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Crowdsourcing and human-in-the-loop for IoT

Research output: Chapter in Book/Report/Conference proceedingChapter

Standard

Crowdsourcing and human-in-the-loop for IoT. / Gonzalez, Luis Ibanez; Reeves, Neal; Simperl, Elena.

Exploiting the Internet of Things (IoT) Data Deluge. WILEY-BLACKWELL, 2020. p. 91-106.

Research output: Chapter in Book/Report/Conference proceedingChapter

Harvard

Gonzalez, LI, Reeves, N & Simperl, E 2020, Crowdsourcing and human-in-the-loop for IoT. in Exploiting the Internet of Things (IoT) Data Deluge. WILEY-BLACKWELL, pp. 91-106.

APA

Gonzalez, L. I., Reeves, N., & Simperl, E. (2020). Crowdsourcing and human-in-the-loop for IoT. In Exploiting the Internet of Things (IoT) Data Deluge (pp. 91-106). WILEY-BLACKWELL.

Vancouver

Gonzalez LI, Reeves N, Simperl E. Crowdsourcing and human-in-the-loop for IoT. In Exploiting the Internet of Things (IoT) Data Deluge. WILEY-BLACKWELL. 2020. p. 91-106

Author

Gonzalez, Luis Ibanez ; Reeves, Neal ; Simperl, Elena. / Crowdsourcing and human-in-the-loop for IoT. Exploiting the Internet of Things (IoT) Data Deluge. WILEY-BLACKWELL, 2020. pp. 91-106

Bibtex Download

@inbook{c887c084ee6a4a8db3e22e07a740d061,
title = "Crowdsourcing and human-in-the-loop for IoT",
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.",
author = "Gonzalez, {Luis Ibanez} and Neal Reeves and Elena Simperl",
year = "2020",
month = "3",
language = "English",
isbn = "9781119545262",
pages = "91--106",
booktitle = "Exploiting the Internet of Things (IoT) Data Deluge",
publisher = "WILEY-BLACKWELL",

}

RIS (suitable for import to EndNote) Download

TY - CHAP

T1 - Crowdsourcing and human-in-the-loop for IoT

AU - Gonzalez, Luis Ibanez

AU - Reeves, Neal

AU - Simperl, Elena

PY - 2020/3

Y1 - 2020/3

N2 - 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.

AB - 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.

M3 - Chapter

SN - 9781119545262

SP - 91

EP - 106

BT - Exploiting the Internet of Things (IoT) Data Deluge

PB - WILEY-BLACKWELL

ER -

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