Buch, Englisch, 274 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 659 g
Buch, Englisch, 274 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 659 g
Reihe: Transactions on Computer Systems and Networks
ISBN: 978-981-99-5055-3
Verlag: Springer
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction to Drone Data Analytics in Aerial computingAnu sayal, M. Akshadha, CSG Jeswanth kumaar
A Study in Federated Learning Analytics for UAVMinakshi Gautam and Mahalakshmi R
Analysis of Geospatial Data Collected by Drones as Part of Aerial ComputingGaliveeti Poornima, Deepak S Sakkari,Manjunath T N, Sukruth Gowda M A, Pallavi R
Beach wrack identification on unmanned aerial vehicles dataset using Artificial Intelligence for Coastal Environmental ManagementAdimoolam M, Maithili K, S. Leelavathy and N. M. Balamurugan
Environmental drones for autonomous air pollution investigation, detection, and remediationI. Aravindaguru, C. Mathan, B. Sharmila, M. Nagarajapandian, P. Veeramani
Detection of Pathogens in Plant Leaves using Drone-based Deep Learning ApproachRemya S, Jeyakrishnan V, Karunakaran V
Artificial Intelligence Based Drones for Plant Disease DetectionK. Srinivasan,V. Rukkumani, C. Mathan, T. Anitha
Machine vision in UAV Data Analytics for Precision Agriculture Parthasarathy Velusamy, Santhosh Rajendran, Alfred Daniel John William
Smart IoT Drone-Rover for Sustainable Crop Prediction Based on Mutual Subset Feature Selection Using U-Net CNN For Sustainable Crop RecommendationDhiyanesh B, Kiruthiga G, Shakkeera L, Sharmasth Vali Y, Asha A
IoT Based Automatic Drip Irrigation Control Using Intelligent AgricultureDharshan Y, Devasena D, Kayalvizhi S, Sharmila B
IOT-Based Innovative Agriculture Farming System Based on Rover-Drone Surveillance Sensing Unit Using Feature Selection and Classification TechniquesBejoy B. J, Ramkumar M, Shanmugaraja P, Dhiyanesh B, Kiruthiga G, Anusuya V
Village mapping for micro level planning using UAV technologyK. Gajalakshmi, Anantharama V, .Anala M.R
An in-sight analysis of Cyber-security Protocols and the Vulnerabilities in the Drone CommunicationPriyadharshini.SP, P. Balamurugan
Introspecting the Impact of Selected Macro-Economic Variables and Policy Interventions in Unmanned Aerial Vehicle (UAV) Sector: The Case of India
R. Magesh Kumar, P. Srinivasan




