Advances in Aerial Sensing and Imaging
This groundbreaking book is a comprehensive guide to the technology found in the complex field of aerial sensing and imaging, and the real-world challenges that stem from its growing significance and demand.
The advent of unmanned aerial vehicles (UAVs), or drones, along with advancements in sensor technology and image processing techniques, has further enhanced the capabilities and applications of aerial sensing and imaging. These developments have opened up new research, innovation, and exploration avenues.
Aerial sensing and imaging have rapidly evolved over the past few decades and have revolutionized several fields, including land cover and usage prediction, crop and livestock management, road accident monitoring, poverty estimation, defense, agriculture, forest fire detection, UAV security issues, and open parking management. This book provides a comprehensive understanding and knowledge of the underlying technology and its practical applications in different domains.
Audience
Computer science and artificial intelligence researchers working in the fields of aerial sensing and imaging, as well as professionals working in industries such as agriculture, geology, surveying, urban planning, disaster response, etc; this book provides them with practical guidance and instruction on how to apply aerial sensing and imaging for various purposes and stay up-to-date with the latest developments in the domain.
Inhoudsopgave
Preface xv
1 A Systematic Study on Aerial Images of Various Domains: Competences, Applications, and Futuristic Scope 1
Abhishek Bhola, Bikash Debnath and Ankita Tiwari
1.1 Introduction 2
1.2 Literature Work 5
1.3 Challenges of Object Detection and Classification in Aerial Images 17
1.4 Applications of Aerial Imaging in Various Domains 21
1.5 Conclusions and Future Scope 26
2 Oriental Method to Predict Land Cover and Land Usage Using Keras with VGG16 for Image Recognition 33
Monali Gulhane and Sandeep Kumar
2.1 Introduction 34
2.2 Literature Review 35
2.3 Materials and Methods 37
2.4 Discussion 40
2.5 Result Analysis 41
2.6 Conclusion 43
3 Aerial Imaging Rescue and Integrated System for Road Monitoring Based on AI/ML 47
Munish Kumar, Poonam Jaglan and Yogesh Kakde
3.1 Introduction 48
3.2 Related Work 49
3.3 Number of Accidents, Fatalities, and Injuries: 2016–2022 52
3.4 Proposed Methodology 53
3.5 Result Analysis 61
3.6 Conclusion 63
4 A Machine Learning Approach for Poverty Estimation Using Aerial Images 69
Nandan Banerji, Sreenivasulu Ballem, Siva Mala Munnangi and Sandeep Mittal
4.1 Introduction 70
4.2 Background and Literature Review 73
4.3 Proposed Methodology 76
4.4 Result and Discussion 82
4.5 Conclusion and Future Scope 83
5 Agriculture and the Use of Unmanned Aerial Vehicles (UAVs): Current Practices and Prospects 87
Ajay Kumar Singh and Suneet Gupta
5.1 Introduction 88
5.2 UAVs Classification 90
5.3 Agricultural Use of UAVs 96
5.4 UAVs in Livestock Farming 101
5.5 Challenges 104
5.6 Conclusion 105
6 An Introduction to Deep Learning-Based Object Recognition and Tracking for Enabling Defense Applications 109
Nitish Mahajan, Aditi Chauhan and Monika Kajal
6.1 Introduction 110
6.2 Related Work 111
6.3 Experimental Methods 121
6.4 Results and Outcomes 122
6.5 Conclusion 123
6.6 Future Scope 125
7 A Robust Machine Learning Model for Forest Fire Detection Using Drone Images 129
Chahil Choudhary, Anurag and Pranjal Shukla
7.1 Introduction 130
7.2 Literature Review 131
7.3 Proposed Methodology 133
7.4 Result and Discussion 135
7.5 Conclusion and Future Scope 142
8 Semantic Segmentation of Aerial Images Using Pixel Wise Segmentation 145
Swathi Gowroju, Shilpa Choudhary, Sandhya Raajaani and Regula Srilakshmi
8.1 Introduction 146
8.2 Related Work 147
8.3 Proposed Method 149
8.4 Datasets 153
8.5 Results and Discussion 154
8.6 Conclusion 161
9 Implementation Analysis of Ransomware and Unmanned Aerial Vehicle Attacks: Mitigation Methods and UAV Security Recommendations 165
Sidhant Sharma, Pradeepta Kumar Sarangi, Bhisham Sharma and Girija Bhusan Subudhi
9.1 Introduction 166
9.2 Types of Ransomwares 167
9.3 History of Ransomware 168
9.4 Notable Ransomware Strains and Their Impact 171
9.5 Mitigation Methods for Ransomware Attacks 184
9.6 Cybersecurity in UAVs (Unmanned Aerial Vehicles) 185
9.7 Experimental analysis of Wi-Fi Attack on Ryze Tello UAVs 194
9.8 Results and Discussion 198
9.9 Conclusion and Future Scope 206
10 A Framework for Detection of Overall Emotional Score of an Event from the Images Captured by a Drone 213
P.V.V.S. Srinivas, Dhiren Dommeti, Pragnyaban Mishra and T.K. Rama Krishna Rao
10.1 Introduction 214
10.2 Literature Review 216
10.3 Proposed Work 220
10.4 Experimentation and Results 223
10.5 Future Work and Conclusion 230
11 Drone-Assisted Image Forgery Detection Using Generative Adversarial Net-Based Module 245
Swathi Gowroju, Shilpa Choudhary, Medipally Rishitha, Singanaboina Tejaswi, Lankala Shashank Reddy and Mallepally Sujith Reddy
11.1 Introduction 246
11.2 Literature Survey 247
11.3 Proposed System 250
11.4 Results 256
11.5 Conclusion 264
12 Optimizing the Identification and Utilization of Open Parking Spaces Through Advanced Machine Learning 267
Harish Padmanaban P. C. and Yogesh Kumar Sharma
12.1 Introduction 267
12.2 Proposed Framework Optimized Parking Space Identifier (OPSI) 270
12.3 Potential Impact 281
12.4 Application and Results 284
12.5 Discussion and Limitations 289
12.6 Future Work 290
12.7 Conclusion 290
13 Graphical Password Authentication Using Python for Aerial Devices/Drones 295
Sushma Singh and Dolly Sharma
13.1 Introduction 296
13.2 Literature Review 297
13.3 Methodology 298
13.4 A Brief Overview of a Drone and Authentication 299
13.5 Password Cracking 305
13.6 Data Analysis 307
13.7 Discussion 309
13.8 Conclusion and Future Scope 309
14 A Study Centering on the Data and Processing for Remote Sensing Utilizing from Annoyed Aerial Vehicles 313
Vandna Bansla, Sandeep Kumar, Vibhoo Sharma, Girish Singh Bisht and Akanksha Srivastav
14.1 Introduction 314
14.2 An Acquisition Method for 3D Data Utilising Annoyed Aerial Vehicles 315
14.3 Background and Literature of Review 317
14.4 Research Gap 319
14.5 Methodology 319
14.6 Discussion 321
14.7 Conclusion 327
15 Satellite Image Classification Using Convolutional Neural Network 333
Pradeepta Kumar Sarangi, Bhisham Sharma, Lekha Rani and Monica Dutta
15.1 Introduction 334
15.2 Literature Review 335
15.3 Objectives of this Research Work 336
15.4 Description of the Dataset 337
15.5 Theoretical Framework 337
15.6 Implementation and Results 339
15.7 Conclusion and Future Scope 350
16 Edge Computing in Aerial Imaging – A Research Perspective 355
Divya Vetriveeran, Rakoth Kandan Sambandam, Jenefa J. and Leena Sri R.
16.1 Introduction 355
16.2 Research Applications of Aerial Imaging 357
16.3 Edge Computing and Aerial Imaging 366
16.4 Comparative Analysis of the Aerial Imaging Algorithms and Architectures 376
16.5 Discussion 379
16.6 Conclusion 380
17 Aerial Sensing and Imaging Analysis for Agriculture 383
Monika Kajal and Aditi Chauhan
17.1 Introduction 384
17.2 Experimental Methods and Techniques 388
17.3 Aerial Imaging and Sensing Applications in Agriculture 390
17.4 Aerial Imaging and Sensing Applications in Livestock Farming 398
17.5 Challenges in Aerial Sensing and Imaging in Agriculture and Livestock Farming 404
17.6 Conclusion 406
References 406
Index 411
Over de auteur
Sandeep Kumar, Ph D, is a professor in the Department of Computer Science and Engineering, K L Deemed to be University, Vijayawada, Andhra Pradesh, India. He has been granted six patents and successfully filed another ten. He has published more than 100 research papers in various national and international journals and proceedings of reputed national and international conferences.
Nageswara Rao Moparthi, Ph D, is a professor at KL University in the Department of Computer and Engineering. He has 13 years of IT industry exposure with major MNC’s and seven years of teaching research experience. He has published 25 articles in reputed Scopus and SCIE/ESCI international journals.
Abhishek Bhola, Ph D, is an associate professor in the Department of Computer Science and Engineering at K L Deemed to be University, Vijayawada, Andhra Pradesh, India. He has more than seven years of experience in academics and research. Additionally, he has published several research papers in various international journals and conferences.
Ravinder Kaur, Ph D, is an assistant professor in the Department of Computer Science and Engineering (CSE) at the University Institute of Engineering, Chandigarh University, Punjab, India. She has published research papers in various renowned international conferences and SCI-indexed journals.
A. Senthil, Ph D, is a professor in the Department of Computer Science and Engineering, KLEF Deemed to be University, A.P., India. He has been in teaching and research for the past 21 years, working as a Professor, Head of Department, and Associate Dean in leading institutions. He has also served as an ABET-USA program evaluator for the Computing Accreditation Commission (CAC) for the last four years.
K.M.V.V. Prasad, Ph D, is an associate professor in the Department of Electronics and Telecommunications, Symbiosis International (Deemed University), Pune, India, with eight years of teaching experience. He has authored and co-authored many papers in international journals and both national and international conferences.
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