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Semantic enrichment of spatio-temporal trajectories for worker safety on construction sites

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Abstract

Thousands of fatalities are reported from the construction industry every year and a high percentage of them are due to the unsafe worker movements which resulted in falling from heights, transportation accidents, exposure to harmful environments, and striking against or being struck by the moving equipment. To reduce such fatalities, a system is proposed to monitor worker movements on a construction site by collecting their raw spatio-temporal trajectory data and enriching it with the relevant semantic information. To acquire the trajectories, the use of an indoor positioning system (IPS) is considered. Bluetooth beacons are used for collecting spatio-temporal information of the building users. By means of an Android-based mobile application, neighboring beacons’ signals are selected, and a geo-localization technique is performed to get the unique pairs of users’ location coordinates. After pre-processing this collected data, three semantic enrichment techniques are used to construct semantically enriched trajectories which are as follows: (1) enrichment with the semantic points which maps site location identification to the trajectory points; (2) enrichment with the semantic lines which relies on the speed-based segmentation approach to infer user modes of transportation; (3) enrichment with the semantic region for mapping a complete trajectory on an actual building or a construction site zone. The proposed system will help in extracting multifaceted trajectory characteristics and generates semantic trajectories to enable the desired semantic insights for better understanding of the underlying meaningful worker movements using the contextual data related to the building environment. Generated semantic trajectories will help health and safety (H&S) managers in making improved decisions for monitoring and controlling site activities by visualizing site-zones’ density to avoid congestion, proximity analysis to prevent workers collisions, identifying unauthorized access to hazardous areas, and monitoring movements of workers and machinery to reduce transportation accidents.

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Acknowledgements

The authors thank the Conseil Régional de Bourgogne-Franche-Comté, the French government for their funding, SATT Grand-Est, and IUT-Dijon (http://iutdijon.u-bourgogne.fr). The authors also want to thank Orval Touitou for his technical assistance to this research work.

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Authors and Affiliations

  1. Laboratoire d’Informatique de Bourgogne - EA 7534, University Bourgogne Franche-Comté, 9 rue Alain Savary, 21078, Dijon Cedex, France

    Muhammad Arslan & Christophe Cruz

  2. Laboratoire Imagerie et Vision Artificielle - EA 7535, University Bourgogne Franche-Comté, 9 rue Alain Savary, 21078, Dijon Cedex, France

    Dominique Ginhac

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  1. Muhammad Arslan
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Correspondence to Muhammad Arslan.

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Arslan, M., Cruz, C. & Ginhac, D. Semantic enrichment of spatio-temporal trajectories for worker safety on construction sites. Pers Ubiquit Comput 23, 749–764 (2019). https://doi.org/10.1007/s00779-018-01199-5

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