Machine Learning for Drone-Enabled IoT Networks : Opportunities, Developments, and Trends / edited by Jahan Hassan, Sara Khalifa, Prasant Misra

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable DevelopmentVerlag: Cham : Springer Nature Switzerland, 2025Verlag: Cham : Imprint: Springer, 2025Auflage: 1st ed. 2025Beschreibung: 1 Online-Ressource(IX, 207 p. 52 illus., 42 illus. in color.)ISBN:

9783031809613

Schlagwörter:

006.31 23

DOI: DOI: 10.1007/978-3-031-80961-3Online-Ressourcen:

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Zusammenfassung: Machine learning algorithms for drone-enabled IoT networks -- Sensing and data collection with drones for IoT applications -- Data analysis and processing for IoT networks assisted by drones -- Energy-efficient and scalable solutions for drone-assisted IoT networks -- Security and privacy issues in drone-enabled IoT networks -- Emerging trends and future directions in ML for drone-assisted IoT networks.Zusammenfassung: This book aims to explore the latest developments, challenges, and opportunities in the application of machine learning techniques to enhance the performance and efficiency of IoT networks assisted by aerial unmanned vehicles (UAVs), commonly known as drones. The book aims to include cutting edge research and development on a number of areas within the topic including but not limited to: •Machine learning algorithms for drone-enabled IoT networks •Sensing and data collection with drones for IoT applications •Data analysis and processing for IoT networks assisted by drones •Energy-efficient and scalable solutions for drone-assisted IoT networks •Security and privacy issues in drone-enabled IoT networks •Emerging trends and future directions in ML for drone-assisted IoT networks.PPN: PPN: 192476928XPackage identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS

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