Applying AI-Based IoT Systems to Simulation-Based Information Retrieval (Hardcover)

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.

General

Imprint:	IGI Global
Country of origin:	United States
Release date:	September 2022
Editors:	Bhatia Madhulika • Bhatia Surabhi • Poonam Tanwar • Kuljeet Kaur
Dimensions:	279 x 216mm (L x W)
Format:	Hardcover - Cloth over boards
Pages:	300
ISBN-13:	978-1-66845-255-4
Categories:	Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	1-66845-255-3
Barcode:	9781668452554

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