The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems

Author: Dinesh Peter

Book Overview: This book discusses the rapid development of the Internet of Things (IoT) and its focus on research in smart cities, particularly on surveillance tracking systems. It emphasizes the need for efficient surveillance tracking systems in the Big Data era, requiring the capability of quickly abstracting useful information from increasing amounts of data.

Key Concepts:

Surveillance Tracking Systems: The book examines the current state of surveillance tracking systems, cognitive cloud architecture for resolving critical issues in surveillance tracking systems, and research opportunities in cognitive computing for surveillance tracking systems.

Cognitive Computing: It covers cognitive computing architectures and approaches, cognitive computing and neural networks, complex analytics and machine learning, design of a symbiotic agent for recognizing real space in ubiquitous environments, and more.

Machine Learning: The book discusses supervised regression and classification methods, clustering and dimensionality reduction methods, model development for machine learning applications, intelligent machines and deep learning networks.

Key Features:

Cognitive Computing Models: It includes coverage of cognitive computing models for scalable environments, privacy and security aspects of surveillance tracking systems, strategies and experiences in cloud architecture and service platform design.

Real-time Information Fusion: The book emphasizes the importance of real-time information fusion in mission critical surveillance tasks for various applications.

Automated IT Systems: It presents concepts aimed at creating automated IT systems capable of resolving problems without demanding human aid.