Edge Artificial Intelligence
Foundations, Techniques, and Applications
1st Edition
Published on 12. November 2025
Book
Hardback
656 pages
978-1-394-35500-6 (ISBN)
Description
Secure your expertise in the next wave of computing with this essential book, which provides a comprehensive guide to Edge AI, detailing its foundational concepts, deployment strategies, and real-world applications for revolutionizing performance and privacy across various industries.
Edge AI has the potential to bring the computational power of AI algorithms closer to where data is generated, processed, and utilized. Traditionally, AI models are deployed in centralized cloud environments, leading to latency issues, bandwidth constraints, and privacy concerns. Edge AI addresses these limitations by enabling AI inference and decision-making directly on edge devices, such as smartphones, IoT sensors, and edge servers. Despite its challenges, edge AI presents numerous opportunities across various domains. From real-time health monitoring and predictive maintenance in industrial IoT to personalized recommendations in retail and immersive experiences in augmented reality, edge AI has the potential to revolutionize how we interact with technology. This book aims to provide a comprehensive exploration of edge AI, covering its foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, emerging trends, and real-world applications. This guide is essential for anyone pushing the boundaries to leverage edge computing for enhanced performance and efficiency.
Readers will find this volume:
Dives deep into the world of edge AI with a comprehensive exploration covering foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, governance frameworks, optimization techniques, and real-world applications;
Offers practical guidance on implementing edge AI solutions effectively in various domains, including architecture design, development frameworks, deployment strategies, and optimization techniques;
Explores concrete examples of edge AI applications across diverse domains such as healthcare, industrial IoT, smart cities, and autonomous systems, providing insights into how edge AI is revolutionizing industries and everyday life;
Provides insights into emerging trends and technologies in the field of edge AI, including convergence with blockchain, augmented reality, virtual reality, autonomous systems, personalized experiences, and cybersecurity.
Audience
Researchers, AI experts, and industry professionals in the field of computer science, IT, and business management.
Edge AI has the potential to bring the computational power of AI algorithms closer to where data is generated, processed, and utilized. Traditionally, AI models are deployed in centralized cloud environments, leading to latency issues, bandwidth constraints, and privacy concerns. Edge AI addresses these limitations by enabling AI inference and decision-making directly on edge devices, such as smartphones, IoT sensors, and edge servers. Despite its challenges, edge AI presents numerous opportunities across various domains. From real-time health monitoring and predictive maintenance in industrial IoT to personalized recommendations in retail and immersive experiences in augmented reality, edge AI has the potential to revolutionize how we interact with technology. This book aims to provide a comprehensive exploration of edge AI, covering its foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, emerging trends, and real-world applications. This guide is essential for anyone pushing the boundaries to leverage edge computing for enhanced performance and efficiency.
Readers will find this volume:
Dives deep into the world of edge AI with a comprehensive exploration covering foundational concepts, development frameworks, deployment strategies, security considerations, ethical implications, governance frameworks, optimization techniques, and real-world applications;
Offers practical guidance on implementing edge AI solutions effectively in various domains, including architecture design, development frameworks, deployment strategies, and optimization techniques;
Explores concrete examples of edge AI applications across diverse domains such as healthcare, industrial IoT, smart cities, and autonomous systems, providing insights into how edge AI is revolutionizing industries and everyday life;
Provides insights into emerging trends and technologies in the field of edge AI, including convergence with blockchain, augmented reality, virtual reality, autonomous systems, personalized experiences, and cybersecurity.
Audience
Researchers, AI experts, and industry professionals in the field of computer science, IT, and business management.
More details
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Dimensions
Height: 158 mm
Width: 238 mm
Thickness: 45 mm
Weight
1052 gr
ISBN-13
978-1-394-35500-6 (9781394355006)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Preeti Agarwal | Anchit Bijalwan
Edge Artificial Intelligence
Foundations, Techniques, and Applications
E-Book
11/2025
1st Edition
Wiley
€202.99
Available for download
Preeti Agarwal | Anchit Bijalwan
Edge Artificial Intelligence
Foundations, Techniques, and Applications
E-Book
10/2025
1st Edition
Wiley
€202.99
Available for download
Persons
Preeti Agarwal, PhD is an assistant professor in the School of Technology Management and Engineering at the Narsee Monjee Institute of Management Studies with more than 13 years of experience. She has extensive publications in international journals and conferences. Her research focuses on optimizing edge-based frameworks for human activity recognition.
Anchit Bijalwan, PhD an Associate Professor in the School of Computing and Innovative Technologies at the British University Vietnam, Hanoi, Vietnam. He has authored two books and published more than fifty research papers in reputed international journals and conferences. His specialization is in privacy and security.
Anchit Bijalwan, PhD an Associate Professor in the School of Computing and Innovative Technologies at the British University Vietnam, Hanoi, Vietnam. He has authored two books and published more than fifty research papers in reputed international journals and conferences. His specialization is in privacy and security.
Content
Preface xxiii
Part 1: Foundations and Core Concepts of Edge AI 1
1 Edge AI Demystified: From Its Origins to Future Frontiers 3
Preeti Agarwal, Anchit Bijalwan, Ayesha Patel, Atharv Amit Deshpande and Vidhi Panchal
2 Optimizing Deep Learning Models for Edge Devices 39
Haripriya Saraf, Kaavya nair, Aditya Kurup, Preeti Agarwal and Anchit Bijalwan
3 Role of Multi Objective Evolutionary Algorithms in Edge AI System Optimization 67
Preeti Gupta and Sakshi Indolia
4 The Convergence of Edge Computing, AI, and Blockchain: Challenges, Opportunities, and Future Prospects 87
Aditya Ray, Suditi Pradhan, Darsh Iyer, Preeti Agarwal and Anchit Bijalwan
5 Network Optimization in Edge Computing 117
Gargee Thakur, Vaibhav Singh, Riddhima Ghule, Anish Dey, Preeti Agarwal and Anchit Bijalwan
6 Comparative Analysis of Pruning Conventional Machine Learning or Deep Learning Frameworks Utilizing Discrete Wavelet Transform for Iris Biometrics 155
Divyang Jadav, Aditee Moudgil, Nilesh Choudhary and Shruti Daw
7 Convergence of K8s and Istio Deployment on Mission-Critical Environments 181
Arunkumar Arulappan, Vetrivel S.B., Shanmuga Priyan T., Gina Rose G. and Murugan Krishnamoorthy
Part 2: Security, Ethics, and Trust in Edge AI 197
8 Edge AI Security and Privacy: Threats, Solutions, and Best Practices 199
Ishika Mohan, Advika Wankhede, Ishita Manral, Rohit Kadam, Preeti Agarwal and Anchit Bijalwan
9 Edge AI in Cybersecurity 231
Vaishali V. Bodade, Jyoti More, Suraj Khandare and Supriya Joshi
10 Database-Guard Artificial Intelligence: Revolutionizing Database Security with Artificial Intelligence 251
Safwan Hungund and Jyoti Kundale
11 Edge-AI Ledger Docs: Revolutionizing Document Storage and Verification with Blockchain 277
Nilima Patel and Mayank Aggarwal
12 A Lightweight Lie Detector for Resource Constraint Devices 307
Mayur Navin Sharma, Rohan Deep Kujur, Khushi Tulsian, Tejaswini J. Chavan and Atharva Manish
13 AIPendant: An Efficient and Lightweight Threat Detection System for Real-Time Personal Safety 317
Sanghyun Yeo, Vu Minh Phuc and Le Anh Ngoc
Part 3: Edge AI in Industry and Domain-Specific Applications 337
14 Edge AI for Connected & Automated Vehicles: Opportunities & Challenges 339
Alok Ranjan, Ashutosh Bandyopadhyay and Guru Prasad A. S.
15 The Role of Edge Computing in Enhancing Autonomous Vehicle Performance 367
Lakshmeesh Mankame, Anushka Raspayle, Onkar Mane, Preeti Agarwal and Anchit Bijalwan
16 Applying Edge AI in the Environment of Industrial Internet of Things (IIoT) 393
Shraddha C. Subhedar and Deepa Parasar
17 Healthcare Applications of Edge AI 415
Shiwani Gupta, Jagruti Jadhav, Shilpa Mathur, Sampada Bhonde and Pranjali Sankhe
18 Design and Enhance of Data Analysis in Healthcare System with AutoML Business Intelligence Technology 439
Rajendra Kachhava, R.K. Somani and Ravi Khatwal
19 A Case Study from Internet of Things to Edge AI with Challenges in Industry 4.0 447
Harishchander Anandaram, Vinisha Sumra, Roosha Shamoon, Kawerinder Singh Sidhu, Shreenidhi K.S. and Kapil Joshi
20 Edge AI and Blockchain: A Synergy for Water Body Preservation 469
Anjali Arora and Mayank Aggarwal
21 Enhancing Stadium Safety Through AI-Based Detection of Violent Incidents with 360-Degree Cameras 501
Phuong Anh Nguyen, Dung Tran, Trung Duong, Duong Pham, Son Nguyen, Dat Do and Ngoc Le
Part 4: Optimization and Intelligent Decision-Making with Edge AI 515
22 Design of a Deep Reinforcement Learning Approach for Optimization of Task Offloading and Resource Allocation for Edge Computing Networks 517
Anindita Khade and Avaneesh Karthikeyan Iyer
23 Optimizing Evacuations Using Agent-Based Modeling 541
Donie Jardeleza
24 CDLPP: Optimized Multi-Drone Path Planning in Evolving Environments Using Machine Learning for Object Detection 555
Lade Gunakar Rao and K. Rajchandar
25 Development of Low-Cost Road Surface Classification System Using Acceleration Sensors on Motorcycles 567
Nguyen Van Thang, Phi Duc Thang, Le Minh Kien, Nguyen Thi Thu and To Hieu Dao
26 Revolutionizing Education with Edge AI: Exploring Its Role, Impact, and Future Potential 579
Kartikeya Sharma, Pranav Gupta, Radheya Shetty, Preeti Agarwal and Anchit Bijalwan
References 608
Index 611
Part 1: Foundations and Core Concepts of Edge AI 1
1 Edge AI Demystified: From Its Origins to Future Frontiers 3
Preeti Agarwal, Anchit Bijalwan, Ayesha Patel, Atharv Amit Deshpande and Vidhi Panchal
2 Optimizing Deep Learning Models for Edge Devices 39
Haripriya Saraf, Kaavya nair, Aditya Kurup, Preeti Agarwal and Anchit Bijalwan
3 Role of Multi Objective Evolutionary Algorithms in Edge AI System Optimization 67
Preeti Gupta and Sakshi Indolia
4 The Convergence of Edge Computing, AI, and Blockchain: Challenges, Opportunities, and Future Prospects 87
Aditya Ray, Suditi Pradhan, Darsh Iyer, Preeti Agarwal and Anchit Bijalwan
5 Network Optimization in Edge Computing 117
Gargee Thakur, Vaibhav Singh, Riddhima Ghule, Anish Dey, Preeti Agarwal and Anchit Bijalwan
6 Comparative Analysis of Pruning Conventional Machine Learning or Deep Learning Frameworks Utilizing Discrete Wavelet Transform for Iris Biometrics 155
Divyang Jadav, Aditee Moudgil, Nilesh Choudhary and Shruti Daw
7 Convergence of K8s and Istio Deployment on Mission-Critical Environments 181
Arunkumar Arulappan, Vetrivel S.B., Shanmuga Priyan T., Gina Rose G. and Murugan Krishnamoorthy
Part 2: Security, Ethics, and Trust in Edge AI 197
8 Edge AI Security and Privacy: Threats, Solutions, and Best Practices 199
Ishika Mohan, Advika Wankhede, Ishita Manral, Rohit Kadam, Preeti Agarwal and Anchit Bijalwan
9 Edge AI in Cybersecurity 231
Vaishali V. Bodade, Jyoti More, Suraj Khandare and Supriya Joshi
10 Database-Guard Artificial Intelligence: Revolutionizing Database Security with Artificial Intelligence 251
Safwan Hungund and Jyoti Kundale
11 Edge-AI Ledger Docs: Revolutionizing Document Storage and Verification with Blockchain 277
Nilima Patel and Mayank Aggarwal
12 A Lightweight Lie Detector for Resource Constraint Devices 307
Mayur Navin Sharma, Rohan Deep Kujur, Khushi Tulsian, Tejaswini J. Chavan and Atharva Manish
13 AIPendant: An Efficient and Lightweight Threat Detection System for Real-Time Personal Safety 317
Sanghyun Yeo, Vu Minh Phuc and Le Anh Ngoc
Part 3: Edge AI in Industry and Domain-Specific Applications 337
14 Edge AI for Connected & Automated Vehicles: Opportunities & Challenges 339
Alok Ranjan, Ashutosh Bandyopadhyay and Guru Prasad A. S.
15 The Role of Edge Computing in Enhancing Autonomous Vehicle Performance 367
Lakshmeesh Mankame, Anushka Raspayle, Onkar Mane, Preeti Agarwal and Anchit Bijalwan
16 Applying Edge AI in the Environment of Industrial Internet of Things (IIoT) 393
Shraddha C. Subhedar and Deepa Parasar
17 Healthcare Applications of Edge AI 415
Shiwani Gupta, Jagruti Jadhav, Shilpa Mathur, Sampada Bhonde and Pranjali Sankhe
18 Design and Enhance of Data Analysis in Healthcare System with AutoML Business Intelligence Technology 439
Rajendra Kachhava, R.K. Somani and Ravi Khatwal
19 A Case Study from Internet of Things to Edge AI with Challenges in Industry 4.0 447
Harishchander Anandaram, Vinisha Sumra, Roosha Shamoon, Kawerinder Singh Sidhu, Shreenidhi K.S. and Kapil Joshi
20 Edge AI and Blockchain: A Synergy for Water Body Preservation 469
Anjali Arora and Mayank Aggarwal
21 Enhancing Stadium Safety Through AI-Based Detection of Violent Incidents with 360-Degree Cameras 501
Phuong Anh Nguyen, Dung Tran, Trung Duong, Duong Pham, Son Nguyen, Dat Do and Ngoc Le
Part 4: Optimization and Intelligent Decision-Making with Edge AI 515
22 Design of a Deep Reinforcement Learning Approach for Optimization of Task Offloading and Resource Allocation for Edge Computing Networks 517
Anindita Khade and Avaneesh Karthikeyan Iyer
23 Optimizing Evacuations Using Agent-Based Modeling 541
Donie Jardeleza
24 CDLPP: Optimized Multi-Drone Path Planning in Evolving Environments Using Machine Learning for Object Detection 555
Lade Gunakar Rao and K. Rajchandar
25 Development of Low-Cost Road Surface Classification System Using Acceleration Sensors on Motorcycles 567
Nguyen Van Thang, Phi Duc Thang, Le Minh Kien, Nguyen Thi Thu and To Hieu Dao
26 Revolutionizing Education with Edge AI: Exploring Its Role, Impact, and Future Potential 579
Kartikeya Sharma, Pranav Gupta, Radheya Shetty, Preeti Agarwal and Anchit Bijalwan
References 608
Index 611