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Appl. Sci. 2017, 7(9), 925; doi:10.3390/app7090925

An Event Reporting and Early-Warning Safety System Based on the Internet of Things for Underground Coal Mines: A Case Study

Department of Civil and Environmental Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea
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Received: 3 August 2017 / Revised: 1 September 2017 / Accepted: 5 September 2017 / Published: 8 September 2017
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Abstract

Fatal accidents associated with underground coal mines require the implementation of high-level gas monitoring and miner’s localization approaches to promote underground safety and health. This study introduces a real-time monitoring, event-reporting and early-warning platform, based on cluster analysis for outlier detection, spatiotemporal statistical analysis, and an RSS range-based weighted centroid localization algorithm for improving safety management and preventing accidents in underground coal mines. The proposed platform seamlessly integrates monitoring, analyzing, and localization approaches using the Internet of Things (IoT), cloud computing, a real-time operational database, application gateways, and application program interfaces. The prototype has been validated and verified at the operating underground Hassan Kishore coal mine. Sensors for air quality parameters including temperature, humidity, CH4, CO2, and CO demonstrated an excellent performance, with regression constants always greater than 0.97 for each parameter when compared to their commercial equivalent. This framework enables real-time monitoring, identification of abnormal events (>90%), and verification of a miner’s localization (with <1.8 m of error) in the harsh environment of underground mines. The main contribution of this study is the development of an open source, customizable, and cost-effective platform for effectively promoting underground coal mine safety. This system is helpful for solving the problems of accessibility, serviceability, interoperability, and flexibility associated with safety in coal mines. View Full-Text
Keywords: underground mines; event detection; outlier detection; Internet of Things; miner’s localization underground mines; event detection; outlier detection; Internet of Things; miner’s localization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Jo, B.W.; Khan, R.M.A. An Event Reporting and Early-Warning Safety System Based on the Internet of Things for Underground Coal Mines: A Case Study. Appl. Sci. 2017, 7, 925.

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