| Mining is a high-risk industries, according to the State Administration of Work Safety Website reported, there were 256 cases of coal mine accidents and 420 people were killed in China from January 2015 to September. Therefore, it is important to reasonably construct the mine safety detection system and fully develop mine safety equipment. Currently, the research of the mine IoT(Internet of things) has achieved certain results which unifies dispatching automation management of mine production from the perspective of system engineering. This topic is based on the concept of Internet of things in mines, aiming to integrate the mine worker and the smart helmet into a special mobile intelligent node by embedding the helmet with personnel positioning system and environment monitoring sensors, through which it has the function of communication, environmental monitoring, positioning and video surveillance. Since the main way of people to obtain information is through images, video surveillance has became an important part of the object monitoring system in underground mines. At present, the mainstream of video surveillance is to install the probes in the fixed position to capture image and then ransmit data through the wired network. It's difficult for this monitoring approach to adapt to the underground complex environment and even take little effects when it comes to motoring the working condition of the mechanical and electrical equipment in the chamber and mining work face water inrush tor hidden trouble and so on. In contrast, mobile video surveillance can well meet the requirements of downhole use. The significance of this project is to provide a video monitoring system which can work offline to solve the problems of the production blind spot inspection, security monitoring and location and other state detection and tracking problems.Innovations of the topics includes:1) put forward a kind of wireless video surveillance which can work on online/offline mode and is integrated with positioning information, providing managers with intuitive image of the monitoring effect, completing the implementation of "quasi real-time video monitoring" in the area of network signal coverage limited. Mobile video surveillance system based on intelligent helmets can be divided into two parts including the mobile terminal and PC management software. Mobile terminals use the platform of HISILICON Hi3516A while the management software will be programmed by C++language, and HISILICON SDK is applied to manage mobile equipment, Qt to design the interface, and decoding kenel is based on FFMPEG framework. After test, it was proved to achieve the video saved offline, online transmission, location information and video information matching functions, which can solve the problem of the small signal coverage limitation.2) Propose a scheme of using H.265/HEVC for underground mobile video surveillance which can reduce the code stream by 50% under the condition that the video quality is constant. Due to the dual limitation of computing power of embedded devices and the bandwidth of underground wireless communication, the algorithm complexity hinder the practice application of H.265/HEVC. In this paper, the algorithm is de-complicated to improve coding speed under the premise of ensuring video quality. The coding options were tested, and a series of representative coding options were selected for the experiment, finally a fast encoding parameters combination was recommended. In this case, the encoding time decreases by 63%, thus effectively improving the coding speed. |
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