Aiot Technologies and Applications for Smart Environments

✍ Scribed by Associate Professor Mamoun Alazab; Associate Professor Meenu Gupta; Associate Professor Shakeel Ahmed

• Publisher: The Institution of Engineering and Technology
• Year: 2023
• Tongue: English
• Leaves: 333
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Cover
Contents
Call for Authors – The IET International Book Series on Applied AIoT
About the editors
Preface
Acknowledgements
1 Introduction to AIoT for smart environments
Abstract
1.1 Introduction
1.2 From IoT to AIoT: smart IoT
1.2.1 Smart retail
1.2.2 Smart office buildings
1.2.3 Autonomous vehicles in fleet management (smart driving)
1.2.4 Autonomous delivery robots
1.2.5 Drone traffic monitoring
1.3 AI implementation and business cases of AIoT
1.3.1 Business case: ET city brain
1.3.2 Business case: Tesla’s autopilot
1.3.3 Business case: classroom monitoring systems
1.4 AI capable IoT platforms
1.5 AIoT practical applications
1.6 AIoT concerns and challenges
1.6.1 Challenges in AIoT
1.7 Conclusion
References
2 Research challenges in smart environments
Abstract
2.1 Introduction
2.2 Literature review
2.3 Applications
2.4 Components in smart environment
2.4.1 Data pre-processing
2.4.2 Sensors
2.4.3 Data processing
2.4.4 Environment control (actuators)
2.4.5 Sensors for homes
2.5 Wireless sensor networks
2.5.1 Home-based sensor platform
2.5.2 Sensor technologies
2.5.3 Smart monitoring and controlling hut
2.5.4 Vehicle system
2.6 Challenges
2.7 Conclusion
References
3 Applications-oriented smart cities based on AIoT emerging technologies
Abstract
3.1 Introduction
3.2 Smart cities overview and AIoT
3.3 The framework deployment and architecture of Smart City
3.4 AIoT-powered Smart City transformation
3.5 Functions and features of Smart Cities
3.6 Instruments that aid in the creation of a Smart City
3.7 AIoT and challenges in building Smart City
3.8 Conclusion and future scope
References
4 Use of smartphones application to identify pedestrian barriers around existing metro stations in Noida
Abstract
4.1 Introduction: background and overview
4.2 Literature survey
4.2.1 Current debate on TOD in India
4.2.2 Walking in Indian cities
4.2.3 GIS-based walkability evaluation
4.2.4 Re-assessing land-use and transport planning using station accessibility
4.3 Study area and data collection
4.3.1 Online smart questionnaire design
4.4 Methodology
4.4.1 Walkable catchment area
4.5 Results
4.5.1 Metro station survey analysis
4.5.2 Analysis of pedestrian catchment areas
4.6 Discussion and conclusion
Acknowledgment
References
5 A hybrid segmentation process for effective disease classification for smart agriculture
Abstract
5.1 Introduction
5.2 Literature survey
5.3 Proposed work
5.4 Performance evaluation
5.5 Conclusion and future workspace
References
6 AIoT-based water management and IoT-based smart irrigation system: effective in smart agriculture
Abstract
6.1 Introduction
6.2 Smart water management
6.2.1 Water leakage inside the circulation community
6.2.2 Water wastage at the consumer locality
6.3 Smart irrigation
6.4 Required components
6.5 Working of G-SM component
6.6 Working of RELAY
Relay design
Relay basics
Energized relay (ON)
De-energized relay (OFF)
Pole-and-throw
Solicitation of relay
Relay selection
6.7 Working of Arduino
What Arduino is
Arduino architecture
6.8 Programming code in Arduino
6.9 Result discussion
6.10 Conclusion
References
7 Adaptive smart farming system using Internet of Things (IoT) and artificial intelligence (AI) modeling
Abstract
7.1 Introduction
7.2 Literature survey
7.3 AI in agriculture
7.4 Use of wireless and automation systems in agriculture
7.5 Discussion
7.6 Conclusions
Conflict of interest
References
8 Time series data air quality prediction using Internet of Things and machine learning techniques
Abstract
8.1 Introduction
8.2 Analyzing the time-series
8.2.1 Time-series forecasting (projection)
8.2.2 Estimation of transfer functions
8.2.3 Analyzing uncommon involvement incidents
8.2.4 Analyzing multivariate time series
8.2.5 Discrete control systems
8.3 ML model (MLM)
8.3.1 ML applications
8.3.2 ML types
8.4 IoT
8.5 Air quality control (AQC)
8.5.1 Air quality evaluation
8.5.2 Flow diagram of AQC
References
9 Role of AIoT-based intelligent automation in robotics, UAVs, and drones
Abstract
9.1 Introduction
9.1.1 Synergy of IoT and AI
9.1.2 IoT-aided robotics
9.1.3 IoT-aided UAVs/drones
9.2 Literature review
9.2.1 Robotics
9.2.2 UAVs/drones
9.3 Components of IoRT system
9.3.1 Components of IoRT system
9.4 Applications of AIoT in robotics and UAVs/drones
9.4.1 Application of AIoT robotics
9.4.2 Application of AIoT in UAVs/drones
9.5 IoT’s AI challenges
9.5.1 Challenges faced in using robotics
9.5.2 Challenges faced in using UAVs/drones
9.6 Future scope
9.6.1 Future with robotics
9.6.2 Future with UAVs/drones
9.7 Summary and conclusion
References
10 AIoT-based waste management systems
Abstract
10.1 Introduction
10.2 Related work
10.3 AIoT
10.4 Various types and techniques for waste disposal
10.5 IoT-based waste management system
10.6 Main features of AIoT-based framework for waste management
10.7 Data and proposed methodology
10.7.1 Design model
10.7.2 Waste collection model
10.7.3 Working of intelligent bin process
10.7.4 Intelligent bin control by using AI
10.8 Conclusion
10.9 Future scope
References
11 AIoT technologies and applications for smart environments
Abstract
11.1 Introduction
11.1.1 Motivation
11.2 IoT in smart manufacturing system
11.2.1 Challenges for smart manufacturing
11.2.2 Vertical sector particular necessities
11.2.3 Challenges in the area of IoT and Big Data analytics
11.2.4 Challenges in the area of IoT and blockchain computing
11.3 Security issues and challenges
11.4 A general outlook on blockchain
11.4.1 The concept of blockchain technology
11.4.2 The applications of blockchain technology utilized in the current period
11.4.3 Advantages and disadvantages of blockchain technology
11.5 The future of blockchain technology
11.6 Proposed model for smart manufacturing in the context of Industry 4.0
11.7 Result and discussion
11.7.1 Low-level security issues
11.7.2 Intermediate-level security issues
11.7.3 High-level security issues
11.8 Conclusion
References
12 AIoT-based e-commerce
Abstract
12.1 Introduction
12.1.1 Working of AIoT
12.1.2 Advantages and challenges of AIoT
12.2 Applications of IoT in e-commerce
12.2.1 Inventory management
12.2.2 Supply chain management
12.2.3 Maintenance and warranty
12.2.4 Smart homes
12.2.5 Personalization
12.2.6 Customer experience
12.3 System design
12.4 Online store
12.5 Selection approach for offline store
12.6 Hardware and software requirements
12.7 Conclusion
12.8 Future scope
References
13 AIoT-based smart education and online teaching
Abstract
13.1 Introduction
13.2 Literature review
13.3 Research methodology
13.3.1 Course design
13.3.2 Research model hypothesis
13.3.3 Research subject
13.3.4 Research tools
13.3.5 Definition of measurement methods
13.4 Experimental results
13.5 Conclusions and suggestions
References
14 Autonomous UAV with obstacle management using AIoT: a case study on healthcare application
Abstract
14.1 Introduction
14.1.1 IoT architecture
14.1.2 Challenges in IoT
14.1.3 AIoT
14.1.4 UAV
14.1.5 Advantages of IoT
14.1.6 Road map of the chapter
14.2 Related work
14.2.1 Motivation and contribution
14.3 Applications of AIoT
14.4 AIoT in healthcare
14.4.1 Case study on COVID-19 pandemic
14.5 UAV and AIoT for healthcare
14.5.1 Artificial intelligent IoT in healthcare
14.5.2 UAV embedded with AIoT in healthcare
14.6 Proposed algorithm: autonomous drone with obstacle management
14.6.1 Different methods of UAV can be used in AIoT healthcare
14.6.2 Algorithm
14.7 Comparison study and analysis of different UAV methods
14.8 Conclusion and future scope
References
15 Effective learning-based attack detection methods for the Internet of Things
Abstract
15.1 Introduction: background and driving forces
15.2 IoT applications
15.3 Anomaly detection
15.3.1 Static environment
15.3.2 Dynamic environment
15.3.3 An IDS
15.3.4 Requirement of IDS
15.4 ML classifiers
15.4.1 Supervised learning (SL)
15.4.2 Unsupervised learning (UL)
15.4.3 Semi-supervised learning
15.4.4 ML ensemble
15.4.5 DL
15.4.6 Auto-encoders
15.5 Synthesis and conclusions
15.5.1 Main findings
15.5.2 Challenges
15.6 Future directions
References
16 Future perspectives of AI-driven Internet of Things
16.1 Summary
16.2 Potential challenges in AIoT technology
16.3 Conclusion of the book
16.4 Future perspectives and research directions
Index
Back Cover