Towards autonomous cloud-based close call data management for construction equipment safety
Construction accounts for up to 25% of all occupational fatalities. About half are being struck by and caught-in/between objects or vehicles, resulting from insufficient or delayed detection of pedestrian workers. Research has proposed detecting visibility-related close calls in order to alarm the i...
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Veröffentlicht in: | Automation in construction 2021-12, Vol.132, p.103962, Article 103962 |
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creator | Golovina, Olga Teizer, Jochen Johansen, Karsten W. König, Markus |
description | Construction accounts for up to 25% of all occupational fatalities. About half are being struck by and caught-in/between objects or vehicles, resulting from insufficient or delayed detection of pedestrian workers. Research has proposed detecting visibility-related close calls in order to alarm the involved personnel and prevent negative consequences at the earliest possible time. This work has three objectives: First, a comprehensive synthesis on close call reporting processes and individual technologies. Second, a system focusing on (a) autonomous close call data generation from real-time proactive proximity detection and alerting technology and (b) cloud-based data processing and visualization in building information models at run time. Test results demonstrate that the developed system reaches purposes for decision making in safety management beyond the scope of existing detection and alarming devices. Third, guiding future research by outlining the role of proximity detection and alarming technology in developing autonomous safety systems for construction.
[Display omitted]
•Struck-by and caught-in/between accidents remain leading causes of fatal injuries.•Frequent worker-machine interactions demand research for autonomous safety systems.•Understanding and use of emerging technology for proactive assistance is limited.•A cloud-based close call data management based on automated reporting is proposed.•Model-based close call data visualization allows right-time personalized feedback. |
doi_str_mv | 10.1016/j.autcon.2021.103962 |
format | Article |
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[Display omitted]
•Struck-by and caught-in/between accidents remain leading causes of fatal injuries.•Frequent worker-machine interactions demand research for autonomous safety systems.•Understanding and use of emerging technology for proactive assistance is limited.•A cloud-based close call data management based on automated reporting is proposed.•Model-based close call data visualization allows right-time personalized feedback.</description><identifier>ISSN: 0926-5805</identifier><identifier>EISSN: 1872-7891</identifier><identifier>DOI: 10.1016/j.autcon.2021.103962</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Accident precursor analysis ; Building management systems ; Close call reporting ; Cloud computing ; Construction equipment ; Construction equipment safety ; Data management ; Data processing ; Decision making ; Object recognition ; Pedestrian worker-machine interaction ; Personalized feedback ; Proactive real-time alerts ; Proximity sensing ; Run time (computers) ; Run time data processing ; Safety management ; Tactile event response ; Visibility</subject><ispartof>Automation in construction, 2021-12, Vol.132, p.103962, Article 103962</ispartof><rights>2021 Elsevier B.V.</rights><rights>Copyright Elsevier BV Dec 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c380t-eeceedab996fb05fe7f60325858d366d301224701274f1e7db89c84238c95ef53</citedby><cites>FETCH-LOGICAL-c380t-eeceedab996fb05fe7f60325858d366d301224701274f1e7db89c84238c95ef53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.autcon.2021.103962$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Golovina, Olga</creatorcontrib><creatorcontrib>Teizer, Jochen</creatorcontrib><creatorcontrib>Johansen, Karsten W.</creatorcontrib><creatorcontrib>König, Markus</creatorcontrib><title>Towards autonomous cloud-based close call data management for construction equipment safety</title><title>Automation in construction</title><description>Construction accounts for up to 25% of all occupational fatalities. About half are being struck by and caught-in/between objects or vehicles, resulting from insufficient or delayed detection of pedestrian workers. Research has proposed detecting visibility-related close calls in order to alarm the involved personnel and prevent negative consequences at the earliest possible time. This work has three objectives: First, a comprehensive synthesis on close call reporting processes and individual technologies. Second, a system focusing on (a) autonomous close call data generation from real-time proactive proximity detection and alerting technology and (b) cloud-based data processing and visualization in building information models at run time. Test results demonstrate that the developed system reaches purposes for decision making in safety management beyond the scope of existing detection and alarming devices. Third, guiding future research by outlining the role of proximity detection and alarming technology in developing autonomous safety systems for construction.
[Display omitted]
•Struck-by and caught-in/between accidents remain leading causes of fatal injuries.•Frequent worker-machine interactions demand research for autonomous safety systems.•Understanding and use of emerging technology for proactive assistance is limited.•A cloud-based close call data management based on automated reporting is proposed.•Model-based close call data visualization allows right-time personalized feedback.</description><subject>Accident precursor analysis</subject><subject>Building management systems</subject><subject>Close call reporting</subject><subject>Cloud computing</subject><subject>Construction equipment</subject><subject>Construction equipment safety</subject><subject>Data management</subject><subject>Data processing</subject><subject>Decision making</subject><subject>Object recognition</subject><subject>Pedestrian worker-machine interaction</subject><subject>Personalized feedback</subject><subject>Proactive real-time alerts</subject><subject>Proximity sensing</subject><subject>Run time (computers)</subject><subject>Run time data processing</subject><subject>Safety management</subject><subject>Tactile event response</subject><subject>Visibility</subject><issn>0926-5805</issn><issn>1872-7891</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9UEtLxDAQDqLguvoPPAQ8d03SJk0ugiy-YMHLevIQ0mQiLd1mN0kV_71d69nLzDDzPZgPoWtKVpRQcdutzJhtGFaMMDqtSiXYCVpQWbOiloqeogVRTBRcEn6OLlLqCCE1EWqB3rfhy0SX8KQQhrALY8K2D6MrGpPAHecE2Jq-x85kg3dmMB-wgyFjHyKeTFOOo81tGDAcxnb_e0rGQ_6-RGfe9Amu_voSvT0-bNfPxeb16WV9vylsKUkuACyAM41SwjeEe6i9ICXjkktXCuFKQhmr6qnWladQu0YqKytWSqs4eF4u0c2su4_hMELKugtjHCZLzQThgquSiglVzSgbQ0oRvN7Hdmfit6ZEH2PUnZ5j1McY9RzjRLubaTB98NlC1Mm2MFhwbQSbtQvt_wI_neF-iA</recordid><startdate>202112</startdate><enddate>202112</enddate><creator>Golovina, Olga</creator><creator>Teizer, Jochen</creator><creator>Johansen, Karsten W.</creator><creator>König, Markus</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>202112</creationdate><title>Towards autonomous cloud-based close call data management for construction equipment safety</title><author>Golovina, Olga ; Teizer, Jochen ; Johansen, Karsten W. ; König, Markus</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c380t-eeceedab996fb05fe7f60325858d366d301224701274f1e7db89c84238c95ef53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accident precursor analysis</topic><topic>Building management systems</topic><topic>Close call reporting</topic><topic>Cloud computing</topic><topic>Construction equipment</topic><topic>Construction equipment safety</topic><topic>Data management</topic><topic>Data processing</topic><topic>Decision making</topic><topic>Object recognition</topic><topic>Pedestrian worker-machine interaction</topic><topic>Personalized feedback</topic><topic>Proactive real-time alerts</topic><topic>Proximity sensing</topic><topic>Run time (computers)</topic><topic>Run time data processing</topic><topic>Safety management</topic><topic>Tactile event response</topic><topic>Visibility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Golovina, Olga</creatorcontrib><creatorcontrib>Teizer, Jochen</creatorcontrib><creatorcontrib>Johansen, Karsten W.</creatorcontrib><creatorcontrib>König, Markus</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Automation in construction</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Golovina, Olga</au><au>Teizer, Jochen</au><au>Johansen, Karsten W.</au><au>König, Markus</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Towards autonomous cloud-based close call data management for construction equipment safety</atitle><jtitle>Automation in construction</jtitle><date>2021-12</date><risdate>2021</risdate><volume>132</volume><spage>103962</spage><pages>103962-</pages><artnum>103962</artnum><issn>0926-5805</issn><eissn>1872-7891</eissn><abstract>Construction accounts for up to 25% of all occupational fatalities. About half are being struck by and caught-in/between objects or vehicles, resulting from insufficient or delayed detection of pedestrian workers. Research has proposed detecting visibility-related close calls in order to alarm the involved personnel and prevent negative consequences at the earliest possible time. This work has three objectives: First, a comprehensive synthesis on close call reporting processes and individual technologies. Second, a system focusing on (a) autonomous close call data generation from real-time proactive proximity detection and alerting technology and (b) cloud-based data processing and visualization in building information models at run time. Test results demonstrate that the developed system reaches purposes for decision making in safety management beyond the scope of existing detection and alarming devices. Third, guiding future research by outlining the role of proximity detection and alarming technology in developing autonomous safety systems for construction.
[Display omitted]
•Struck-by and caught-in/between accidents remain leading causes of fatal injuries.•Frequent worker-machine interactions demand research for autonomous safety systems.•Understanding and use of emerging technology for proactive assistance is limited.•A cloud-based close call data management based on automated reporting is proposed.•Model-based close call data visualization allows right-time personalized feedback.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.autcon.2021.103962</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accident precursor analysis Building management systems Close call reporting Cloud computing Construction equipment Construction equipment safety Data management Data processing Decision making Object recognition Pedestrian worker-machine interaction Personalized feedback Proactive real-time alerts Proximity sensing Run time (computers) Run time data processing Safety management Tactile event response Visibility |
title | Towards autonomous cloud-based close call data management for construction equipment safety |
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