Scientific Library of Tomsk State University

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Unmanned aerial vehicles and multidisciplinary applications using AI techniques [edited by] Bella Mary I. Thusnavis, K. Martin Sagayam, Ahmed A. Elngar.

Contributor(s): Thusnavis, Mary Bella I, 1985- | Sagayam, K. Martin, 1987- | Elngar, Ahmed AMaterial type: TextTextSeries: Advances in computational intelligence and robotics (ACIR) book seriesPublisher: Hershey, PA IGI Global, Engineering Science Reference, an imprint of IGI Global, [2022]Description: 1 online resource (xix, 306 pages) illustrations (some color)ISBN: 1799887650; 9781799887669; 1799887669; 9781799887652Subject(s): Drone aircraft -- Industrial applications | Aerial surveillance | Drones -- Applications industrielles | Surveillance aérienne | Aerial surveillanceGenre/Form: EBSCO eBooks DDC classification: 629.133/39 LOC classification: TL685.35 | .U555 2022Online resources: EBSCOhost
Contents:
Chapter 1. UAVs for multidisciplinary applications: introduction -- 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: an outlook -- Chapter 6. Urban intelligence and IoT-UAV applications in smart cities: unmanned aerial vehicle-based city management, human activity recognition, and monitoring for health -- 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: machine learning integration for projects (MLI4P) -- Chapter 10. Future trends and challenges of UAV: conclusion.
Summary: "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"-- Provided by publisher.
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"Premier reference source"--Cover.

Includes bibliographical references and index.

"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"-- Provided by publisher.

Chapter 1. UAVs for multidisciplinary applications: introduction -- 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: an outlook -- Chapter 6. Urban intelligence and IoT-UAV applications in smart cities: unmanned aerial vehicle-based city management, human activity recognition, and monitoring for health -- 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: machine learning integration for projects (MLI4P) -- Chapter 10. Future trends and challenges of UAV: conclusion.

Description based on online resource; title from digital title page (viewed on October 10, 2022).

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