Visualizing intrusions in dynamic building environments for worker safety

Abstract

To overcome the limitations of traditional Behavior-Based Safety (BBS) methods, geo-localization systems are used for acquiring spatio-temporal trajectories to identify unsafe worker behaviors on construction sites. However, spatiotemporal trajectories lack contextual building or site information. For incorporating the geographical and applicationspecific context in trajectories, semantic enrichment processes are executed. The semantic enrichment process should include changing contextual information related to the evolving building objects over time. The changing contextual information of building objects is required to be tracked by a system to study the worker behaviors in a dynamic building environment context. After reviewing the existing literature, it is concluded that none of the present systems offer a mechanism to identify unsafe worker behaviors such as intrusions in dynamic environments where the contextual information of building spaces evolves over time in terms of location, size, properties and relationships with the environment. To fill this research gap, a system is proposed; First, to acquire the worker movements using Bluetooth Low Energy (BLE) beacons. Second, to perform the pre-processing as well as semantically enriching the spatio-temporal worker trajectories using relevant updated contextual information of a building. Lastly, to visualize the building locations where intrusions have occurred using Building Information Modeling (BIM) approach. The developed system presents an integration of systems from the data acquisition stage to visualizing the unsafe work behaviors that could serve as a foundation for future research in studying advanced movement-related worker behaviors in dynamic environments by overcoming the spatio-temporal data management challenges.

Spatio-temporal dataset of building occupants

“…The described dataset presented above has been utilized in developing applications for monitoring worker safety by analyzing their movements in real-time [3,4]. As the collected spatio-temporal data consist of ordered sequences of discrete-time triples in the form of 〈latitude, longitude, timestamp〉 include a timestamp (i.e.…”

“…the building locations, where the data was acquired), and the semantics of time (i.e. time interval of an occupant movement with a start and a stop timestamp) give move meaning in extracting mobility-related behaviors of occupants in buildings [3,4]. Based on the extracted information from spatio-temporal movements and an OSM file of a building, two applications were developed.…”

“…Based on the extracted information from spatio-temporal movements and an OSM file of a building, two applications were developed. The developed applications [3,4] focused on; 1) acquiring the spatio-temporal data of occupants, 2) executing relevant safety risk assessment techniques on the processed spatio-temporal data, 3) generating timely alerts to occupants for triggering safety interventions to improve their personal behavior during hazard proximity conditions, and 4) disseminating the safety information as defined by the system user to building supervisors and safety managers to take quick actions for maintaining building safety.…”

“…1BLE beacons by Kontakt.io used for data collection.

Fig. 2Mounting BLE beacons on different floors in a building [3,4].

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Understanding Occupant Behaviors in Dynamic Environments using OBiDE framework

“…Few locations were not identified correctly because of indoor interferences caused by the building objects and people which resulted in inaccurate recognition of the building locations. Closer investigation [51] to trajectory data revealed that inaccuracies in the system majorly caused because of below reasons;…”