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Unmanned aerial vehicles and multidisciplinary applications using AI techniques

Record Type:	Electronic resources : Monograph/item
Title/Author:	Unmanned aerial vehicles and multidisciplinary applications using AI techniquesBella Mary I. Thusnavis, K. Martin Sagayam, and Ahmed A. Elngar, editors.
other author:	Thusnavis, Mary Bella I.,
Published:	Hershey, Pennsylvania :IGI Global,2022.
Description:	1 online resource (306 p.)
Subject:	Drone aircraftIndustrial applications.
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-8763-8
ISBN:	9781799887652$q(ebook)

Unmanned aerial vehicles and multidisciplinary applications using AI techniques
Unmanned aerial vehicles and multidisciplinary applications using AI techniques[electronic resource] /Bella Mary I. Thusnavis, K. Martin Sagayam, and Ahmed A. Elngar, editors. - Hershey, Pennsylvania :IGI Global,2022. - 1 online resource (306 p.)

Includes bibliographical references and index.

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.

"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"--

Mode of access: World Wide Web.

ISBN: 9781799887652$q(ebook)Subjects--Topical Terms:

757093
Drone aircraft
--Industrial applications.Subjects--Index Terms:

Agricultural Applications.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: TL685.35 / .U555 2022eb

Dewey Class. No.: 629.133/39

Unmanned aerial vehicles and multidisciplinary applications using AI techniques
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245 0 0 $a Unmanned aerial vehicles and multidisciplinary applications using AI techniques $h [electronic resource] / $c Bella Mary I. Thusnavis, K. Martin Sagayam, and Ahmed A. Elngar, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2022.
300 $a 1 online resource (306 p.)
504 $a Includes bibliographical references and index.
505 0 $a 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.
520 3 $a "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"-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
650 0 $a Drone aircraft $x Industrial applications. $3 757093
650 0 $a Aerial surveillance. $3 801335
653 $a Agricultural Applications.
653 $a Amphibius Unmanned Aerial Vehicle Systems.
653 $a Business Transformation.
653 $a Enterprise Architecture Projects.
653 $a Human Activity Recognition.
653 $a Machine Learning Integration for Projects (MLI4P)
653 $a Mathematical Modeling.
653 $a Ortho-Photos.
653 $a Recommendation of Crops.
653 $a Smart Cities.
653 $a Smart Farming.
653 $a Soil Health Assessment.
653 $a Urban Intelligence.
653 $a Vehicular Surveillance Systems.
653 $a Yield Prediction.
655 4 $a Electronic books. $2 local. $3 214472
700 1 $a Thusnavis, Mary Bella I., $d 1985- $3 995188
700 1 $a Sagayam, K. Martin, $d 1987- $e editor. $3 868344
700 1 $a Elngar, Ahmed A. $3 976738
710 2 $a IGI Global. $3 529832
776 0 8 $i Print version: $z 1799887634 $z 9781799887638
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-8763-8