Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology
Hazards potentially affect the safety of people on construction sites include falls from heights (FFH), trench and scaffold collapse, electric shock and arc flash/arc blast, and failure to use proper personal protective equipment. Such hazards are significant contributors to accidents and fatalities...
Uloženo v:
| Vydáno v: | Automation in construction Ročník 119; s. 103310 |
|---|---|
| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Amsterdam
Elsevier B.V
01.11.2020
Elsevier BV |
| Témata: | |
| ISSN: | 0926-5805, 1872-7891 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Hazards potentially affect the safety of people on construction sites include falls from heights (FFH), trench and scaffold collapse, electric shock and arc flash/arc blast, and failure to use proper personal protective equipment. Such hazards are significant contributors to accidents and fatalities. Computer vision has been used to automatically detect safety hazards to assist with the mitigation of accidents and fatalities. However, as safety regulations are subject to change and become more stringent prevailing computer vision approaches will become obsolete as they are unable to accommodate the adjustments that are made to practice. This paper integrates computer vision algorithms with ontology models to develop a knowledge graph that can automatically and accurately recognise hazards while adhering to safety regulations, even when they are subjected to change. Our developed knowledge graph consists of: (1) an ontological model for hazards: (2) knowledge extraction; and (3) knowledge inference for hazard identification. We focus on the detection of hazards associated with FFH as an example to illustrate our proposed approach. We also demonstrate that our approach can successfully detect FFH hazards in varying contexts from images.
•A knowledge graph is developed to automatically identify hazards.•Computer vision algorithms and ontology are used to develop knowledge graph.•Examples are used to illustrate the feasibility of the proposed approach. |
|---|---|
| AbstractList | Hazards potentially affect the safety of people on construction sites include falls from heights (FFH), trench and scaffold collapse, electric shock and arc flash/arc blast, and failure to use proper personal protective equipment. Such hazards are significant contributors to accidents and fatalities. Computer vision has been used to automatically detect safety hazards to assist with the mitigation of accidents and fatalities. However, as safety regulations are subject to change and become more stringent prevailing computer vision approaches will become obsolete as they are unable to accommodate the adjustments that are made to practice. This paper integrates computer vision algorithms with ontology models to develop a knowledge graph that can automatically and accurately recognise hazards while adhering to safety regulations, even when they are subjected to change. Our developed knowledge graph consists of: (1) an ontological model for hazards: (2) knowledge extraction; and (3) knowledge inference for hazard identification. We focus on the detection of hazards associated with FFH as an example to illustrate our proposed approach. We also demonstrate that our approach can successfully detect FFH hazards in varying contexts from images. Hazards potentially affect the safety of people on construction sites include falls from heights (FFH), trench and scaffold collapse, electric shock and arc flash/arc blast, and failure to use proper personal protective equipment. Such hazards are significant contributors to accidents and fatalities. Computer vision has been used to automatically detect safety hazards to assist with the mitigation of accidents and fatalities. However, as safety regulations are subject to change and become more stringent prevailing computer vision approaches will become obsolete as they are unable to accommodate the adjustments that are made to practice. This paper integrates computer vision algorithms with ontology models to develop a knowledge graph that can automatically and accurately recognise hazards while adhering to safety regulations, even when they are subjected to change. Our developed knowledge graph consists of: (1) an ontological model for hazards: (2) knowledge extraction; and (3) knowledge inference for hazard identification. We focus on the detection of hazards associated with FFH as an example to illustrate our proposed approach. We also demonstrate that our approach can successfully detect FFH hazards in varying contexts from images. •A knowledge graph is developed to automatically identify hazards.•Computer vision algorithms and ontology are used to develop knowledge graph.•Examples are used to illustrate the feasibility of the proposed approach. |
| ArticleNumber | 103310 |
| Author | Luo, Hanbin Ding, Lieyun Fang, Weili Love, Peter E.D. Ma, Ling Zhou, Ao |
| Author_xml | – sequence: 1 givenname: Weili surname: Fang fullname: Fang, Weili email: weili.fang@curtin.edu.au organization: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, 430074, Hubei, China – sequence: 2 givenname: Ling surname: Ma fullname: Ma, Ling email: l.ma@ucl.ac.uk organization: The Bartlett School of Construction and Project Management, University College London, London WC1E 6BT, United Kingdom – sequence: 3 givenname: Peter E.D. surname: Love fullname: Love, Peter E.D. email: p.love@curtin.edu.au organization: Dept. of Civil and Mechanical Engineering, Curtin University, Perth, WA 6845, Australia – sequence: 4 givenname: Hanbin surname: Luo fullname: Luo, Hanbin email: luohbcem@hust.edu.cn organization: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, 430074, Hubei, China – sequence: 5 givenname: Lieyun surname: Ding fullname: Ding, Lieyun email: dly@hust.edu.cn organization: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, 430074, Hubei, China – sequence: 6 givenname: Ao surname: Zhou fullname: Zhou, Ao organization: School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, 430074, Hubei, China |
| BookMark | eNqFkE1LAzEQhoMoWD_-gYcFz1vzsU02HgQpfqHgRc8hzs62KTWpSbZSf727rCcPehpmeJ8Z5jki-z54JOSM0SmjTF6sprbLEPyUUz6MhGB0j0xYrXipas32yYRqLstZTWeH5CilFaVUUaknZPnow-camwUWi2g3y6INsXAN-uzanfOLYmm_bGxSEXzRX0g5dpBd3ySXMV0WDz5jD-YhCuF902WMxdalIfLp8rLncliHxe6EHLR2nfD0px6T19ubl_l9-fR89zC_fipBiCqXzL7V7UyCoFLZSgNvUDcUEEG34g205kIJy2hbSaiqCiwoRmtpLedCwkyLY3I-7t3E8NFhymYVuuj7k4ZXkqpaKTmkqjEFMaQUsTWb6N5t3BlGzeDUrMzo1AxOzei0xy5_YeCyHXzkaN36P_hqhLF_f-swmgQOPWDjIkI2TXB_L_gG37GZKA |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2023_3253807 crossref_primary_10_1016_j_autcon_2025_106117 crossref_primary_10_1016_j_jsasus_2025_05_004 crossref_primary_10_1016_j_autcon_2022_104696 crossref_primary_10_1016_j_jlp_2024_105525 crossref_primary_10_1016_j_oceaneng_2025_120536 crossref_primary_10_3390_app14010057 crossref_primary_10_1016_j_aei_2025_103454 crossref_primary_10_1111_mice_12632 crossref_primary_10_1016_j_autcon_2025_106476 crossref_primary_10_1007_s12583_022_1641_1 crossref_primary_10_1016_j_jobe_2021_103036 crossref_primary_10_1016_j_rcim_2022_102489 crossref_primary_10_1016_j_autcon_2024_105938 crossref_primary_10_1016_j_autcon_2024_105539 crossref_primary_10_1007_s11831_021_09576_9 crossref_primary_10_1016_j_aei_2023_102194 crossref_primary_10_1016_j_jobe_2024_108609 crossref_primary_10_3390_app11178130 crossref_primary_10_3390_info15070390 crossref_primary_10_1108_ECAM_12_2024_1751 crossref_primary_10_1155_2022_4183059 crossref_primary_10_3390_buildings13082093 crossref_primary_10_1016_j_autcon_2022_104580 crossref_primary_10_1016_j_ssci_2022_106043 crossref_primary_10_3390_su15064812 crossref_primary_10_1109_ACCESS_2024_3375879 crossref_primary_10_1016_j_autcon_2023_104961 crossref_primary_10_3390_buildings13112812 crossref_primary_10_3390_buildings11090409 crossref_primary_10_1016_j_aei_2025_103869 crossref_primary_10_1016_j_ssci_2025_106813 crossref_primary_10_1016_j_autcon_2025_106181 crossref_primary_10_1007_s12583_022_1724_z crossref_primary_10_1061__ASCE_CP_1943_5487_0001064 crossref_primary_10_1108_ECAM_03_2023_0255 crossref_primary_10_1155_2023_6047489 crossref_primary_10_1016_j_measurement_2024_114960 crossref_primary_10_1088_1755_1315_861_5_052098 crossref_primary_10_1016_j_asoc_2025_113374 crossref_primary_10_3390_smartcities7040086 crossref_primary_10_1016_j_dibe_2025_100645 crossref_primary_10_1016_j_compind_2021_103448 crossref_primary_10_1016_j_aei_2023_102215 crossref_primary_10_1016_j_aej_2025_07_037 crossref_primary_10_1038_s44359_025_00047_z crossref_primary_10_1016_j_aei_2022_101688 crossref_primary_10_1016_j_autcon_2024_105686 crossref_primary_10_1111_tgis_12911 crossref_primary_10_1016_j_autcon_2021_103617 crossref_primary_10_1371_journal_pone_0294130 crossref_primary_10_1109_TITS_2023_3240104 crossref_primary_10_1007_s13349_025_00977_z crossref_primary_10_1016_j_autcon_2024_105451 crossref_primary_10_1016_j_autcon_2025_106206 crossref_primary_10_3390_su142013618 crossref_primary_10_3390_app13084666 crossref_primary_10_1016_j_autcon_2022_104443 crossref_primary_10_1145_3655599 crossref_primary_10_1016_j_aei_2024_102507 crossref_primary_10_1016_j_psep_2023_01_060 crossref_primary_10_1016_j_aei_2022_101699 crossref_primary_10_1016_j_autcon_2023_105158 crossref_primary_10_1061_JCEMD4_COENG_15493 crossref_primary_10_1016_j_pacfin_2025_102924 crossref_primary_10_1061_JCEMD4_COENG_14436 crossref_primary_10_1061_JCEMD4_COENG_14839 crossref_primary_10_3390_buildings13102419 crossref_primary_10_1016_j_autcon_2022_104252 crossref_primary_10_1016_j_jobe_2023_107049 crossref_primary_10_1109_TEM_2021_3093166 crossref_primary_10_3389_fbuil_2020_575738 crossref_primary_10_1016_j_autcon_2023_105227 crossref_primary_10_1016_j_autcon_2022_104530 crossref_primary_10_3390_rs17152679 crossref_primary_10_1109_EMR_2023_3342200 crossref_primary_10_1016_j_aei_2025_103655 crossref_primary_10_1016_j_autcon_2022_104535 crossref_primary_10_1080_10447318_2024_2387421 crossref_primary_10_3390_math11061499 crossref_primary_10_1016_j_autcon_2023_105224 crossref_primary_10_3390_su14106126 crossref_primary_10_1016_j_autcon_2024_105739 crossref_primary_10_3390_buildings14113403 crossref_primary_10_1016_j_autcon_2025_106302 crossref_primary_10_1016_j_engappai_2022_105742 crossref_primary_10_1016_j_autcon_2025_106305 crossref_primary_10_1145_3522586 crossref_primary_10_3390_buildings12060857 crossref_primary_10_1016_j_autcon_2022_104302 crossref_primary_10_1016_j_autcon_2025_106301 crossref_primary_10_1016_j_compind_2022_103610 crossref_primary_10_1016_j_aei_2024_102446 crossref_primary_10_3390_app15042218 crossref_primary_10_1016_j_compgeo_2024_106431 crossref_primary_10_1108_ECAM_05_2024_0622 crossref_primary_10_1177_15705838241312424 crossref_primary_10_1051_e3sconf_202340904002 crossref_primary_10_1038_s41598_023_34342_1 crossref_primary_10_1016_j_autcon_2022_104191 crossref_primary_10_1016_j_knosys_2022_110115 crossref_primary_10_1016_j_aei_2024_103075 crossref_primary_10_1016_j_autcon_2025_106419 crossref_primary_10_1108_ECAM_02_2025_0298 crossref_primary_10_3390_buildings13020377 crossref_primary_10_3390_su132413579 crossref_primary_10_1016_j_autcon_2024_105800 crossref_primary_10_3390_buildings14092879 crossref_primary_10_1109_ACCESS_2024_3423697 crossref_primary_10_1007_s40747_020_00208_6 crossref_primary_10_1061_JCEMD4_COENG_15310 crossref_primary_10_3390_app122110822 crossref_primary_10_1016_j_aei_2024_102650 crossref_primary_10_1016_j_jii_2023_100519 crossref_primary_10_1016_j_aei_2020_101164 crossref_primary_10_3390_buildings13071853 crossref_primary_10_1016_j_procs_2023_10_626 crossref_primary_10_1016_j_autcon_2025_106127 crossref_primary_10_1111_mice_13078 crossref_primary_10_1016_j_autcon_2021_103892 crossref_primary_10_1016_j_jenvman_2022_115685 crossref_primary_10_1016_j_aei_2025_103246 crossref_primary_10_3390_app12178574 crossref_primary_10_4018_IJKSS_325794 crossref_primary_10_1061_JMENEA_MEENG_5445 crossref_primary_10_1080_10803548_2025_2463224 crossref_primary_10_1080_09613218_2023_2238851 crossref_primary_10_1061__ASCE_CO_1943_7862_0002297 crossref_primary_10_1108_ECAM_08_2024_1066 crossref_primary_10_1016_j_engstruct_2023_116132 crossref_primary_10_3390_ijerph18137040 crossref_primary_10_1051_matecconf_202541103002 |
| Cites_doi | 10.1016/j.apergo.2018.01.007 10.1016/j.autcon.2013.10.020 10.1061/(ASCE)CP.1943-5487.0000094 10.1016/j.ssci.2016.04.008 10.1080/00140139.2019.1644379 10.1016/j.autcon.2012.06.001 10.1016/j.autcon.2018.02.018 10.1016/j.autcon.2017.02.009 10.1006/knac.1993.1008 10.1016/j.aei.2018.12.005 10.1016/j.autcon.2017.06.014 10.1007/978-3-030-01228-1_26 10.1016/j.aei.2018.05.003 10.1061/(ASCE)CP.1943-5487.0000125 10.1111/j.1467-8667.2010.00690.x 10.1016/j.aei.2015.03.009 10.1016/j.autcon.2012.03.003 10.1061/(ASCE)CO.1943-7862.0001767 10.1061/(ASCE)CP.1943-5487.0000027 10.1061/(ASCE)CP.1943-5487.0000594 10.1016/j.aei.2019.100980 10.1016/j.aei.2014.05.001 10.1016/S0926-5805(01)00061-9 10.1016/j.ssci.2017.08.015 10.1061/41020(339)47 10.3390/ijerph13070638 10.1023/B:VISI.0000029664.99615.94 10.1016/j.autcon.2019.103013 10.1108/14714170810888976 10.1016/j.patcog.2017.05.025 10.3390/s17081841 10.1061/(ASCE)CP.1943-5487.0000562 10.1061/(ASCE)CP.1943-5487.0000179 10.1016/j.autcon.2017.10.004 10.1109/TPAMI.2012.59 10.1016/j.autcon.2017.12.034 10.1016/j.autcon.2018.12.014 10.1038/nature14539 10.1016/j.autcon.2015.05.002 10.1016/j.autcon.2015.02.007 10.1080/01446193.2013.816435 10.1016/j.autcon.2017.05.002 10.1016/j.autcon.2017.11.002 10.1061/(ASCE)CO.1943-7862.0000116 |
| ContentType | Journal Article |
| Copyright | 2020 Elsevier B.V. Copyright Elsevier BV Nov 2020 |
| Copyright_xml | – notice: 2020 Elsevier B.V. – notice: Copyright Elsevier BV Nov 2020 |
| DBID | AAYXX CITATION 7SC 7SP 8FD FR3 JQ2 KR7 L7M L~C L~D |
| DOI | 10.1016/j.autcon.2020.103310 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Civil Engineering Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Civil Engineering Abstracts |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Economics Engineering |
| EISSN | 1872-7891 |
| ExternalDocumentID | 10_1016_j_autcon_2020_103310 S0926580519309082 |
| GroupedDBID | --K --M .~1 0R~ 1B1 1~. 1~5 23N 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AACTN AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AATTM AAXKI AAXUO ABFNM ABJNI ABMAC ABWVN ABXDB ACDAQ ACGFS ACIWK ACNNM ACRLP ACRPL ADBBV ADEZE ADMUD ADNMO ADTZH AEBSH AECPX AEIPS AEKER AENEX AFJKZ AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AIEXJ AIKHN AITUG AKRWK ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU APLSM ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC BNPGV CS3 EBS EFJIC EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HVGLF HZ~ IHE J1W JJJVA KOM LY7 M41 MO0 N9A NEJ O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 R2- RIG RNS ROL RPZ SDF SDG SDP SES SET SEW SPC SPCBC SSB SSD SSH SST SSZ T5K WUQ ZMT ~G- 9DU AAYWO AAYXX ACLOT ACVFH ADCNI AEUPX AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP APXCP CITATION EFKBS EFLBG ~HD 7SC 7SP 8FD FR3 JQ2 KR7 L7M L~C L~D |
| ID | FETCH-LOGICAL-c334t-1ab8f56c3067a49c2de9d0ceec9f3bc992373a10f46c444cac71086aa2236c593 |
| ISICitedReferencesCount | 150 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000579045500002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0926-5805 |
| IngestDate | Sun Nov 09 06:02:26 EST 2025 Sat Nov 29 07:17:19 EST 2025 Tue Nov 18 22:39:58 EST 2025 Sun Apr 06 06:54:43 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Computer vision Hazards Safety Ontology Knowledge graph database |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c334t-1ab8f56c3067a49c2de9d0ceec9f3bc992373a10f46c444cac71086aa2236c593 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| PQID | 2460787769 |
| PQPubID | 2045277 |
| ParticipantIDs | proquest_journals_2460787769 crossref_primary_10_1016_j_autcon_2020_103310 crossref_citationtrail_10_1016_j_autcon_2020_103310 elsevier_sciencedirect_doi_10_1016_j_autcon_2020_103310 |
| PublicationCentury | 2000 |
| PublicationDate | November 2020 2020-11-00 20201101 |
| PublicationDateYYYYMMDD | 2020-11-01 |
| PublicationDate_xml | – month: 11 year: 2020 text: November 2020 |
| PublicationDecade | 2020 |
| PublicationPlace | Amsterdam |
| PublicationPlace_xml | – name: Amsterdam |
| PublicationTitle | Automation in construction |
| PublicationYear | 2020 |
| Publisher | Elsevier B.V Elsevier BV |
| Publisher_xml | – name: Elsevier B.V – name: Elsevier BV |
| References | Lee, Kim, Yu (bb0200) 2014; 41 Zhou, Goh, Shen (bb0315) 2016; 30 Ji, Xu, Yang, Yu (bb0165) 2013; 35 Wang, Boukamp, Elghamrawy (bb0290) 2011; 25 Ding, Fang, Luo, Love, Zhong, Ouyang (bb0050) 2018; 86 Johnpaul, Mathew (bb0170) 2017 Zhong, Li, Luo, Zhou, Fang, Xing (bb0140) 2020; 146 Gong, Caldas (bb0130) 2009; 24 Lingard (bb0220) 2013; 31 Xiao, Liu, Zhou, Jiang, Sun (bb0300) 2018 Zhang, Cao, Zhao (bb0310) 2017; 17 Jia, Issa (bb0160) 2015; 29 Fang, Ding, Luo, Love (bb0100) 2018; 91 Guo, Goh (bb0070) 2017; 82 Azar, McCabe (bb0010) 2012; 24 Anumba, Issa, Pan, Mutis (bb0005) 2008; 8 T. Elghamrawy, F. Boukamp, H.S. Kim, Ontology-based, semi-automatic framework for storing and retrieving on-site construction problem information — An RFID-based case study, in: Construction Research Congress, Seattle, Washington, United States, 2009, April5–7, pp. 457–466. doi He, Gkioxari, Dollar, Girshick, R (bb0150) 2017 Deng, Dong, Socher, Li, Li (bb0045) 2009 Wang, Schmid (bb0285) 2013 Love, Smith, Teo (bb0205) 2018; 69 Fang, Love, Luo, Ding (bb0120) 2020; 43 Hadikusumo, Rowlinson (bb0135) 2002; 11 html2014 (January 17, 2015). Kim, Kim, Kim (bb0185) 2016; 30 Nanni, Ghidoni, Brahnam (bb0260) 2017; 71 . Martinez-Aires, Lopez-Alonso, Martinez-Rojas (bb0250) 2018; 101 Wang, Boukamp (bb0295) 2011; 25 Ding, Zhong, Wu, Luo (bb0055) 2016; 87 Goh, Chua (bb0060) 2010; 136 Kim, Kim (bb0175) 2018; 88 Kim, Kim, Kim (bb0180) 2017; 83 Guia, Soares, Bernardina (bb0065) 2017 Fang, Ding, Love, Luo, Li, Peña-Mora, Zhong, Zhou (bb0115) 2020; 110 Han, Golparvar-Fard (bb0145) 2015; 53 Dalal, Triggs (bb0040) 2005 Kim, Liu, Lee, Kamat (bb0190) 2019; 99 Azar, McCabe (bb0015) 2012; 26 Chi, Lin, Hsieh (bb0025) 2014; 28 El-Diraby (bb0085) 2014; 19 Fang, Zhong, Zhao, Love, Luo, Xue, Xu (bb0110) 2019; 39 Chi, Caldas (bb0030) 2011; 26 Nadhim, Hon, Xia, Stewart (bb0230) 2016; 13 K. Simonyan, A. Zisserman, Two-stream convolutional networks for action recognition in videos. Part of Advances in Neural Information Processing Systems (NIPS 2014). Hippolyte, Rezgui, Li, Jayan, Howell (bb0155) 2018; 86 Gruber (bb0075) 1993; 5 Edwards (bb0080) 2017 Fang, Ding, Zhong, Love, Luo (bb0105) 2018; 37 LeCun, Bengio, Hinton (bb0195) 2015; 521 Yu, Guo, Ding, Li, Skitmore (bb0305) 2017; 82 Love, Teo, Smith, Ackermann, Zhou (bb0210) 2019; 62 Corry, Pauwels, Hu, Keane, O’Donnell (bb0035) 2015; 57 Park, Brilakis (bb0275) 2012; 28 Lowe (bb0225) 2004; 60 OSHA, Commonly used statistics Nanni (10.1016/j.autcon.2020.103310_bb0260) 2017; 71 Zhang (10.1016/j.autcon.2020.103310_bb0310) 2017; 17 Lingard (10.1016/j.autcon.2020.103310_bb0220) 2013; 31 Ji (10.1016/j.autcon.2020.103310_bb0165) 2013; 35 Kim (10.1016/j.autcon.2020.103310_bb0180) 2017; 83 Nadhim (10.1016/j.autcon.2020.103310_bb0230) 2016; 13 Guia (10.1016/j.autcon.2020.103310_bb0065) 2017 Xiao (10.1016/j.autcon.2020.103310_bb0300) 2018 Fang (10.1016/j.autcon.2020.103310_bb0105) 2018; 37 Love (10.1016/j.autcon.2020.103310_bb0210) 2019; 62 10.1016/j.autcon.2020.103310_bb0280 Fang (10.1016/j.autcon.2020.103310_bb0100) 2018; 91 He (10.1016/j.autcon.2020.103310_bb0150) 2017 Han (10.1016/j.autcon.2020.103310_bb0145) 2015; 53 Edwards (10.1016/j.autcon.2020.103310_bb0080) Ding (10.1016/j.autcon.2020.103310_bb0050) 2018; 86 Azar (10.1016/j.autcon.2020.103310_bb0015) 2012; 26 Jia (10.1016/j.autcon.2020.103310_bb0160) 2015; 29 Corry (10.1016/j.autcon.2020.103310_bb0035) 2015; 57 Wang (10.1016/j.autcon.2020.103310_bb0290) 2011; 25 Fang (10.1016/j.autcon.2020.103310_bb0120) 2020; 43 10.1016/j.autcon.2020.103310_bb0090 Goh (10.1016/j.autcon.2020.103310_bb0060) 2010; 136 Fang (10.1016/j.autcon.2020.103310_bb0110) 2019; 39 Wang (10.1016/j.autcon.2020.103310_bb0285) 2013 Azar (10.1016/j.autcon.2020.103310_bb0010) 2012; 24 Lee (10.1016/j.autcon.2020.103310_bb0200) 2014; 41 Gruber (10.1016/j.autcon.2020.103310_bb0075) 1993; 5 Kim (10.1016/j.autcon.2020.103310_bb0190) 2019; 99 Gong (10.1016/j.autcon.2020.103310_bb0130) 2009; 24 Kim (10.1016/j.autcon.2020.103310_bb0185) 2016; 30 LeCun (10.1016/j.autcon.2020.103310_bb0195) 2015; 521 Zhou (10.1016/j.autcon.2020.103310_bb0315) 2016; 30 Park (10.1016/j.autcon.2020.103310_bb0275) 2012; 28 Ding (10.1016/j.autcon.2020.103310_bb0055) 2016; 87 Dalal (10.1016/j.autcon.2020.103310_bb0040) 2005 Hadikusumo (10.1016/j.autcon.2020.103310_bb0135) 2002; 11 10.1016/j.autcon.2020.103310_bb0265 El-Diraby (10.1016/j.autcon.2020.103310_bb0085) 2014; 19 Johnpaul (10.1016/j.autcon.2020.103310_bb0170) 2017 Zhong (10.1016/j.autcon.2020.103310_bb0140) 2020; 146 Kim (10.1016/j.autcon.2020.103310_bb0175) 2018; 88 Chi (10.1016/j.autcon.2020.103310_bb0025) 2014; 28 Hippolyte (10.1016/j.autcon.2020.103310_bb0155) 2018; 86 Deng (10.1016/j.autcon.2020.103310_bb0045) 2009 Wang (10.1016/j.autcon.2020.103310_bb0295) 2011; 25 Anumba (10.1016/j.autcon.2020.103310_bb0005) 2008; 8 Lowe (10.1016/j.autcon.2020.103310_bb0225) 2004; 60 Martinez-Aires (10.1016/j.autcon.2020.103310_bb0250) 2018; 101 Chi (10.1016/j.autcon.2020.103310_bb0030) 2011; 26 Guo (10.1016/j.autcon.2020.103310_bb0070) 2017; 82 Yu (10.1016/j.autcon.2020.103310_bb0305) 2017; 82 Love (10.1016/j.autcon.2020.103310_bb0205) 2018; 69 Fang (10.1016/j.autcon.2020.103310_bb0115) 2020; 110 |
| References_xml | – volume: 86 start-page: 210 year: 2018 end-page: 225 ident: bb0155 article-title: Ontology-driven development of web services to support district energy applications publication-title: Autom. Constr. – volume: 28 start-page: 381 year: 2014 end-page: 394 ident: bb0025 article-title: Using ontology-based text classification to assist job Hazard analysis publication-title: Adv. Eng. Inform. – volume: 136 start-page: 170 year: 2010 end-page: 178 ident: bb0060 article-title: Case-based reasoning approach to construction safety Hazard identification: adaptation and utilization publication-title: ASCE Journal of Construction Engineering and Management – volume: 26 start-page: 368 year: 2011 end-page: 380 ident: bb0030 article-title: Automated object identification using optical video cameras on construction sites publication-title: Computer-Aided Civil and Infrastructure Engineering – volume: 86 start-page: 118 year: 2018 end-page: 124 ident: bb0050 article-title: X, a deep hybrid learning model to detect unsafe behavior: integrating convolution neural networks and long short-term memory publication-title: Autom. Constr. – volume: 41 start-page: 94 year: 2014 end-page: 105 ident: bb0200 article-title: BIM and ontology-based approach for building cost estimation publication-title: Autom. Constr. – volume: 62 start-page: 1273 year: 2019 end-page: 1288 ident: bb0210 article-title: The nature and severity of workplace injuries in construction: engendering operational benchmarking publication-title: Ergonomics – volume: 25 start-page: 442 year: 2011 end-page: 456 ident: bb0295 article-title: Ontology-based representation and reasoning framework for supporting job Hazard analysis publication-title: J. Comput. Civ. Eng. – volume: 88 start-page: 23 year: 2018 end-page: 30 ident: bb0175 article-title: 3D reconstruction of a concrete mixer truck for training object detectors publication-title: Autom. Constr. – volume: 35 start-page: 221 year: 2013 end-page: 231 ident: bb0165 article-title: 3D convolutional neural networks for human action recognition publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – start-page: 3551 year: 2013 end-page: 3558 ident: bb0285 article-title: C, action recognition with improved trajectories publication-title: IEEE International Conference on Computer Vision – volume: 521 start-page: 436 year: 2015 end-page: 444 ident: bb0195 article-title: Deep learning publication-title: Nature – volume: 30 year: 2016 ident: bb0185 article-title: Vision-based object-centric safety assessment using fuzzy inference: monitoring struck-by accidents with moving objects publication-title: J. Comput. Civ. Eng. – volume: 60 start-page: 91 year: 2004 end-page: 110 ident: bb0225 article-title: Distinctive image features from scale-invariant keypoints publication-title: Int. J. Comput. Vis. – volume: 11 start-page: 501 year: 2002 end-page: 509 ident: bb0135 article-title: Integration of virtually real construction model and design-for-safety-process database publication-title: Autom. Constr. – volume: 146 year: 2020 ident: bb0140 article-title: Ontology-Based Semantic Modeling of Knowledge in Construction: Classification and Identification of Hazards Implied in Images publication-title: J. Constr. Eng. Manage. – volume: 87 start-page: 202 year: 2016 end-page: 213 ident: bb0055 article-title: Construction risk knowledge management in BIM using ontology and semantic web technology publication-title: Saf. Sci. – start-page: 22 year: 2017 end-page: 29 ident: bb0150 article-title: Mask R-CNN publication-title: IEEE International Conference on Computer Vision – year: 2017 ident: bb0170 article-title: A cypher query based NoSQL data mining on protein databases using Neo4j graph database publication-title: 4th International Conference on Advanced Computing and Communication Systems. Coimbatore, India – volume: 101 start-page: 11 year: 2018 end-page: 18 ident: bb0250 article-title: Building information modeling and safety management: a systematic review publication-title: Saf. Sci. – volume: 25 start-page: 331 year: 2011 end-page: 346 ident: bb0290 article-title: Ontology-based approach to context representation and reasoning for managing context-sensitive construction information publication-title: J. Comput. Civ. Eng. – volume: 28 start-page: 15 year: 2012 end-page: 25 ident: bb0275 article-title: Construction worker detection in video frames for initializing vision trackers publication-title: Autom. Constr. – volume: 82 start-page: 138 year: 2017 end-page: 153 ident: bb0070 article-title: Ontology for the design of active fall protection systems publication-title: Autom. Constr. – volume: 31 start-page: 505 year: 2013 end-page: 514 ident: bb0220 article-title: Occupational health and safety in the construction industry publication-title: Constr. Manag. Econ. – volume: 53 start-page: 44 year: 2015 end-page: 57 ident: bb0145 article-title: Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs publication-title: Autom. Constr. – volume: 5 start-page: 199 year: 1993 end-page: 220 ident: bb0075 article-title: A translation approach to portable ontologies publication-title: Knowl. Acquis. – volume: 39 start-page: 170 year: 2019 end-page: 177 ident: bb0110 article-title: A deep learning-based approach for mitigating falls from a height with computer vision: convolutional neural network publication-title: Adv. Eng. Inform. – start-page: 432 year: 2018 end-page: 448 ident: bb0300 article-title: Unified perceptual parsing for scene understanding publication-title: Lect. Notes Comput. Sci – volume: 99 start-page: 168 year: 2019 end-page: 182 ident: bb0190 article-title: Remote proximity monitoring between mobile construction resources using camera-mounted UAVs publication-title: Autom. Constr. – reference: OSHA, Commonly used statistics, – volume: 71 start-page: 158 year: 2017 end-page: 172 ident: bb0260 article-title: Handcrafted vs. non-handcrafted features for computer vision classification publication-title: Pattern Recogn. – start-page: 886 year: 2005 end-page: 893 ident: bb0040 article-title: Histograms of oriented gradients for human detection publication-title: IEEE Computer Society Conference on Computer Vision and Pattern Recognition – volume: 19 start-page: 474 year: 2014 end-page: 493 ident: bb0085 article-title: Validating ontologies in informatics systems: approaches and lessons learned for AEC publication-title: Journal of Information Technology in Construction – reference: T. Elghamrawy, F. Boukamp, H.S. Kim, Ontology-based, semi-automatic framework for storing and retrieving on-site construction problem information — An RFID-based case study, in: Construction Research Congress, Seattle, Washington, United States, 2009, April5–7, pp. 457–466. doi: – volume: 69 start-page: 104 year: 2018 end-page: 114 ident: bb0205 article-title: Putting into practice error management theory: unlearning and learning to manage action errors in construction publication-title: Appl. Ergon. – volume: 57 start-page: 249 year: 2015 end-page: 259 ident: bb0035 article-title: A performance assessment ontology for the environmental and energy management of buildings publication-title: Autom. Constr. – volume: 91 start-page: 53 year: 2018 end-page: 61 ident: bb0100 article-title: Falls from heights: a computer vision-based approach for safety harness detection publication-title: Autom. Constr. – volume: 29 start-page: 472 year: 2015 end-page: 482 ident: bb0160 article-title: Developing taxonomy for the domain ontology of construction contractual semantics: a case study on the AIA A201 document publication-title: Adv. Eng. Inform. – start-page: 248 year: 2009 end-page: 255 ident: bb0045 article-title: ImageNet: A large-scale hierarchical image database publication-title: 2009 IEEE Conference on Computer Vision and Pattern Recognition – reference: . html2014 (January 17, 2015). – start-page: 351 year: 2017 end-page: 356 ident: bb0065 article-title: Graph database: Neo4j analysis publication-title: Proc. of the 19 – reference: K. Simonyan, A. Zisserman, Two-stream convolutional networks for action recognition in videos. Part of Advances in Neural Information Processing Systems (NIPS 2014). – volume: 17 start-page: 1481 year: 2017 ident: bb0310 article-title: Applying sensor-based technology to improve construction safety management publication-title: Sensors – volume: 13 start-page: 638 year: 2016 ident: bb0230 article-title: Falls from height in the construction industry: a critical review of the scientific literature publication-title: Int. J. Environ. Res. Public Health – volume: 24 start-page: 252 year: 2009 end-page: 263 ident: bb0130 article-title: Computer vision-based video interpretation model for automated productivity analysis of construction operations publication-title: ASCE Journal of Computing in Civil Engineering – volume: 82 start-page: 193 year: 2017 end-page: 206 ident: bb0305 article-title: An experimental study of real-time identification of construction workers’ unsafe behaviors publication-title: Autom. Constr. – volume: 30 year: 2016 ident: bb0315 article-title: Overview and analysis of ontology studies supporting development of the construction industry publication-title: J. Comput. Civ. Eng. – volume: 8 start-page: 218 year: 2008 end-page: 239 ident: bb0005 article-title: Ontology-based information and knowledge management in construction publication-title: Constr. Innov. – volume: 83 start-page: 390 year: 2017 end-page: 403 ident: bb0180 article-title: Image-based construction hazard avoidance system using augmented reality in a wearable device publication-title: Autom. Constr. – reference: . – volume: 37 start-page: 139 year: 2018 end-page: 149 ident: bb0105 article-title: Automated detection of workers and heavy equipment on construction sites: a convolutional neural network approach publication-title: Adv. Eng. Inform. – volume: 24 start-page: 194 year: 2012 end-page: 202 ident: bb0010 article-title: Part based model and spatial-temporal reasoning to recognize hydraulic excavators in construction images and videos publication-title: Autom. Constr. – volume: 43 year: 2020 ident: bb0120 article-title: Computer vision for behavior-based safety in construction: a review and future directions publication-title: Adv. Eng. Inform. – volume: 110 year: 2020 ident: bb0115 article-title: Computer vision applications in construction safety assurance publication-title: Autom. Constr. – year: 2017 ident: bb0080 article-title: Fatal injuries arising from accidents at work in Great Britain 2017 to 2018 – volume: 26 start-page: 769 year: 2012 end-page: 781 ident: bb0015 article-title: Automated visual recognition of dump trucks in construction videos publication-title: ASCE Journal of Computing in Civil Engineering – volume: 69 start-page: 104 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0205 article-title: Putting into practice error management theory: unlearning and learning to manage action errors in construction publication-title: Appl. Ergon. doi: 10.1016/j.apergo.2018.01.007 – volume: 41 start-page: 94 year: 2014 ident: 10.1016/j.autcon.2020.103310_bb0200 article-title: BIM and ontology-based approach for building cost estimation publication-title: Autom. Constr. doi: 10.1016/j.autcon.2013.10.020 – volume: 25 start-page: 331 year: 2011 ident: 10.1016/j.autcon.2020.103310_bb0290 article-title: Ontology-based approach to context representation and reasoning for managing context-sensitive construction information publication-title: J. Comput. Civ. Eng. doi: 10.1061/(ASCE)CP.1943-5487.0000094 – volume: 87 start-page: 202 year: 2016 ident: 10.1016/j.autcon.2020.103310_bb0055 article-title: Construction risk knowledge management in BIM using ontology and semantic web technology publication-title: Saf. Sci. doi: 10.1016/j.ssci.2016.04.008 – volume: 62 start-page: 1273 issue: 10 year: 2019 ident: 10.1016/j.autcon.2020.103310_bb0210 article-title: The nature and severity of workplace injuries in construction: engendering operational benchmarking publication-title: Ergonomics doi: 10.1080/00140139.2019.1644379 – start-page: 886 year: 2005 ident: 10.1016/j.autcon.2020.103310_bb0040 article-title: Histograms of oriented gradients for human detection – volume: 28 start-page: 15 year: 2012 ident: 10.1016/j.autcon.2020.103310_bb0275 article-title: Construction worker detection in video frames for initializing vision trackers publication-title: Autom. Constr. doi: 10.1016/j.autcon.2012.06.001 – volume: 91 start-page: 53 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0100 article-title: Falls from heights: a computer vision-based approach for safety harness detection publication-title: Autom. Constr. doi: 10.1016/j.autcon.2018.02.018 – volume: 82 start-page: 138 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0070 article-title: Ontology for the design of active fall protection systems publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.02.009 – volume: 5 start-page: 199 issue: 2 year: 1993 ident: 10.1016/j.autcon.2020.103310_bb0075 article-title: A translation approach to portable ontologies publication-title: Knowl. Acquis. doi: 10.1006/knac.1993.1008 – start-page: 351 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0065 article-title: Graph database: Neo4j analysis – volume: 39 start-page: 170 year: 2019 ident: 10.1016/j.autcon.2020.103310_bb0110 article-title: A deep learning-based approach for mitigating falls from a height with computer vision: convolutional neural network publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2018.12.005 – volume: 83 start-page: 390 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0180 article-title: Image-based construction hazard avoidance system using augmented reality in a wearable device publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.06.014 – start-page: 432 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0300 article-title: Unified perceptual parsing for scene understanding publication-title: Lect. Notes Comput. Sci doi: 10.1007/978-3-030-01228-1_26 – start-page: 248 year: 2009 ident: 10.1016/j.autcon.2020.103310_bb0045 article-title: ImageNet: A large-scale hierarchical image database – volume: 37 start-page: 139 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0105 article-title: Automated detection of workers and heavy equipment on construction sites: a convolutional neural network approach publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2018.05.003 – start-page: 3551 year: 2013 ident: 10.1016/j.autcon.2020.103310_bb0285 article-title: C, action recognition with improved trajectories – volume: 25 start-page: 442 year: 2011 ident: 10.1016/j.autcon.2020.103310_bb0295 article-title: Ontology-based representation and reasoning framework for supporting job Hazard analysis publication-title: J. Comput. Civ. Eng. doi: 10.1061/(ASCE)CP.1943-5487.0000125 – volume: 19 start-page: 474 year: 2014 ident: 10.1016/j.autcon.2020.103310_bb0085 article-title: Validating ontologies in informatics systems: approaches and lessons learned for AEC publication-title: Journal of Information Technology in Construction – ident: 10.1016/j.autcon.2020.103310_bb0280 – volume: 26 start-page: 368 year: 2011 ident: 10.1016/j.autcon.2020.103310_bb0030 article-title: Automated object identification using optical video cameras on construction sites publication-title: Computer-Aided Civil and Infrastructure Engineering doi: 10.1111/j.1467-8667.2010.00690.x – volume: 29 start-page: 472 year: 2015 ident: 10.1016/j.autcon.2020.103310_bb0160 article-title: Developing taxonomy for the domain ontology of construction contractual semantics: a case study on the AIA A201 document publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2015.03.009 – start-page: 22 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0150 article-title: Mask R-CNN – volume: 24 start-page: 194 year: 2012 ident: 10.1016/j.autcon.2020.103310_bb0010 article-title: Part based model and spatial-temporal reasoning to recognize hydraulic excavators in construction images and videos publication-title: Autom. Constr. doi: 10.1016/j.autcon.2012.03.003 – volume: 146 year: 2020 ident: 10.1016/j.autcon.2020.103310_bb0140 article-title: Ontology-Based Semantic Modeling of Knowledge in Construction: Classification and Identification of Hazards Implied in Images publication-title: J. Constr. Eng. Manage. doi: 10.1061/(ASCE)CO.1943-7862.0001767 – volume: 24 start-page: 252 year: 2009 ident: 10.1016/j.autcon.2020.103310_bb0130 article-title: Computer vision-based video interpretation model for automated productivity analysis of construction operations publication-title: ASCE Journal of Computing in Civil Engineering doi: 10.1061/(ASCE)CP.1943-5487.0000027 – volume: 30 issue: 6 year: 2016 ident: 10.1016/j.autcon.2020.103310_bb0315 article-title: Overview and analysis of ontology studies supporting development of the construction industry publication-title: J. Comput. Civ. Eng. doi: 10.1061/(ASCE)CP.1943-5487.0000594 – volume: 43 year: 2020 ident: 10.1016/j.autcon.2020.103310_bb0120 article-title: Computer vision for behavior-based safety in construction: a review and future directions publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2019.100980 – ident: 10.1016/j.autcon.2020.103310_bb0080 – volume: 28 start-page: 381 year: 2014 ident: 10.1016/j.autcon.2020.103310_bb0025 article-title: Using ontology-based text classification to assist job Hazard analysis publication-title: Adv. Eng. Inform. doi: 10.1016/j.aei.2014.05.001 – volume: 11 start-page: 501 issue: 5 year: 2002 ident: 10.1016/j.autcon.2020.103310_bb0135 article-title: Integration of virtually real construction model and design-for-safety-process database publication-title: Autom. Constr. doi: 10.1016/S0926-5805(01)00061-9 – volume: 101 start-page: 11 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0250 article-title: Building information modeling and safety management: a systematic review publication-title: Saf. Sci. doi: 10.1016/j.ssci.2017.08.015 – ident: 10.1016/j.autcon.2020.103310_bb0090 doi: 10.1061/41020(339)47 – volume: 13 start-page: 638 issue: 7 year: 2016 ident: 10.1016/j.autcon.2020.103310_bb0230 article-title: Falls from height in the construction industry: a critical review of the scientific literature publication-title: Int. J. Environ. Res. Public Health doi: 10.3390/ijerph13070638 – ident: 10.1016/j.autcon.2020.103310_bb0265 – volume: 60 start-page: 91 year: 2004 ident: 10.1016/j.autcon.2020.103310_bb0225 article-title: Distinctive image features from scale-invariant keypoints publication-title: Int. J. Comput. Vis. doi: 10.1023/B:VISI.0000029664.99615.94 – volume: 110 year: 2020 ident: 10.1016/j.autcon.2020.103310_bb0115 article-title: Computer vision applications in construction safety assurance publication-title: Autom. Constr. doi: 10.1016/j.autcon.2019.103013 – volume: 8 start-page: 218 year: 2008 ident: 10.1016/j.autcon.2020.103310_bb0005 article-title: Ontology-based information and knowledge management in construction publication-title: Constr. Innov. doi: 10.1108/14714170810888976 – volume: 71 start-page: 158 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0260 article-title: Handcrafted vs. non-handcrafted features for computer vision classification publication-title: Pattern Recogn. doi: 10.1016/j.patcog.2017.05.025 – volume: 17 start-page: 1481 issue: 8 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0310 article-title: Applying sensor-based technology to improve construction safety management publication-title: Sensors doi: 10.3390/s17081841 – volume: 30 year: 2016 ident: 10.1016/j.autcon.2020.103310_bb0185 article-title: Vision-based object-centric safety assessment using fuzzy inference: monitoring struck-by accidents with moving objects publication-title: J. Comput. Civ. Eng. doi: 10.1061/(ASCE)CP.1943-5487.0000562 – volume: 26 start-page: 769 year: 2012 ident: 10.1016/j.autcon.2020.103310_bb0015 article-title: Automated visual recognition of dump trucks in construction videos publication-title: ASCE Journal of Computing in Civil Engineering doi: 10.1061/(ASCE)CP.1943-5487.0000179 – volume: 86 start-page: 210 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0155 article-title: Ontology-driven development of web services to support district energy applications publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.10.004 – volume: 35 start-page: 221 issue: 1 year: 2013 ident: 10.1016/j.autcon.2020.103310_bb0165 article-title: 3D convolutional neural networks for human action recognition publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2012.59 – volume: 88 start-page: 23 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0175 article-title: 3D reconstruction of a concrete mixer truck for training object detectors publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.12.034 – volume: 99 start-page: 168 year: 2019 ident: 10.1016/j.autcon.2020.103310_bb0190 article-title: Remote proximity monitoring between mobile construction resources using camera-mounted UAVs publication-title: Autom. Constr. doi: 10.1016/j.autcon.2018.12.014 – volume: 521 start-page: 436 year: 2015 ident: 10.1016/j.autcon.2020.103310_bb0195 article-title: Deep learning publication-title: Nature doi: 10.1038/nature14539 – volume: 57 start-page: 249 year: 2015 ident: 10.1016/j.autcon.2020.103310_bb0035 article-title: A performance assessment ontology for the environmental and energy management of buildings publication-title: Autom. Constr. doi: 10.1016/j.autcon.2015.05.002 – volume: 53 start-page: 44 year: 2015 ident: 10.1016/j.autcon.2020.103310_bb0145 article-title: Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs publication-title: Autom. Constr. doi: 10.1016/j.autcon.2015.02.007 – volume: 31 start-page: 505 year: 2013 ident: 10.1016/j.autcon.2020.103310_bb0220 article-title: Occupational health and safety in the construction industry publication-title: Constr. Manag. Econ. doi: 10.1080/01446193.2013.816435 – year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0170 article-title: A cypher query based NoSQL data mining on protein databases using Neo4j graph database – volume: 82 start-page: 193 year: 2017 ident: 10.1016/j.autcon.2020.103310_bb0305 article-title: An experimental study of real-time identification of construction workers’ unsafe behaviors publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.05.002 – volume: 86 start-page: 118 year: 2018 ident: 10.1016/j.autcon.2020.103310_bb0050 article-title: X, a deep hybrid learning model to detect unsafe behavior: integrating convolution neural networks and long short-term memory publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.11.002 – volume: 136 start-page: 170 issue: 2 year: 2010 ident: 10.1016/j.autcon.2020.103310_bb0060 article-title: Case-based reasoning approach to construction safety Hazard identification: adaptation and utilization publication-title: ASCE Journal of Construction Engineering and Management doi: 10.1061/(ASCE)CO.1943-7862.0000116 |
| SSID | ssj0007069 |
| Score | 2.639112 |
| Snippet | Hazards potentially affect the safety of people on construction sites include falls from heights (FFH), trench and scaffold collapse, electric shock and arc... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 103310 |
| SubjectTerms | Accidents Algorithms Computer vision Construction sites Fatalities Flashover Hazard identification Hazard mitigation Hazards Knowledge bases (artificial intelligence) Knowledge graph database Ontology Regulations Safety |
| Title | Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology |
| URI | https://dx.doi.org/10.1016/j.autcon.2020.103310 https://www.proquest.com/docview/2460787769 |
| Volume | 119 |
| WOSCitedRecordID | wos000579045500002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-7891 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0007069 issn: 0926-5805 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1db9MwFLWgQwIeEAwQg4H8wFvkKYkdO-ZtgqIN0ITEgL5FjpOwTFMy0W6a-PVcf7alQgMkXqIqbeyo59i5Prn3GKGXTa6bmsqMUCYawnjaEKkUI5rrQjPa0dxWpX35II6OytlMfvSC_txuJyCGoby6kuf_FWo4B2Cb0tm_gDs2CifgM4AOR4Adjn8E_PugkiXWjNrmEfa2HNeVNJ2oH6bQyrwl0OPSPzYxr5Ftftyhd5Dw5bh204fE1aA72dZYHkQxPjjYXixGVwWZ9OsNR4Z4Zfpr25_1SyHcCwPfYmbQeNnGxOFkuvdmL35zYWXdAzXU3i7cqxWwNM3W1IrNMhqnReacFGVarE3LbirdmOKd2nBqEnyMYmA6Mc4B1GfHrptnfzJNm5YhTk3N7u430VYuCllO0Nb-4XT2Lj61RcqdL6O_lVBmaXMBN_v6XRjzywPdRinH99E9v7zA-44WD9CNdthGt0P1-Xwb3V0xoHyITiJZsCULBrLgFbJgTxY8DngVU2zJ8gqvUAUHqmBHFWyoggNVHqHPb6fHrw-I33uDaErZgmSqLruCa7OiVEzqvGllk0JEpWVHay1hXSCoytKOcc0Y00oLs2eXUhBuwjCX9DGaDOPQPkGYtTDiO16oOjPLcS0hhNSlYtBPwyWXO4iGv7LS3pje7I9yVoUMxNPKAVAZACoHwA4i8apzZ8xyze9FQKnywaULGisg1jVX7gZQKz_O51UO0xo86wSXT_-54WfoznKI7KIJYNg-R7f05aKff3_hCfoTkxGt-g |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Knowledge+graph+for+identifying+hazards+on+construction+sites%3A+Integrating+computer+vision+with+ontology&rft.jtitle=Automation+in+construction&rft.au=Fang%2C+Weili&rft.au=Ma%2C+Ling&rft.au=Love%2C+Peter+E.D.&rft.au=Luo%2C+Hanbin&rft.date=2020-11-01&rft.pub=Elsevier+B.V&rft.issn=0926-5805&rft.volume=119&rft_id=info:doi/10.1016%2Fj.autcon.2020.103310&rft.externalDocID=S0926580519309082 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0926-5805&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0926-5805&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0926-5805&client=summon |