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Applying AI-Based IoT Systems to Simulation-Based Information Retrieval (Paperback)
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Applying AI-Based IoT Systems to Simulation-Based Information Retrieval (Paperback)
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Communication based on the internet of things (IoT) generates huge
amounts of data from sensors over time, which opens a wide range of
applications and areas for researchers. The application of
analytics, machine learning, and deep learning techniques over such
a large volume of data is a very challenging task. Therefore, it is
essential to find patterns, retrieve novel insights, and predict
future behavior using this large amount of sensory data. Artificial
intelligence (AI) has an important role in facilitating analytics
and learning in the IoT devices. Applying AI-Based IoT Systems to
Simulation-Based Information Retrieval provides relevant frameworks
and the latest empirical research findings in the area. It is ideal
for professionals who wish to improve their understanding of the
strategic role of trust at different levels of the information and
knowledge society and trust at the levels of the global economy,
networks and organizations, teams and work groups, information
systems, and individuals as actors in the networked environments.
Covering topics such as blockchain visualization, computer-aided
drug discovery, and health monitoring, this premier reference
source is an excellent resource for business leaders and
executives, IT managers, security professionals, data scientists,
students and faculty of higher education, librarians, hospital
administrators, researchers, and academicians.
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