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Drone Data Analytics in Aerial Computing
Title
Drone Data Analytics in Aerial Computing [electronic resource] / edited by P. Karthikeyan, Sathish Kumar, V. Anbarasu.
ISBN
9789819950560
Edition
1st ed. 2023.
Publication
Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Physical Description
XVI, 274 p. 117 illus., 99 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
October 03, 2023
Series
Transactions on Computer Systems and Networks,
Contents
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. .
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