Название: Cognitive Internet of Things: Frameworks, Tools and Applications
Автор: Huimin Lu
Издательство: Springer
Год: 2019 (2020 Edition)
Страниц: 504
Язык: английский
Формат: pdf (true)
Размер: 20.9 MB

This book provides insights into the research in the fields of artificial intelligence in combination with Internet of Things (IoT) technologies. Today, the integration of artificial intelligence and IoT technologies is attracting considerable interest from both researchers and developers from academic fields and industries around the globe. It is foreseeable that the next generation of IoT research will focus on artificial intelligence/beyond artificial intelligence approaches. The rapidly growing numbers of artificial intelligence algorithms and big data solutions have significantly increased the number of potential applications for IoT technologies, but they have also created new challenges for the artificial intelligence community. This book shares the latest scientific advances in this area.

In recent years, Artificial Intelligence (AI) has attracted attention as a key for growth in developed countries and developing countries. The attention has been focused mainly on developing new deep learning-based Information Communication Technology (ICT) and Internet of Things (IoT) applications. Although recently developed deep learning technology certainly excels in extracting certain patterns, there are many limitations. Most of recent models are overly dependent on big data, lack a self-idea function, and are complicated. In order to overcome these limitations and to solve the real-world industrial problems, Cognitive Computing (CC) and Computational Neuroscience (CN) are driving as one of the best tools for future brain-inspired intelligence IoTs.

Rather than merely developing next-generation AI models, we are trying to provide a platform to share up-to-date scientific and industrial achievements of general-purpose intelligence cognition methods. These methods provide efficient tools to solve the issues of recent AI models, and capture remarkable human learning abilities, combining the strengths of CC/CN and deep generative neural networks.

The overall aim of this book is to collect the state-of-the-art contributions on the Computational Neuroscience, Computational Cognition and Perception, Computer Vision, Natural Language Processing, Human Action Analysis, and related applications.