 Название: Smart Cities Performability, Cognition, & Security
Автор: Fadi Al-Turjman
Издательство: Springer
Год: 2019 (2020 Edition)
Страниц: 247
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
This book provides knowledge into the intelligence and security areas of smart-city paradigms. It focuses on connected computing devices, mechanical and digital machines, objects, and/or people that are provided with unique identifiers. The authors discuss the ability to transmit data over a wireless network without requiring human-to-human or human-to-computer interaction via secure/intelligent methods. The authors also provide a strong foundation for researchers to advance further in the assessment domain of these topics in the IoT era. The aim of this book is hence to focus on both the design and implementation aspects of the intelligence and security approaches in smart city applications that are enabled and supported by the IoT paradigms.
The objective of this book is to overview existing smart cities applications while focusing on performability, cognition, and security issues. The main focus is on the smart design aspects that can help in realizing such paradigm in an efficient and secured way. The artificial intelligent (AI) techniques as well as new emerging technologies such as the Internet of Things (IoT) and the Smart-Cloud accompanied with critical evaluation metrics, constraints, and open research issues are included for discussion. This conceptual book, which is unique in the field, will assist researchers and professionals working in the area to better assess the proposed smart cities paradigms which have already started to appear in our societies.
- Presents research related to cognitive computing and secured telecommunication paradigms;
- Discusses development of intelligent outdoor monitoring systems via wireless sensing technologies;
- With contributions from researchers, scientists, engineers and practitioners in telecommunication and smart cities.
Contents:
An Effective Design for Polar Codes over Multipath Fading Channels
LearningCity: Knowledge Generation for Smart Cities
Deep Reinforcement Learning Paradigm for Dense Wireless Networks in Smart Cities
Energy Demand Forecasting Using Deep Learning
Context-Aware Location Recommendations for Smart Cities
Fractional Derivatives for Edge Detection: Application to Road Obstacles
Machine Learning Parameter Estimation in a Smart-City Paradigm for the Medical Field
Open Source Tools for Machine Learning with Big Data in Smart Cities
Identity Verification Using Biometrics in Smart-Cities
Network Analysis of Dark Web Traffic Through the Geo-Location of South African IP Address Space
LBCLCT: Location Based Cross Language Cipher Technique
Index - 235
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