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Artificial Intelligence-Based Detection System for Hazardous Liquid Metal Fire

机译:基于人工智能的危险液体金属火灾检测系统

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Liquid metals are commonly used in chemical industries and nuclear reactors. Since liquid metals may be hazardous, they should be handled very carefully. Careless handling might cause an adverse effect and even disasters. Corrosion and pressure can deteriorate the structure that handles the liquid metals. Leakage of liquid metals can result in ecological disasters and can lead to a humanitarian crisis. Early warning systems, detection of the accident, and prompt steps taken after the incident are the three important phases of monitoring. Continuous monitoring and timely detection of risk reduce the impact caused by the leakage of liquid metal. At present, industries have sensors-based detection. This paper proposes an enhanced version of the existing system. Here, continuous monitoring uses sensors, the Internet of things (IoT), and an artificial intelligence-based system. In this paper, the conventional system is integrated with AI to identify indoor and open-air fire situations. This paper discusses different data collected and investigated data from the videos, sensors, other monitoring systems. And the false-positive results are reduced by using the proposed methodology.
机译:液体金属通常用于化学工业和核反应堆。由于液体金属可能是危险的,因此应该非常仔细地处理它们。粗心的处理可能会导致不利影响甚至灾难。腐蚀和压力会使处理液态金属的结构劣化。液体金属的渗漏可能导致生态灾害,可以导致人道主义危机。早期预警系统,检测事故,事件发生后采取的提示措施是监测的三个重要阶段。持续监测和及时检测风险降低了液态金属泄漏造成的影响。目前,行业具有基于传感器的检测。本文提出了现有系统的增强版本。这里,连续监控使用传感器,物联网(物联网)和基于人工智能的系统。在本文中,传统系统与AI集成,以识别室内和露天火灾情况。本文讨论了收集和调查视频,传感器,其他监控系统的数据的不同数据。通过使用所提出的方法来减少假阳性结果。

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