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http://dx.doi.org/10.12815/kits.2020.19.6.61

Methodology of Calibration for Falling Objects Accident-Risk-Zone Approach Detection Algorithm at Port Considering GPS Errors  

Son, Seung-Oh (Dept. of Smart city Eng., Hanyang Univ.)
Kim, Hyeonseo (Dept. of Smart city Eng., Hanyang Univ.)
Park, Juneyoung (Dept. of Transportation & Logistics Eng, Smart city Eng., Hanyang Univ.)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.19, no.6, 2020 , pp. 61-73 More about this Journal
Abstract
Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.
Keywords
Active safety management system; Port worker safety; Accident risk management algorithm; Internet of Things (IoT); Real-time locating system;
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Times Cited By KSCI : 1  (Citation Analysis)
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