This book discusses the latest research, theoretical, and experimental research innovations in drone data analytics in aerial computing. Drone data analytics guarantees that the right people have the correct data at their fingertips whenever they need it. The contents also discuss the challenges faced with drone data analytics, such as due to the high mobility of drones, aerial computing is significantly different from terrestrial computing. It also includes case studies from leading drone vendors. The book also focuses on the comparison of data management and security mechanisms in drone data analytics. This book is useful to those working in agriculture, mining, waste management, and defenses department.

Discusses state-of-the-art drone data analytics in aerial computing with the use of illustrations Covers the latest developments in drone data analytics in agriculture Presents a comparison of the data management and security mechanisms in drone data analytics

Autorentext
P. Karthikeyan obtained his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, and Tamil Nadu, India, in 2005 and received his Master of Engineering (M.E) in Computer Science and Engineering from Anna University, Coimbatore, India, in 2009. He completed his Ph.D. degree at Anna University, Chennai, in 2018. He has completed postdoctoral fellowship at National Chung Cheng University, Taiwan. He was skilled in developing projects and carrying out research in cloud computing and deep learning with programming skills in Java, Python, R, and C. He published more than 30 international journals with good impact factors and presented at more than 10 international conferences. He was the reviewer of Elsevier, Springer, Inderscience, and reputed Scopus-indexed journals. He is an editorial board member in EAI Endorsed Transactions on Energy Web, The International Arab Journal of Information Technology, and Blue Eyes Intelligence Engineering andSciences Publication journal.
Sathish Kumar is currently an associate professor of Computer Science in the Department of Electrical Engineering and Computer Science at Cleveland State University (CSU). He is also serving as the co-director of CSU T.E.C.H Hub. He is also currently serving as an associate editor for IEEE Access. He has had experience in the industry for over a decade before joining academia as a full-time faculty member in 2013. His research interests are cybersecurity, machine learning, distributed systems, and the Internet of Things and related applications. His research has been supported by the National Science Foundation, Air Force Research Laboratory, Cleveland Foundation, Center for Disease Control, and National Institutes of Health. He has also served on the program committees of numerous international conferences, as a panelist for NSF, and as a reviewer for several IEEE Transactions. He obtained his Ph.D. in Computer Science and Engineering from the University of Louisville, KY, USA.
V. Anbarasu received his B.E. from SVNIT, Surat, Gujarat, in Computer Engineering and M.Tech. in IT and Ph.D. in CSE from Sathyabama University, Chennai, in 2006 and 2014, respectively. Presently, he is working as an associate professor in the Department of Computer Science & Engineering, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu. He also has 18 years of work experience in engineering colleges around India. He has published 25 national and international journals and 31 conference publications, attended various workshops and seminars, and delivered lectures in workshops during his career. He has five patents. and also acting as a guest faculty in BITS, Pilani, and taking various offline/online courses. He is currently the reviewer of Elsevier, Springer, Inderscience, and reputed Scopus-indexed journals.

Inhalt
Introduction to Drone Data Analytics in Aerial computing.- A Study in Federated Learning Analytics for UAV.- Analysis of Geospatial Data Collected by Drones as Part of Aerial Computing.- Beach wrack identification on unmanned aerial vehicles dataset using Artificial Intelligence for Coastal Environmental Management.- Environmental drones for autonomous air pollution investigation, detection, and remediation.- Detection of Pathogens in Plant Leaves using Drone-based Deep Learning Approach.- Artificial Intelligence Based Drones for Plant Disease Detection.- Machine vision in UAV Data Analytics for Precision Agriculture.- Smart IoT Drone-Rover for Sustainable Crop Prediction Based on Mutual Subset Feature Selection Using U-Net CNN For Sustainable Crop Recommendation.- IoT Based Automatic Drip Irrigation Control Using Intelligent Agriculture.- IOT-Based Innovative Agriculture Farming System Based on Rover-Drone Surveil-lance Sensing Unit Using Feature Selection and Classification Techniques.- Village mapping for micro level planning using UAV technology.- An in-sight analysis of Cyber-security Protocols and the Vulnerabilities in the Drone Communication.- Introspecting the Impact of Selected Macro-Economic Variables and Policy Interventions in Unmanned Aerial Vehicle (UAV) Sector: The Case of India.