Emerging technologies for smart cities : select proceedings of EGTET 2020 / Prabin K. Bora, Sukumar Nandi, Shakuntala Laskar, editors.
2021
TD159.4 .I48 2020
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Details
Title
Emerging technologies for smart cities : select proceedings of EGTET 2020 / Prabin K. Bora, Sukumar Nandi, Shakuntala Laskar, editors.
Meeting Name
ISBN
9789811615504 (electronic bk.)
9811615500 (electronic bk.)
9789811615498
9811615497
9811615500 (electronic bk.)
9789811615498
9811615497
Published
Singapore : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource : illustrations (chiefly color)
Item Number
10.1007/978-981-16-1550-4 doi
Call Number
TD159.4 .I48 2020
Dewey Decimal Classification
307.760285
Summary
This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topical sections include Smart Buildings, Infrastructures and Disaster Management; Smart Governance; Technologies for Smart Cities, and Wireless Connectivity for Smart Cities. This book will cater to students, researchers, industry professionals, and policy making bodies interested and involved in the planning and implementation of smart city projects.
Note
International conference proceedings.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 18, 2021).
Series
Lecture notes in electrical engineering ; v. 765. 1876-1100
Available in Other Form
Print version: 9789811615498
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Table of Contents
Integration of Internet of Things and Blockchain Technology for Smart Cities
An IoT and Machine Learning Based Crop Prediction System for Precision Agriculture
A Smart Feature Reduction Approach to Detect Botnet Attack in IoT
An approach to handle Heterogeneous Healthcare IoT data using Deep Convolutional Neural Network
Designing of NimbleArm
A Low-Cost and Interactive Semi-Autonomous Robotic Arm
Cascade-based Pedestrian Detector using Edge and Pattern features.
An IoT and Machine Learning Based Crop Prediction System for Precision Agriculture
A Smart Feature Reduction Approach to Detect Botnet Attack in IoT
An approach to handle Heterogeneous Healthcare IoT data using Deep Convolutional Neural Network
Designing of NimbleArm
A Low-Cost and Interactive Semi-Autonomous Robotic Arm
Cascade-based Pedestrian Detector using Edge and Pattern features.