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Drone data analytics in aerial computing

Karttikeyan, Pa.

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Drone data analytics in aerial computing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Drone data analytics in aerial computing/ edited by P. Karthikeyan, Sathish Kumar, V. Anbarasu.
other author:	Karttikeyan, Pa.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	xvi, 274 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Drone aircraft - Data processing. -
Online resource:	https://doi.org/10.1007/978-981-99-5056-0
ISBN:	9789819950560

Drone data analytics in aerial computing
Drone data analytics in aerial computing[electronic resource] /edited by P. Karthikeyan, Sathish Kumar, V. Anbarasu. - Singapore :Springer Nature Singapore :2023. - xvi, 274 p. :ill., digital ;24 cm. - Transactions on computer systems and networks,2730-7492. - Transactions on computer systems and networks..

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.

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.

ISBN: 9789819950560

Standard No.: 10.1007/978-981-99-5056-0doiSubjects--Topical Terms:

3666622
Drone aircraft
--Data processing.

LC Class. No.: Q342

Dewey Class. No.: 629.1333902856312

Drone data analytics in aerial computing
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245 0 0 $a Drone data analytics in aerial computing $h [electronic resource] / $c edited by P. Karthikeyan, Sathish Kumar, V. Anbarasu.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xvi, 274 p. : $b ill., digital ; $c 24 cm.
490 1 $a Transactions on computer systems and networks, $x 2730-7492
505 0 $a 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.
520 $a 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.
650 0 $a Drone aircraft $x Data processing. $3 3666622
650 0 $a Data mining. $3 562972
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Data Analysis and Big Data. $3 3538537
700 1 $a Karttikeyan, Pa. $3 3666619
700 1 $a Kumar, Sathish A. P. $3 3666620
700 1 $a Anbarasu, V. $3 3666621
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Transactions on computer systems and networks. $3 3514031
856 4 0 $u https://doi.org/10.1007/978-981-99-5056-0
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)