1. Главная
  2. Ресурсы
  3. Библиотечный поиск
An Event Reportingand Early-WarningSafety System Basedon the Internet ofThings forUnderground CoalMines: A Case Study Byung-Wan JoRana Muhammad Asad Khan2017 год

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

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: 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.
Год издания: 2017
Авторы: Byung-Wan Jo, Rana Muhammad Asad Khan
Издательство: Multidisciplinary Digital Publishing Institute
Источник: Applied Sciences
Ключевые слова: Fire Detection and Safety Systems, Air Quality Monitoring and Forecasting, Anomaly Detection Techniques and Applications
Другие ссылки: Applied Sciences (PDF)
Applied Sciences (HTML)
DOAJ (DOAJ: Directory of Open Access Journals) (HTML)
The Royal Society of Chemistry’s Journals, Books and Databases (The Royal Society of Chemistry) (PDF)
The Royal Society of Chemistry’s Journals, Books and Databases (The Royal Society of Chemistry) (HTML)