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Location-Based Safety Management with Wearable Seamless Indoor-Outdoor Positioning

arXiv2 min read

arXiv:2610.21503v1 Announce Type: new Abstract: Reliable worker localization is essential for real-time industrial safety management, but seamless outdoor-indoor positioning remains challenging. GNSS performs well outdoors yet degrades near buildings and fails indoors, while many indoor systems require costly infrastructure or extensive calibration. This paper presents a practical safety-oriented positioning system that uses resource-constrained wearable tags and a device-cloud split architecture for continuous outdoor-indoor worker tracking. The tag integrates GNSS, IMU, barometric sensing, LTE Cat-M communication, and performs lightweight sensor fusion, while the cloud server executes map-aware fusion for continuous tracking. Developed as an operational platform, the system also includes a database, a map tool, and a dashboard that provide real-time monitoring, geofencing-based access alerts, and safety and productivity analysis. Experiments with multiple participants, each walking an approximately 1400 m outdoor-indoor route, using LTE Cat-M communication, achieve mean errors of 1.32 m indoors and 3.30 m outdoors, while maintaining low positioning latency and efficient power consumption. These results demonstrate the feasibility of wearable-based seamless positioning for scalable real-time safety management.

Abstract:Reliable worker localization is essential for real-time industrial safety management, but seamless outdoor-indoor positioning remains challenging. GNSS performs well outdoors yet degrades near buildings and fails indoors, while many indoor systems require costly infrastructure or extensive calibration. This paper presents a practical safety-oriented positioning system that uses resource-constrained wearable tags and a device-cloud split architecture for continuous outdoor-indoor worker tracking. The tag integrates GNSS, IMU, barometric sensing, LTE Cat-M communication, and performs lightweight sensor fusion, while the cloud server executes map-aware fusion for continuous tracking. Developed as an operational platform, the system also includes a database, a map tool, and a dashboard that provide real-time monitoring, geofencing-based access alerts, and safety and productivity analysis. Experiments with multiple participants, each walking an approximately 1400 m outdoor-indoor route, using LTE Cat-M communication, achieve mean errors of 1.32 m indoors and 3.30 m outdoors, while maintaining low positioning latency and efficient power consumption. These results demonstrate the feasibility of wearable-based seamless positioning for scalable real-time safety management.

Robotics (cs.RO)

arXiv:2610.21503 [cs.RO]

(or arXiv:2610.21503v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.21503 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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