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Internet of things, smart computing ...

Dey, Nilanjan.

Internet of things, smart computing and technologya roadmap ahead /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Internet of things, smart computing and technologyedited by Nilanjan Dey ... [et al.].
其他題名:	a roadmap ahead /
其他作者:	Dey, Nilanjan.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xvi, 403 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Machine learning.
電子資源:	https://doi.org/10.1007/978-3-030-39047-1
ISBN:	9783030390471$q(electronic bk.)

Internet of things, smart computing and technologya roadmap ahead /
Internet of things, smart computing and technologya roadmap ahead /[electronic resource] :edited by Nilanjan Dey ... [et al.]. - Cham :Springer International Publishing :2020. - xvi, 403 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v.2662198-4182 ;. - Studies in systems, decision and control ;v.3..

Efficacy of a classical and a few modified machine learning algorithms in forecasting financial time series -- Analysis of facial expression recognition of visible, thermal and fused imaginary in indoor and outdoor environment -- AI - Assisted Chatbot for E-Commerce to Address Selection of Products from Multiple Products -- A Novel Approach to detect microcalcification for Accurate Detection for Diagnosis of Breast Cancer -- Rethinking Decentralised Identifiers and Verifiable Credentials for the Internet of Things -- The Invisible Eye - A Security Architecture to Protect Motorways.

This book addresses a broad range of topics concerning machine learning, big data, the Internet of things (IoT), and security in the IoT. Its goal is to bring together several innovative studies on these areas, in order to help researchers, engineers, and designers in several interdisciplinary domains pursue related applications. It presents an overview of the various algorithms used, focusing on the advantages and disadvantages of each in the fields of machine learning and big data. It also covers next-generation computing paradigms that are expected to support wireless networking with high data transfer rates and autonomous decision-making capabilities. In turn, the book discusses IoT applications (e.g. healthcare applications) that generate a huge amount of sensor data and imaging data that must be handled correctly for further processing. In the traditional IoT ecosystem, cloud computing offers a solution for the efficient management of huge amounts of data, thanks to its ability to access shared resources and provide a common infrastructure in a ubiquitous manner. Though these new technologies are invaluable, they also reveal serious IoT security challenges. IoT applications are vulnerable to various types of attack such as eavesdropping, spoofing and false data injection, the man-in-the-middle attack, replay attack, denial-of-service attack, jamming attack, flooding attack, etc. These and other security issues in the Internet of things are explored in detail. In addition to highlighting outstanding research and recent advances from around the globe, the book reports on current challenges and future directions in the IoT. Accordingly, it offers engineers, professionals, researchers, and designers an applied-oriented resource to support them in a broad range of interdisciplinary areas.

ISBN: 9783030390471$q(electronic bk.)

Standard No.: 10.1007/978-3-030-39047-1doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .I584 2020

Dewey Class. No.: 629.8

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520 $a This book addresses a broad range of topics concerning machine learning, big data, the Internet of things (IoT), and security in the IoT. Its goal is to bring together several innovative studies on these areas, in order to help researchers, engineers, and designers in several interdisciplinary domains pursue related applications. It presents an overview of the various algorithms used, focusing on the advantages and disadvantages of each in the fields of machine learning and big data. It also covers next-generation computing paradigms that are expected to support wireless networking with high data transfer rates and autonomous decision-making capabilities. In turn, the book discusses IoT applications (e.g. healthcare applications) that generate a huge amount of sensor data and imaging data that must be handled correctly for further processing. In the traditional IoT ecosystem, cloud computing offers a solution for the efficient management of huge amounts of data, thanks to its ability to access shared resources and provide a common infrastructure in a ubiquitous manner. Though these new technologies are invaluable, they also reveal serious IoT security challenges. IoT applications are vulnerable to various types of attack such as eavesdropping, spoofing and false data injection, the man-in-the-middle attack, replay attack, denial-of-service attack, jamming attack, flooding attack, etc. These and other security issues in the Internet of things are explored in detail. In addition to highlighting outstanding research and recent advances from around the globe, the book reports on current challenges and future directions in the IoT. Accordingly, it offers engineers, professionals, researchers, and designers an applied-oriented resource to support them in a broad range of interdisciplinary areas.
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