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Crowdsourcing and human-in-the-loop for IoT

Research output: Chapter in Book/Report/Conference proceedingChapter

Luis Ibanez Gonzalez, Neal Reeves, Elena Simperl

Original languageEnglish
Title of host publicationExploiting the Internet of Things (IoT) Data Deluge
PublisherWILEY-BLACKWELL
Chapter8
Pages91-106
ISBN (Electronic)9781119545279
ISBN (Print)9781119545262
Publication statusPublished - Mar 2020

King's Authors

Abstract

Written by experts in the field, this book addresses the IoT technology stack, from connectivity through data platforms to end-user case studies, and considers the tradeoffs between business needs and data security and privacy throughout. There is a particular emphasis on data processing technologies that enable the extraction of actionable insights from data to inform improved decision making. These include artificial intelligence techniques such as stream processing, deep learning and knowledge graphs, as well as data interoperability and the key aspects of privacy, security and trust. Additional aspects covered include: creating and supporting IoT ecosystems; edge computing; data mining of sensor datasets; and crowd-sourcing, amongst others. The book also presents several sections featuring use cases across a range of application areas such as smart energy, transportation, smart factories, and more. The book concludes with a chapter on key considerations when deploying IoT technologies in the enterprise, followed by a brief review of future research directions and challenges.

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