainage systems
143(1)
6.3 Conclusions
144(7)
References
145(6)
7 Statistical analysis for sensory E-Health applications: opportunities and challenges
151(20)
Hakan Yekta Yatbaz
Ali Cevat Tasiran
7.1 Introduction
152(1)
7.2 Background
153(3)
7.3 Data set
156(3)
7.3.1 Aruba test bed
156(1)
7.3.2 Data set and activities
156(1)
7.3.3 Data preparation
157(2)
7.4 Opportunities and directions
159(7)
7.5 Conclusion
166(5)
References
167(4)
8 Cybersecurity attacks on medical IoT devices for smart city healthcare services
171(18)
Marina Karageorgou
Georgios Mantas
Ismael Essop
Jonathan Rodriguez
Dimitrios Lymberopoulos
8.1 Introduction
171(1)
8.2 Smart city healthcare
172(3)
8.2.1 Overview
172(1)
8.2.2 Smart city healthcare systems
173(2)
8.2.3 Benefits arising from smart city healthcare
175(1)
8.3 IoT medical devices for smart city healthcare systems
175(2)
8.3.1 Overview
175(1)
8.3.2 Medical IoT devices security objectives
176(1)
8.4 Cybersecurity attacks on medical IoT devices
177(4)
8.4.1 Attack vectors
178(1)
8.4.2 Post-compromise actions
179(1)
8.4.3 Impact
180(1)
8.4.4 Impact evaluation
180(1)
8.5 Security countermeasures
181(3)
8.5.1 Ensuring confidentiality and integrity
181(1)
8.5.2 Ensuring availability
182(1)
8.5.3 Ensuring authentication and authorization
183(1)
8.5.4 Ensuring nonrepudiation
183(1)
8.6 Emerging good practice and approaches (standards)
184(1)
8.7 Conclusions and further challenges
185(4)
References
185(4)
9 HaLow: registering thousands of low-power sensors in smart cities
189(18)
Rashid Ali
Nurullah Shahin
Fadi Al-Turjman
Byung-Seo Kim
Sung Won Kim
9.1 Introduction
190(1)
9.2 IEEE 802.1ah HaLow: an overview
191(3)
9.2.1 Use cases for HaLow
192(1)
9.2.2 HaLow MAC layer
193(1)
9.3 Link set-up in HaLow networks for massive IoT devices registration
194(3)
9.3.1 Link set-up in WLANs
194(2)
9.3.2 Distributed authentication control
196(1)
9.3.3 Centralized authentication control
196(1)
9.4 Case study: hybrid slotted-CSMA/CA-TDMA
197(6)
9.4.1 SIFT geometric distribution
199(2)
9.4.2 Expected number of AuthReq frames in a C-Slot
201(2)
9.5 Conclusions
203(4)
References
204(3)
10 Statistical analysis of low-power sensor motes used in IoT applications
207(22)
Ali Cevat Tasiran
Burak Kizilkaya
10.1 Introduction
207(1)
10.2 Literature review
208(2)
10.3 Data set: Mica2Dot sensors and statistical analysis
210(14)
10.3.1 Descriptive analysis
210(4)
10.3.2 Linear regression model (ordinary least squares estimates)
214(2)
10.3.3 Ordered logit models
216(8)
10.4 Conclusion and future works
224(3)
References
224(3)
Appendix A Variables by duration groups
227(2)
11 Conclusions and recommendations
229(4)
Fadi Al-Turjman
Index 233
Fadi Al-Turjman is a professor and a research center director at Near East University in Nicosia, Cyprus. He is a leading authority in the areas of smart/cognitive, wireless and mobile networks' architectures, protocols, deployments and performance evaluation. He has served as the Lead Guest Editor in several journals including the IET Wireless Sensor Systems (WSS) and Elsevier Computer Communications. He was also the publication chair for the IEEE International Conf. on Local Computer Networks (LCN'18).



Muhammad Imran is an assistant professor at the College of Computer and Information Sciences, King Saud University (KSU), Saudi Arabia. He is also a Visiting Scientist with various universities including Iowa State University, USA. He is Editor in Chief of EAI Transactions on Pervasive Health and Technology, and serves as an associate editor for several journals including IET Wireless Sensor Systems, IEEE Communications Magazine, and Wireless Communication and Mobile Computing Journal.
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