Fang, W;
Ma, L;
Love, PED;
Luo, H;
Ding, L;
Zhou, A;
(2020)
Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology.
Automation in Construction
, 119
, Article 103310. 10.1016/j.autcon.2020.103310.
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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.
| Type: | Article |
|---|---|
| Title: | Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.autcon.2020.103310 |
| Publisher version: | https://doi.org/10.1016/j.autcon.2020.103310 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Hazards; ontology; computer vision; safety; knowledge graph database |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10104559 |
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