Loading…

Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices

With the rapid development and usage of Internet-of-Things (IoT) and smart-home devices, researchers continue efforts to improve the "smartness" of those devices to address daily needs in people's lives. Such efforts usually begin with understanding evolving user behaviors on how huma...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2021-09
Main Authors: Yu, Haoxiang, Hua, Jie, Julien, Christine
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Yu, Haoxiang
Hua, Jie
Julien, Christine
description With the rapid development and usage of Internet-of-Things (IoT) and smart-home devices, researchers continue efforts to improve the "smartness" of those devices to address daily needs in people's lives. Such efforts usually begin with understanding evolving user behaviors on how humans utilize the devices and what they expect in terms of their behavior. However, while research efforts abound, there is a very limited number of datasets that researchers can use to both understand how people use IoT devices and to evaluate algorithms or systems for smart spaces. In this paper, we collect and characterize more than 50,000 recipes from the online If-This-Then-That (IFTTT) service to understand a seemingly straightforward but complicated question: "What kinds of behaviors do humans expect from their IoT devices?"
doi_str_mv 10.48550/arxiv.2110.00068
format article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2578928961</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2578928961</sourcerecordid><originalsourceid>FETCH-LOGICAL-a521-301707d64d2262bf52f00860c5c472ec490b450a6f303ca66c40605590b9c0ec3</originalsourceid><addsrcrecordid>eNotz01Lw0AUheFBECy1P8DdgBtdpN7c-UjirrTWBgqCjisXZTqZaErN1NxJtf_egK4OPIsDL2NXKUxlrhTc2e6nOU4xHQAAdH7GRihEmuQS8YJNiHYDo85QKTFibwsbLfl4z2et3Z-oIR5qXi6NMfzZu-bgicfAX2JfnfgqfPNV_2lb4q_kedlG37U-JqFOzEfTvhO_KYO55Qt_bJynS3Ze2z35yf-OmVk-mPkqWT89lvPZOrEK00RAmkFWaVkhatzWCmuAXINTTmbonSxgKxVYXQsQzmrtJGhQauDCgXdizK7_bg9d-Oo9xc0u9N1QQxtUWV5gXuhU_AI41VFZ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2578928961</pqid></control><display><type>article</type><title>Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices</title><source>Publicly Available Content (ProQuest)</source><creator>Yu, Haoxiang ; Hua, Jie ; Julien, Christine</creator><creatorcontrib>Yu, Haoxiang ; Hua, Jie ; Julien, Christine</creatorcontrib><description>With the rapid development and usage of Internet-of-Things (IoT) and smart-home devices, researchers continue efforts to improve the "smartness" of those devices to address daily needs in people's lives. Such efforts usually begin with understanding evolving user behaviors on how humans utilize the devices and what they expect in terms of their behavior. However, while research efforts abound, there is a very limited number of datasets that researchers can use to both understand how people use IoT devices and to evaluate algorithms or systems for smart spaces. In this paper, we collect and characterize more than 50,000 recipes from the online If-This-Then-That (IFTTT) service to understand a seemingly straightforward but complicated question: "What kinds of behaviors do humans expect from their IoT devices?"</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2110.00068</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Algorithms ; Datasets ; Devices ; Internet of Things ; Smart buildings ; Systems analysis</subject><ispartof>arXiv.org, 2021-09</ispartof><rights>2021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2578928961?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25752,27924,37011,44589</link.rule.ids></links><search><creatorcontrib>Yu, Haoxiang</creatorcontrib><creatorcontrib>Hua, Jie</creatorcontrib><creatorcontrib>Julien, Christine</creatorcontrib><title>Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices</title><title>arXiv.org</title><description>With the rapid development and usage of Internet-of-Things (IoT) and smart-home devices, researchers continue efforts to improve the "smartness" of those devices to address daily needs in people's lives. Such efforts usually begin with understanding evolving user behaviors on how humans utilize the devices and what they expect in terms of their behavior. However, while research efforts abound, there is a very limited number of datasets that researchers can use to both understand how people use IoT devices and to evaluate algorithms or systems for smart spaces. In this paper, we collect and characterize more than 50,000 recipes from the online If-This-Then-That (IFTTT) service to understand a seemingly straightforward but complicated question: "What kinds of behaviors do humans expect from their IoT devices?"</description><subject>Algorithms</subject><subject>Datasets</subject><subject>Devices</subject><subject>Internet of Things</subject><subject>Smart buildings</subject><subject>Systems analysis</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNotz01Lw0AUheFBECy1P8DdgBtdpN7c-UjirrTWBgqCjisXZTqZaErN1NxJtf_egK4OPIsDL2NXKUxlrhTc2e6nOU4xHQAAdH7GRihEmuQS8YJNiHYDo85QKTFibwsbLfl4z2et3Z-oIR5qXi6NMfzZu-bgicfAX2JfnfgqfPNV_2lb4q_kedlG37U-JqFOzEfTvhO_KYO55Qt_bJynS3Ze2z35yf-OmVk-mPkqWT89lvPZOrEK00RAmkFWaVkhatzWCmuAXINTTmbonSxgKxVYXQsQzmrtJGhQauDCgXdizK7_bg9d-Oo9xc0u9N1QQxtUWV5gXuhU_AI41VFZ</recordid><startdate>20210930</startdate><enddate>20210930</enddate><creator>Yu, Haoxiang</creator><creator>Hua, Jie</creator><creator>Julien, Christine</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20210930</creationdate><title>Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices</title><author>Yu, Haoxiang ; Hua, Jie ; Julien, Christine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a521-301707d64d2262bf52f00860c5c472ec490b450a6f303ca66c40605590b9c0ec3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Datasets</topic><topic>Devices</topic><topic>Internet of Things</topic><topic>Smart buildings</topic><topic>Systems analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Yu, Haoxiang</creatorcontrib><creatorcontrib>Hua, Jie</creatorcontrib><creatorcontrib>Julien, Christine</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Haoxiang</au><au>Hua, Jie</au><au>Julien, Christine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices</atitle><jtitle>arXiv.org</jtitle><date>2021-09-30</date><risdate>2021</risdate><eissn>2331-8422</eissn><abstract>With the rapid development and usage of Internet-of-Things (IoT) and smart-home devices, researchers continue efforts to improve the "smartness" of those devices to address daily needs in people's lives. Such efforts usually begin with understanding evolving user behaviors on how humans utilize the devices and what they expect in terms of their behavior. However, while research efforts abound, there is a very limited number of datasets that researchers can use to both understand how people use IoT devices and to evaluate algorithms or systems for smart spaces. In this paper, we collect and characterize more than 50,000 recipes from the online If-This-Then-That (IFTTT) service to understand a seemingly straightforward but complicated question: "What kinds of behaviors do humans expect from their IoT devices?"</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.2110.00068</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2021-09
issn 2331-8422
language eng
recordid cdi_proquest_journals_2578928961
source Publicly Available Content (ProQuest)
subjects Algorithms
Datasets
Devices
Internet of Things
Smart buildings
Systems analysis
title Dataset: Analysis of IFTTT Recipes to Study How Humans Use Internet-of-Things (IoT) Devices
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T16%3A06%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Dataset:%20Analysis%20of%20IFTTT%20Recipes%20to%20Study%20How%20Humans%20Use%20Internet-of-Things%20(IoT)%20Devices&rft.jtitle=arXiv.org&rft.au=Yu,%20Haoxiang&rft.date=2021-09-30&rft.eissn=2331-8422&rft_id=info:doi/10.48550/arxiv.2110.00068&rft_dat=%3Cproquest%3E2578928961%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a521-301707d64d2262bf52f00860c5c472ec490b450a6f303ca66c40605590b9c0ec3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2578928961&rft_id=info:pmid/&rfr_iscdi=true