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Full Description
The Internet of Things (IoT) concept is defined as a flexible and futuristic network where all the different types of devices and smart objects can become seamlessly connected to each other and can actively participate in all types of processes which are happening around us. The grand objective of making physical, mechanical, electrical, and electronic devices to use the deeper and extreme connectivity and service-enablement techniques is to make them intelligent in their deeds, decisions, and deals. Cognitive IoT is the application of cognitive computing technologies to the data which is generated by the connected devices of the IoT ecosystem. Cognition means thinking; however, computers are not yet fully capable of mimicking human like thought. However, the present-day computer systems can perform some functions which are like the capability of human beings to think.
Cognitive Internet of Things: Enabling Technologies, Platforms, and Use Cases explains the concepts surrounding Cognitive IoT. It also looks at the use cases and such supporting technologies as artificial intelligence and machine learning that act as key enablers of Cognitive IoT ecosystem. Different Cognitive IoT enabled platforms like IBM Watson and other product specific use cases like Amazon Alexa are covered in depth. Other highlights of the book include:
Demystifying the cognitive computing paradigm
Delineating the key capabilities of cognitive cloud environments
Deep learning algorithms for cognitive IoT solutions
Natural language processing (NLP) methods for cognitive IoT systems
Designing a secure infrastructure for cognitive IoT platforms and applications
Contents
1. Describing the Cognitive IoT Paradigm 2. Demystifying the Cognitive Computing Paradigm 3. The Cognitive IoT: The Platforms, Technologies and Their Use cases 4. Delineating the Key Capabilities of Cognitive Cloud Environments 5. Machine Learning (ML) Algorithms for Enabling the Cognitive Internet of Things (CIoT) 6. Unsupervised and Semi-supervised Machine Learning Algorithms for Cognitive IoT Systems 7. Deep Learning Algorithms for Cognitive IoT Solutions 8. Computer Vision (CV) Technologies and Tools for Vision-based Cognitive IoT Systems 9. Natural Language Processing (NLP) Methods for Cognitive IoT Systems 10. Design of a Secure Infrastructure for Cognitive IoT Platforms and Applications 11. Revolutionizing Manufacturing Using Cognitive IoT Technologies 12. Edge AI - The Consumer, Social, and Industry Use Cases
