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Paper lc3-2017-185:
BIM4LIFE: GNSS and BIM Data Fusion for Mapping Human-Machine Interaction

Facilitated by the SciX project

Olga Golovina and Jochen Teizer

BIM4LIFE: GNSS and BIM Data Fusion for Mapping Human-Machine Interaction

Abstract: This paper presents an effective approach towards integrating Real-time Location Sensing (RTLS) and Building Information Modeling (BIM) data for mapping near hit events related to human-machine interaction on construction sites. The study under the concept called BIM for lean and injury free environments (BIM4LIFE) focuses on key managerial and technological issues in planning safe and productive work environments: (a) the reliance of current performance measurement practices on lagging instead of adapting to leading indicator data and (b) the common unstructured nature and dynamic progress of construction work environments making it difficult to collect data that leads to quality information. Both call for reliable information and communication technology (ICT) in infrastructure and information management processes to advance safety in construction. The data employed are trajectories from Global Navigation Satellite System (GNSS) data loggers, while an as-is building information model and a-priori collected true geometric equipment information are the other main data sources. The initial result of the data fusion process is a heat map that precisely analyses pedestrian worker and equipment interactions. The novelty of this work lies in solving the interface issues from RTLS data to BIM and to automated protective safety equipment modelling. The methods were tested in realistic work settings. The paper concludes with a critical review on the reliability of the methods employed as well as an outlook on possible changes to current work practices.

Keywords: BIM4LIFE, Construction Safety, Remote Sensing, Equipment Operator Visibility, Human-Machine Interaction, Building Information Modelling (BIM)

DOI: https://doi.org/10.24928/JC3-2017/0185

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Series: jc3:2017 (browse)
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