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文件名称：Cognitive Computing for Big Data Systems Over IoT: Frameworks, Tools and App
文件大小：7.89MB
文件格式：PDF
更新时间：2021-08-19 06:52:50
大数据
The paradigm shift in towards Internet of Things (IoT) is becoming the vital
component of Internet. Low-cost sensing and actuation are available to the whole
world, which enable seamless information exchange and networked interactions of
physical and digital objects. This interconnectivity together with large-scale data
processing, advanced machine learning, robotics and new fabrication techniques are
steadily bringing in innovation and business models of digital space into the
physical world. Further, IoT is expected to improve the intelligence, promote the
interaction between the human and the environment, as well to enhance reliability,
resilience, operational efficiency, energy efficiency and resource consumption.
Subsequently, many of the IoT systems and technologies are relatively novel, there
are still many untapped applications areas, numerous challenges and issues that
need to be improved.
Cognitive science has broad horizons, which cover different characteristics of
cognition. The field is highly transdisciplinary in nature, combining ideas, principles
and methods of psychology, computer science, linguistics, philosophy, neuroscience,
etc. In addition, cognitive computing is the creation of self-learning
systems that use data mining, pattern recognition and natural language processing
(NLP) to solve complicated problems without constant human oversight.
Cognitive computing will bring a high level of fluidity to analytics. The chapters
included in this book aim on addressing recent trends, innovative ideas, challenges
and cognitive computing solutions in big data and IoT. Moreover, these chapters
specify novel in-depth fundamental research contributions from a methodological/
application in data science accomplishing sustainable solution for the future perspective.
Further, this book provides a comprehensive overview of constituent
paradigms underlying cognitive computing methods, which are illustrating more
attention to big data over IoT problems as they evolve. Hence, the main objective
of the book is to facilitate a forum to a large variety of researchers, where
decision-making approaches under cognitive computing paradigms are adapted to
demonstrate how the proposed procedures as well as big data and IoT problems can
be handled in practice.