"This comprehensive edited book covers Artificial techniques, pattern recognition, machine and deep learning--based methods and techniques applied to different real time applications of unmanned aerial vehicles (UAV) with the goal to synthesize the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems and numerous application areas"--.

• Cover
• Title Page
• Copyright Page
• Book Series
• Table of Contents
• Detailed Table of Contents
• Preface
• Chapter 1: UAVs for Multidisciplinary Applications
• Chapter 2: A Review on the Applications of Unmanned Aerial Vehicles and Internet of Things Towards Smart Farming
• Chapter 3: Recommendation of Crop and Yield Prediction by Assessing Soil Health From Ortho-Photos
• Chapter 4: Design and Implementation of an Amphibious Unmanned Aerial Vehicle System for Agriculture Applications
• Chapter 5: Scope of UAVs for Smart Cities
• Chapter 6: Urban Intelligence and IoT-UAV Applications in Smart Cities
• Chapter 7: Mathematical Modeling of Unmanned Aerial Vehicles for Smart City Vehicular Surveillance Systems
• Chapter 8: Unmanned Aerial Vehicle Brands Fan Page Engagement Behavior Analytics
• Chapter 9: Business Transformation and Enterprise Architecture Projects
• Chapter 10: Future Trends and Challenges of UAV
• Compilation of References
• Related References
• About the Contributors
• Index