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AIoT Technologies and Applications for Smart Environments [Kõva köide]

Edited by (Charles Darwin University, Faculty of Science and Technology, Australia), Edited by (Chandigarh University, UIE-CSE Department, India), Edited by (King Faisal University, College of Computer Sciences and Information Technology, Saudi Arabia)
  • Formaat: Hardback, 333 pages, kõrgus x laius: 234x156 mm
  • Sari: Computing and Networks
  • Ilmumisaeg: 03-Apr-2023
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1839536330
  • ISBN-13: 9781839536335
  • Formaat: Hardback, 333 pages, kõrgus x laius: 234x156 mm
  • Sari: Computing and Networks
  • Ilmumisaeg: 03-Apr-2023
  • Kirjastus: Institution of Engineering and Technology
  • ISBN-10: 1839536330
  • ISBN-13: 9781839536335

Although some IoT systems are built for simple event control where a sensor signal triggers a corresponding reaction, many events are far more complex, requiring applications to interpret the event using analytical techniques to initiate proper actions. Artificial intelligence of things (AIoT) applies intelligence to the edge and gives devices the ability to understand the data, observe the environment around them, and decide what to do best with minimum human intervention. With the power of AI, AIoT devices are not just messengers feeding information to control centers. They have evolved into intelligent machines capable of performing self-driven analytics and acting independently. A smart environment uses technologies such as wearable devices, IoT, and mobile internet to dynamically access information, connect people, materials and institutions, and then actively manages and responds to the ecosystem's needs in an intelligent manner.

In this edited book, the contributors present challenges, technologies, applications and future trends of AIoT in realizing smart and intelligent environments, including frameworks and methodologies for applying AIoT in monitoring devices and environments, tools and practices most applicable to product or service development to solve innovation problems, advanced and innovative techniques, and practical implementations to enhance future smart environment systems. Chapters cover a broad range of applications including smart cities, smart transportation and smart agriculture.

This book is a valuable resource for industry and academic researchers, scientists, engineers and advanced students in the fields of ICTs and networking, IoT, AI and machine and deep learning, data science, sensing, robotics, automation and smart technologies and smart environments.



In this edited book, the authors present the challenges, technologies, applications and future trends of the artificial intelligence-enabled internet of things (AIoT) in realizing smart and intelligent environments.

Call for Authors -- The IET International Book Series on Applied AIoT xiii
About the editors xv
Preface xvii
Acknowledgements xix
1 Introduction to AIoT for smart environments
1(20)
Chander Prabha
Meenu Gupta
Shakeel Ahmed
1.1 Introduction
1(2)
1.2 From IoT to AIoT: smart IoT
3(3)
1.2.1 Smart retail
5(1)
1.2.2 Smart office buildings
5(1)
1.2.3 Autonomous vehicles in fleet management (smart driving)
5(1)
1.2.4 Autonomous delivery robots
6(1)
1.2.5 Drone traffic monitoring
6(1)
1.3 AI implementation and business cases of AIoT
6(5)
1.3.1 Business case: ET city brain
9(1)
1.3.2 Business case: Tesla's autopilot
9(1)
1.3.3 Business case: classroom monitoring systems
9(2)
1.4 AI capable IoT platforms
11(1)
1.5 AIoT practical applications
11(4)
1.6 AIoT concerns and challenges
15(2)
1.6.1 Challenges in AIoT
16(1)
1.7 Conclusion
17(4)
References
17(4)
2 Research challenges in smart environments
21(16)
Nitika Kapoor
Parminder Singh
Kusrini
2.1 Introduction
21(3)
2.2 Literature review
24(3)
2.3 Applications
27(1)
2.4 Components in smart environment
27(2)
2.4.1 Data pre-processing
28(1)
2.4.2 Sensors
29(1)
2.4.3 Data processing
29(1)
2.4.4 Environment control (actuators)
29(1)
2.4.5 Sensors for homes
29(1)
2.5 Wireless sensor networks
29(1)
2.5.1 Home-based sensor platform
30(1)
2.5.2 Sensor technologies
30(1)
2.5.3 Smart monitoring and controlling hut
30(1)
2.5.4 Vehicle system
30(1)
2.6 Challenges
30(4)
2.7 Conclusion
34(3)
References
34(3)
3 Applications-oriented smart cities based on AIoT emerging technologies
37(20)
Chander Prabha
Jaspreet Singh
Raihan Rasool
3.1 Introduction
37(1)
3.2 Smart cities overview and AIoT
38(4)
3.3 The framework deployment and architecture of Smart City
42(2)
3.4 AIoT-powered Smart City transformation
44(2)
3.5 Functions and features of Smart Cities
46(3)
3.6 Instruments that aid in the creation of a Smart City
49(1)
3.7 AIoT and challenges in building Smart City
50(3)
3.8 Conclusion and future scope
53(4)
References
53(4)
4 Use of smartphones application to identify pedestrian barriers around existing metro stations in Noida
57(18)
S.S. Kapoor
T.S. Brar
4.1 Introduction: background and overview
58(2)
4.2 Literature survey
60(4)
4.2.1 Current debate on TOD in India
62(1)
4.2.2 Walking in Indian cities
62(1)
4.2.3 GIS-based walkability evaluation
63(1)
4.2.4 Re-assessing land-use and transport planning using station accessibility
63(1)
4.3 Study area and data collection
64(1)
4.3.1 Online smart questionnaire design
64(1)
4.4 Methodology
65(3)
4.4.1 Walkable catchment area
67(1)
4.5 Results
68(2)
4.5.1 Metro station survey analysis
68(1)
4.5.2 Analysis of pedestrian catchment areas
69(1)
4.6 Discussion and conclusion
70(5)
Acknowledgment
71(1)
References
72(3)
5 A hybrid segmentation process for effective disease classification for smart agriculture
75(18)
R. Karthickmanoj
T. Sasilatha
5.1 Introduction
75(3)
5.2 Literature survey
78(7)
5.3 Proposed work
85(1)
5.4 Performance evaluation
86(3)
5.5 Conclusion and future workspace
89(4)
References
89(4)
6 AIoT-based water management and IoT-based smart irrigation system: effective in smart agriculture
93(20)
Mamata Rath
Subhranshu Sekhar Tripathy
Niva Tripathy
Chhabi Rani Panigrahi
Bibudhendu Pati
6.1 Introduction
93(1)
6.2 Smart water management
94(3)
6.2.1 Water leakage inside the circulation community
95(1)
6.2.2 Water wastage at the consumer locality
96(1)
6.3 Smart irrigation
97(3)
6.4 Required components
100(1)
6.5 Working of G-SM component
100(1)
6.6 Working of RELAY
101(3)
6.7 Working of Arduino
104(2)
6.8 Programming code in Arduino
106(3)
6.9 Result discussion
109(1)
6.10 Conclusion
109(4)
References
109(4)
7 Adaptive smart farming system using Internet of Things (IoT) and artificial intelligence (AI) modeling
113(14)
Swati Singh
K. V. Suresh Babu
7.1 Introduction
113(3)
7.2 Literature survey
116(1)
7.3 AI in agriculture
117(2)
7.4 Use of wireless and automation systems in agriculture
119(1)
7.5 Discussion
120(1)
7.6 Conclusions
120(7)
References
121(6)
8 Time series data air quality prediction using Internet of Things and machine learning techniques
127(24)
Qasem Abu Al-Haija
Noor A. Jebril
8.1 Introduction
127(1)
8.2 Analyzing the time-series
128(7)
8.2.1 Time-series forecasting (projection)
130(2)
8.2.2 Estimation of transfer functions
132(1)
8.2.3 Analyzing uncommon involvement incidents
133(1)
8.2.4 Analyzing multivariate time series
133(1)
8.2.5 Discrete control systems
133(2)
8.3 ML model (MLM)
135(3)
8.3.1 ML applications
135(1)
8.3.2 ML types
136(2)
8.4 IoT
138(1)
8.5 Air quality control (AQC)
139(12)
8.5.1 Air quality evaluation
142(2)
8.5.2 Flow diagram of AQC
144(2)
References
146(5)
9 Role of AIoT-based intelligent automation in robotics, UAVs, and drones
151(32)
Chander Prakash
Lakhwinder Pal Singh
Ajay Gupta
9.1 Introduction
151(8)
9.1.1 Synergy of IoT and AI
152(1)
9.1.2 IoT-aided robotics
153(2)
9.1.3 IoT-aided UAVs/drones
155(4)
9.2 Literature review
159(7)
9.2.1 Robotics
159(2)
9.2.2 UAVs/drones
161(5)
9.3 Components of IoRT system
166(1)
9.3.1 Components of IoRT system
167(1)
9.4 Applications of AIoT in robotics and UAVs/drones
167(3)
9.4.1 Application of AIoT robotics
167(2)
9.4.2 Application of AIoT in UAVs/drones
169(1)
9.5 IoT's AI challenges
170(1)
9.5.1 Challenges faced in using robotics
170(1)
9.5.2 Challenges faced in using UAVs/drones
171(1)
9.6 Future scope
171(4)
9.6.1 Future with robotics
171(1)
9.6.2 Future with UAVs/drones
172(3)
9.7 Summary and conclusion
175(8)
References
176(7)
10 AIoT-based waste management systems
183(16)
Sharad Chauhan
Shubham Gargrish
10.1 Introduction
183(2)
10.2 Related work
185(2)
10.3 AIoT
187(1)
10.4 Various types and techniques for waste disposal
188(1)
10.5 IoT-based waste management system
189(1)
10.6 Main features of AIoT-based framework for waste management
190(1)
10.7 Data and proposed methodology
191(3)
10.7.1 Design model
192(1)
10.7.2 Waste collection model
193(1)
10.7.3 Working of intelligent bin process
193(1)
10.7.4 Intelligent bin control by using AI
194(1)
10.8 Conclusion
194(2)
10.9 Future scope
196(3)
References
196(3)
11 AIoT technologies and applications for smart environments
199(16)
Richa Umesh Shah
Jai Prakash Verma
Rachna Jain
Sanjay Garg
11.1 Introduction
199(2)
11.1.1 Motivation
200(1)
11.2 IoT in smart manufacturing system
201(2)
11.2.1 Challenges for smart manufacturing
201(1)
11.2.2 Vertical sector particular necessities
202(1)
11.2.3 Challenges in the area of IoT and Big Data analytics
202(1)
11.2.4 Challenges in the area of IoT and blockchain computing
202(1)
11.3 Security issues and challenges
203(1)
11.4 A general outlook on blockchain
203(5)
11.4.1 The concept of blockchain technology
204(2)
11.4.2 The applications of blockchain technology utilized in the current period
206(1)
11.4.3 Advantages and disadvantages of blockchain technology
207(1)
11.5 The future of blockchain technology
208(1)
11.6 Proposed model for smart manufacturing in the context of Industry 4.0
209(1)
11.7 Result and discussion
209(3)
11.7.1 Low-level security issues
210(1)
11.7.2 Intermediate-level security issues
211(1)
11.7.3 High-level security issues
211(1)
11.8 Conclusion
212(3)
References
212(3)
12 AIoT-based e-commerce
215(14)
Kshatrapal Singh
Ashish Kumar
Yogesh Kumar Sharma
Arun Kumar Rai
12.1 Introduction
215(2)
12.1.1 Working of AIoT
216(1)
12.1.2 Advantages and challenges of AIoT
216(1)
12.2 Applications of IoT in e-commerce
217(2)
12.2.1 Inventory management
217(1)
12.2.2 Supply chain management
218(1)
12.2.3 Maintenance and warranty
218(1)
12.2.4 Smart homes
218(1)
12.2.5 Personalization
218(1)
12.2.6 Customer experience
219(1)
12.3 System design
219(1)
12.4 Online store
220(3)
12.5 Selection approach for offline store
223(1)
12.6 Hardware and software requirements
224(1)
12.7 Conclusion
224(1)
12.8 Future scope
225(4)
References
225(4)
13 AIoT-based smart education and online teaching
229(22)
Somya Srivastava
Disha Mohini Pathak
13.1 Introduction
230(1)
13.2 Literature review
231(4)
13.3 Research methodology
235(6)
13.3.1 Course design
239(1)
13.3.2 Research model hypothesis
239(1)
13.3.3 Research subject
239(1)
13.3.4 Research tools
239(1)
13.3.5 Definition of measurement methods
240(1)
13.4 Experimental results
241(4)
13.5 Conclusions and suggestions
245(6)
References
245(6)
14 Autonomous UAV with obstacle management using AIoT: a case study on healthcare application
251(24)
Vandana Mohindru Sood
Kapil Mehta
14.1 Introduction
251(5)
14.1.1 IoT architecture
252(1)
14.1.2 Challenges in IoT
253(2)
14.1.3 AIoT
255(1)
14.1.4 UAV
255(1)
14.1.5 Advantages of IoT
255(1)
14.1.6 Road map of the chapter
256(1)
14.2 Related work
256(2)
14.2.1 Motivation and contribution
258(1)
14.3 Applications of AIoT
258(1)
14.4 AIoT in healthcare
259(1)
14.4.1 Case study on COVID-19 pandemic
259(1)
14.5 UAV and AIoT for healthcare
259(5)
14.5.1 Artificial intelligent IoT in healthcare
260(1)
14.5.2 UAV embedded with AIoT in healthcare
260(4)
14.6 Proposed algorithm: autonomous drone with obstacle management
264(3)
14.6.1 Different methods of UAV can be used in AIoT healthcare
265(1)
14.6.2 Algorithm
266(1)
14.7 Comparison study and analysis of different UAV methods
267(1)
14.8 Conclusion and future scope
267(8)
References
270(5)
15 Effective learning-based attack detection methods for the Internet of Things
275(20)
Khalid Albulayhi
Qasem Abu Al-Haija
Frederick T. Sheldon
15.1 Introduction: background and driving forces
276(1)
15.2 IoT applications
277(3)
15.3 Anomaly detection
280(2)
15.3.1 Static environment
280(1)
15.3.2 Dynamic environment
281(1)
15.3.3 An IDS
281(1)
15.3.4 Requirement of IDS
281(1)
15.4 ML classifiers
282(5)
15.4.1 Supervised learning (SL)
283(1)
15.4.2 Unsupervised learning (UL)
284(1)
15.4.3 Semi-supervised learning
285(1)
15.4.4 ML ensemble
285(1)
15.4.5 DL
286(1)
15.4.6 Auto-encoders
287(1)
15.5 Synthesis and conclusions
287(2)
15.5.1 Main findings
288(1)
15.5.2 Challenges
289(1)
15.6 Future directions
289(6)
References
290(5)
16 Future perspectives of AI-driven Internet of Things
295(6)
Shakeel Ahmed
Parvathaneni Naga Srinivasu
Meenu Gupta
16.1 Summary
295(1)
16.2 Potential challenges in AIoT technology
296(2)
16.3 Conclusion of the book
298(2)
16.4 Future perspectives and research directions
300(1)
Index 301
Mamoun Alazab is a professor at the Faculty of Science and Technology, Charles Darwin University, Australia. His research is multidisciplinary and focuses on cyber security, digital forensics of computer systems, and cybercrime detection and prevention. He is a senior member of the IEEE and Founding Chair of the IEEE Northern Territory (NT) Subsection.



Meenu Gupta is an associate professor at the UIE-CSE Department, Chandigarh University, India. Her areas of research include machine learning, intelligent systems, and data mining, with a specific interest in artificial intelligence, image processing and analysis, smart cities, data analysis, and human/brain-machine interaction (BMI). She has edited two books on healthcare and cancer diseases and authored four engineering books. She is a reviewer for several journals including Big Data, CMC, Scientific Report and TSP.



Shakeel Ahmed is an associate professor at the College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. His areas of interest include software verification and validation, mobile ad hoc networks, software engineering and cloud computing. He has authored research papers in journals and IEEE international conferences. He is a PC member for several international conferences and a reviewer for quartile journals. He holds a PhD in computer science from Indore University, India.