A mine video transmission method and system

Abstract

The present application is suitable for the field of communication transmission, and provides a mine-used video transmission method, which comprises the following steps: acquiring real-time video data and event alarm data and synchronously associating to obtain real-time data stream; identifying and detecting the real-time data stream, and generating a video repair instruction including a specific time range according to the identification and detection result; issuing the video repair instruction to the corresponding camera equipment in the mine, so as to make the camera equipment upload the corresponding video segment stored in itself; after receiving the video segment, the video data is replaced by means of timestamp alignment and content checking. The present application effectively overcomes the problems of unstable network and easy packet loss in the complex environment of the mine, and significantly improves the data resilience of the mine safety monitoring system.

Description

Technical Field

[0001] This invention relates to the field of communication transmission, specifically to a video transmission method and system for use in mines. Background Technology

[0002] In modern mine safety systems, underground video surveillance plays a crucial role. The transmitted and stored video data is the core basis for real-time scheduling, behavioral monitoring, and post-accident tracing. Therefore, ensuring the integrity of key video segments is extremely important.

[0003] Mine video transmission typically employs a hybrid wired and wireless networking mode. It primarily uses a fiber optic ring network to form a high-speed, reliable backbone channel connecting various areas. Wired access is then provided via industrial Ethernet at fixed monitoring points, while mobile devices (such as coal mining machines and inspection vehicles) and complex areas rely on mine-specific Wi-Fi or dedicated 5G networks for flexible wireless coverage. However, the complex and harsh mine environment, with its variable tunnel structures and strong electromagnetic interference from large equipment, leads to highly unstable network transmission channels. This causes packet loss and bit errors during real-time video transmission, resulting in screen tearing, stuttering, and even keyframe loss in the centrally stored video.

[0004] Existing solutions primarily focus on optimizing real-time transmission quality or implementing simple local caching. However, once transmission is interrupted and the cache is overwritten, it becomes impossible to repair archived video defects, making it difficult to meet the stringent requirements of mines for critical visual evidence. Therefore, this paper proposes a video transmission method and system for mines, aiming to address the aforementioned problems. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a video transmission method and system for mines to solve the problems existing in the background technology.

[0006] This invention is implemented as follows: a video transmission method for use in mines, the method comprising the following steps: Real-time video data and event alarm data are acquired and synchronously correlated to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. The real-time data stream is identified and detected, and a video repair instruction including a specific time range is generated based on the identification and detection results. The time range is the start and end time of the video segment to be repaired. The video repair command is sent to the corresponding camera device downhole, so that the camera device can upload the corresponding video clip stored on it. Upon receiving the video segment, the video data is overwritten and replaced using timestamp alignment and content verification.

[0007] As a further aspect of the present invention: the step of acquiring real-time video data and event alarm data and synchronously associating them to obtain a real-time data stream specifically includes: A three-dimensional structural model of the mine is constructed based on geological exploration data and mine construction drawings, and a spatial coordinate database of reflection points in the mine space is established based on the known locations of camera equipment. When acquiring real-time video data from camera equipment, edge detection technology is used to extract reflected images from the video frame. These reflected images are obtained by deploying reflectors at reflection points within the mine and coordinating with visible light sources synchronized with the camera equipment. Based on a three-dimensional structural model and a spatial coordinate database of reflection points, the reflected image is converted into video data from a normal viewing angle through geometric transformation and image reconstruction, and then integrated with the real-time video data, thereby expanding the field of view of the camera device. The processed real-time video data and event alarm data are spatiotemporally aligned to obtain a structured real-time data stream, wherein the event alarm data is obtained through various sensors deployed in the mine.

[0008] As a further aspect of the present invention: the step of identifying and detecting real-time data streams specifically includes: The frame sequence number and timestamp interval of real-time video data are checked, and lightweight image analysis is performed to obtain video features, which are used to check for frame loss and screen distortion. The event alarm data is analyzed to obtain signal features, which are then correlated with video features; The associated features are prioritized according to pre-defined rules, with the priority decreasing in the order of alarm events, behavioral events, and transmission anomaly events. Based on the priority classification results, a task scheduling plan is generated so that alarm-type events and behavioral events are issued and executed in a timely manner, while transmission anomaly-type events are issued and executed only during network idle periods.

[0009] As a further aspect of the present invention: the prefabrication rules include: When alarm characteristics are detected in the event alarm data, all videos within the corresponding time window are marked as the highest priority event; When abnormal behavior characteristics are identified through video analysis, the video of the time period corresponding to the abnormal behavior is marked as a high-priority event. When an anomaly is detected only at the video transmission level, the real-time video data that is abnormal will be marked as a normal priority event.

[0010] As a further aspect of the present invention, the method further includes: The video streams from all cameras within its coverage area are continuously received and cached by the regional edge node, which is a data storage device deployed in the underground machine room; When it is determined that video repair and uploading are required and the corresponding camera device does not respond, an auxiliary repair request is generated. The request includes the time range of the required video segment and the corresponding camera device identifier. The auxiliary repair request is sent to the edge node of the region to which the camera device belongs, so that the edge node retrieves and extracts the corresponding complete video segment from its cache and sends it back; Receive complete video clips transmitted from edge nodes in the receiving area and perform overwrite replacement.

[0011] As a further aspect of the present invention, the method further includes: When video repair and uploading are required, the real-time status parameters of the corresponding camera device are queried. The real-time status parameters include the remaining lifespan of the storage medium, the read / write error rate, and the network connection quality. The health status of the camera device is judged based on real-time status parameters stored locally. When its health status is abnormal, ignore the request process to the camera device and directly execute the process of generating an auxiliary repair request and sending it to the regional edge node; After obtaining the complete video segment, integrity is verified by calculating the hash value, and an archive log is recorded after the video is overwritten or replaced.

[0012] Another object of the present invention is to provide a video transmission system for use in mines, the system comprising: The data association module is used to acquire real-time video data and event alarm data and synchronize them to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. The identification and detection module is used to identify and detect the real-time data stream, and generate video repair instructions including a specific time range based on the identification and detection results. The time range is the start and end time of the video segment to be repaired. The repair execution module is used to send video repair instructions to the corresponding camera equipment downhole, so that the camera equipment can upload the corresponding video clips stored in itself; The verification and replacement module is used to overwrite and replace video data after receiving the video segment by means of timestamp alignment and content verification.

[0013] As a further aspect of the present invention: the data association module includes: The model building unit is used to build a three-dimensional structural model of the mine based on geological exploration data and mine construction drawings, and to establish a spatial coordinate database of reflection points in the mine space based on the known locations of camera equipment. The image extraction unit is used to extract the reflected image in the video frame using edge detection technology when acquiring real-time video data from the camera equipment. The reflected image is obtained by deploying reflectors at reflection points in the mine and deploying visible light sources synchronized with the camera equipment. The perspective conversion unit is used to convert reflected images into video data from a normal perspective based on a three-dimensional structural model and a spatial coordinate database of reflection points through geometric transformation and image reconstruction, and integrate it with the real-time video data to expand the field of view of the camera device. The spatiotemporal alignment unit is used to spatiotemporally align the processed real-time video data with the event alarm data to obtain a structured real-time data stream. The event alarm data is obtained through various sensors deployed in the mine.

[0014] As a further aspect of the present invention: the identification and detection module includes: The inspection and analysis unit is used to check the frame sequence number and timestamp interval of real-time video data, and perform lightweight image analysis to obtain video features, which are used to check for frame loss and screen distortion. The feature association unit is used to parse the event alarm data to obtain signal features and associate them with video features; The priority classification unit is used to classify associated features according to pre-defined rules, with the priority of alarm-type events, behavioral events, and transmission anomaly events decreasing in that order. The task scheduling unit is used to generate a task scheduling plan based on the priority classification results, so that alarm-type events and behavioral events are sent out and executed in a timely manner, while transmission anomaly-type events are sent out and executed only during network idle periods.

[0015] As a further aspect of the present invention: the system further includes a collaborative repair module, which includes: An edge caching unit is used to continuously receive and cache video streams from all cameras within its coverage area through a regional edge node, wherein the regional edge node is a data storage device deployed in an underground machine room. The request generation unit is used to generate an auxiliary repair request when it is determined that video repair and uploading are required and the corresponding camera device does not respond. The request includes the time range of the required video segment and the corresponding camera device identifier. The request forwarding unit is used to send the auxiliary repair request to the area edge node to which the camera device belongs, so that the area edge node can retrieve and extract the corresponding complete video segment from its cache and send it back. The receiving execution unit is used to receive complete video segments transmitted from the edge nodes of the region and perform overlay replacement.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention, through intelligent correlation analysis of real-time video data and event alarm data, can diagnose quality defects caused by interference in real time during video transmission, or identify key segments by combining alarm events, and automatically initiate a video repair process. It extracts high-quality original video from the local cache of the camera equipment and then replaces the video segments, thus ensuring the integrity and reliability of archived video, especially key evidence before and after accident alarms, without relying on increasing real-time transmission bandwidth. This gives mine video transmission a proactive repair function. In summary, this invention effectively overcomes the problems of network instability and packet loss in the complex environment of mines, significantly improving the data resilience of mine safety monitoring systems. Attached Figure Description

[0017] Figure 1 This is a flowchart of a video transmission method for use in mines.

[0018] Figure 2 This is a flowchart illustrating how a video transmission method for use in mines obtains real-time data streams.

[0019] Figure 3 This is a flowchart illustrating the identification and detection of real-time data streams in a video transmission method for use in mines.

[0020] Figure 4 This is a flowchart illustrating a complete video segment transmitted from an edge node in a receiving area of ​​a video transmission method used in mines.

[0021] Figure 5 This is a flowchart illustrating the process of determining the health status of locally stored video equipment in a video transmission method for use in mines.

[0022] Figure 6 This is a schematic diagram of a video transmission system for use in mines.

[0023] Figure 7 This is a schematic diagram of the data association module in a video transmission system for mining operations.

[0024] Figure 8 This is a schematic diagram of the structure of an identification and detection module in a video transmission system used in mines.

[0025] Figure 9 This is a schematic diagram of the structure of a collaborative repair module in a video transmission system for use in mines. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0027] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0028] like Figure 1 As shown in the figure, an embodiment of the present invention provides a video transmission method for mines, the method comprising the following steps: S100: Acquire real-time video data and event alarm data and synchronize and correlate them to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. S200, identify and detect the real-time data stream, and generate a video repair instruction including a specific time range based on the identification and detection results, wherein the time range is the start and end time of the video segment to be repaired; S300 sends video repair instructions to the corresponding camera equipment downhole, so that the camera equipment can upload the corresponding video clips stored in itself; S400: After receiving the video segment, the video data is overwritten and replaced by timestamp alignment and content verification.

[0029] In this embodiment of the invention, through intelligent correlation analysis of real-time video data and event alarm data, the invention can diagnose quality defects caused by interference in real time during video transmission, or identify key segments by combining alarm events, and automatically initiate a video repair process. It extracts high-quality original video from the local cache of the camera equipment and then replaces the video segments, thereby ensuring the integrity and reliability of archived video, especially key evidence before and after accident alarms, without relying on increasing real-time transmission bandwidth. This enables proactive video repair capabilities in mines. In summary, this invention effectively overcomes problems such as network instability and packet loss in complex mine environments, significantly improving the data resilience of mine safety monitoring systems.

[0030] It should be noted that this invention does not require ideal real-time transmission with zero packet loss in the harsh channel conditions of mines. Instead, it proactively accepts the possibility of transmission impairment. This invention involves simultaneous transmission, inspection, and repair, with a primary focus on the data archiving stage. Without altering the existing mine network architecture or significantly increasing bandwidth pressure, this invention utilizes the synergy of edge storage and central intelligence to achieve time-selective restoration of critical video evidence, striking a balance between cost and reliability.

[0031] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of acquiring real-time video data and event alarm data and synchronously associating them to obtain a real-time data stream specifically includes: S101, Based on geological exploration data and mine construction drawings, a three-dimensional structural model of the mine is constructed, and a spatial coordinate database of reflection points in the mine space is established according to the known locations of camera equipment; S102, when acquiring real-time video data from the camera equipment, edge detection technology is used to extract the reflection image in the video frame. The reflection image is obtained by deploying reflectors at reflection points in the mine and deploying visible light sources synchronized with the camera equipment. S103, based on the three-dimensional structural model and the spatial coordinate database of reflection points, converts the reflected image into video data from a normal perspective through geometric transformation and image reconstruction, and integrates it with the real-time video data, thereby expanding the field of view of the camera device; S104, the processed real-time video data and event alarm data are spatiotemporally aligned to obtain a structured real-time data stream, wherein the event alarm data is obtained through various sensors deployed in the mine.

[0032] In this embodiment of the invention, a three-dimensional structural model is first constructed based on geological and mine construction drawings, and a precise spatial coordinate database of reflectors is established based on the known camera positions, thereby providing a spatial reference for image reconstruction. During actual data acquisition, reflectors and dedicated light sources synchronized with the cameras are deployed at key reflection points in the tunnel (such as corners), enabling the cameras to capture reflected light path images from non-direct-view areas. Then, edge detection technology is used to separate these reflected images from the original video frames. At this point, the role of the three-dimensional structural model is demonstrated. Through geometric correction and image reconstruction algorithms, distorted reflected images can be restored to images that conform to the normal viewing angle of the human eye. This method mainly utilizes optical principles to overcome the physical field of view limitations of the camera, achieving an indirect expansion of the monitoring range. Finally, the video stream after field of view expansion processing is precisely timestamped and spatially correlated with event alarm data (such as data from gas, vibration, and temperature sensors), thereby generating a spatiotemporally unified, structured real-time data stream. For example, at the corner of an L-shaped tunnel, cameras installed in the straight tunnel cannot directly monitor the area beyond the bend. Therefore, a reflector facing the concealed area is deployed at the bend, equipped with a synchronized strobe light source. When personnel or equipment are moving behind the bend, their images can be captured by the camera through this optical path, thus achieving monitoring coverage of the original physical blind spot.

[0033] It should be noted that the visible light source must strictly comply with mine safety standards and be a dedicated lighting device that is intrinsically safe or explosion-proof for mining. Its operating characteristics include hardware synchronization or precise timing linkage with the camera equipment, such as emitting pulses of light at specific frequencies within the camera's exposure cycle, thereby ensuring the clarity and signal-to-noise ratio of the captured reflected image. Furthermore, the spectrum, intensity, and duration of operation of the light source must be optimized to meet the minimum illuminance requirements for image acquisition while absolutely avoiding overheating or becoming a potential ignition source underground due to prolonged high-power operation.

[0034] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of identifying and detecting the real-time data stream specifically includes: S201 checks the frame sequence number and timestamp interval of real-time video data and performs lightweight image analysis to obtain video features, which are used to check for frame loss and screen distortion. S202, parse the event alarm data to obtain signal features, and associate them with video features; S203, classify the associated features according to pre-defined rules, with the priority of alarm-type events, behavior-type events, and transmission anomaly-type events decreasing in that order; S204, Generate a task scheduling plan based on the priority classification results, so that alarm events and behavioral events are sent and executed in a timely manner, while transmission anomaly events are sent and executed only during network idle periods.

[0035] It should be noted that the pre-defined rules include: when alarm features are detected in the event alarm data, all videos within the corresponding time window are marked as the highest priority event; when abnormal behavior features are detected through video analysis, the videos in the time period corresponding to the abnormal behavior are marked as high priority events; when only video transmission layer abnormalities are detected, the real-time video data with abnormalities are marked as ordinary priority events.

[0036] In this embodiment of the invention, the bitstream layer of real-time video data is first diagnosed. Packet loss and latency are detected by verifying the continuity of frame sequence numbers and analyzing the rationality of timestamp intervals. Lightweight image analysis algorithms are used to detect image defects such as screen tearing and blurring, thereby extracting video features that characterize the integrity and clarity of the video. Simultaneously, event alarm data from various mine safety sensors are analyzed to extract signal features representing their type and intensity. These signal features are then spatiotemporally correlated and bound with video features from the same time and space. Pre-defined rules are then used to prioritize the correlated features. For example, video time periods associated with hard safety alarms such as gas exceeding limits and emergency calls are marked as "highest priority events"; video time periods associated with potential risk behaviors such as running and smoke identified by video analysis are marked as "high-priority events"; and video time periods with only transmission errors and no content or safety association are marked as "normal priority events". Task scheduling (i.e., video repair) is then performed based on the priority determination results, ensuring that abnormal parts of high-priority videos are processed first. It should be noted that the objects determined by the pre-defined rules are all video segments that need repair. Suppose that at a certain moment, an anomaly is detected in the video through analysis. If a gas alarm is then detected from the event alarm data, the video at that moment will be prioritized for repair.

[0037] like Figure 4 As shown, in a preferred embodiment of the present invention, the video transmission method for mines further includes: S501, continuously receives and caches video streams from all cameras within its coverage area through a regional edge node, wherein the regional edge node is a data storage device deployed in an underground machine room; S502, when it is determined that video repair and uploading are required and the corresponding camera device does not respond, an auxiliary repair request is generated. The request includes the time range of the required video segment and the corresponding camera device identifier. S503, the auxiliary repair request is sent to the area edge node to which the camera device belongs, so that the area edge node retrieves and extracts the corresponding complete video segment from its cache and sends it back; S504 receives the complete video clip transmitted from the edge node of the region and performs overlay replacement.

[0038] In this embodiment of the invention, another parallel processing method is also provided, such as... Figure 5 As shown, the method further includes: S512, when video repair and uploading are required, query the real-time status parameters of the corresponding camera device. The real-time status parameters include the remaining lifespan of the storage medium, the read / write error rate, and the network connection quality. S513 determines the health status stored locally by the camera device based on real-time status parameters; S514, when its health status is abnormal, ignores the request process to the camera device and directly executes the process of generating an auxiliary repair request and sending it to the regional edge node; S515 performs integrity verification by calculating hash values ​​after obtaining a complete video segment, and records the archive log after the video is overwritten or replaced.

[0039] In a specific implementation, a multi-layered redundant repair mechanism is constructed by introducing regional edge nodes and a device health pre-inspection mechanism. The prerequisite is the deployment of regional edge nodes in relatively favorable locations such as underground mining area machine rooms. These nodes act as secondary caches, continuously receiving and storing copies of video streams uploaded by all camera devices within their jurisdiction, forming an intermediate data layer independent of the camera devices' local storage and the ground-based central storage. The system provides two progressive data acquisition logics for repair: first, when a direct request for supplementary recording to a camera device fails to receive a response, the request is redirected to its corresponding regional edge node; second, before making any request, the health status parameters of the camera device are queried. If an anomaly is detected, the request to that device is skipped, and the process of requesting the regional edge node is executed instead. It should be noted that regardless of the method used to obtain the complete video segment, a strict integrity check (such as hash value comparison) must be performed before data replacement, and the archive log must be updated after replacement. For example, if the system detects that the video from camera device X needs to be repaired for a certain period of time, and finds that the read / write error rate of camera device X's SD card has exceeded the safety threshold and has been judged as "abnormal health status", then it will not send a request to camera device X, but will directly generate an auxiliary repair request and send it to the edge node Z of the region that manages camera device X. Node Z will then retrieve the video copy for the corresponding time period from its cache and send it back.

[0040] like Figure 6 As shown in the figure, this embodiment of the invention also provides a video transmission system for mines, the system comprising: The data association module 100 is used to acquire real-time video data and event alarm data and synchronously associate them to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. The identification and detection module 200 is used to identify and detect the real-time data stream, and generate a video repair instruction including a specific time range based on the identification and detection results. The time range is the start and end time of the video segment to be repaired. The repair execution module 300 is used to send video repair instructions to the corresponding camera equipment downhole, so that the camera equipment can upload the corresponding video clips stored in itself. The verification and replacement module 400 is used to overwrite and replace video data by means of timestamp alignment and content verification after receiving the video segment.

[0041] like Figure 7 As shown, in a preferred embodiment of the present invention, the data association module 100 includes: Model building unit 101 is used to build a three-dimensional structural model of the mine based on geological exploration data and mine construction drawings, and to establish a spatial coordinate database of reflection points in the mine space based on the known locations of camera equipment. The image extraction unit 102 is used to extract the reflected image in the video frame using edge detection technology when acquiring real-time video data from the camera device. The reflected image is obtained by deploying reflectors at reflection points in the mine and deploying visible light sources synchronized with the camera device. The perspective conversion unit 103 is used to convert the reflected image into video data with a normal perspective based on the three-dimensional structural model and the spatial coordinate database of the reflection point through geometric transformation and image reconstruction, and integrate it with the real-time video data to expand the field of view of the camera device. The spatiotemporal alignment unit 104 is used to perform spatiotemporal alignment of the processed real-time video data and event alarm data to obtain a structured real-time data stream. The event alarm data is obtained through various sensors deployed in the mine.

[0042] like Figure 8 As shown, in a preferred embodiment of the present invention, the identification and detection module 200 includes: The inspection and analysis unit 201 is used to check the frame sequence number and timestamp interval of real-time video data, and perform lightweight image analysis to obtain video features, which are used to check for frame loss and screen distortion. The feature association unit 202 is used to parse the event alarm data to obtain signal features and associate them with video features; Priority classification unit 203 is used to classify associated features according to pre-defined rules, wherein the priority of alarm-type events, behavior-type events, and transmission anomaly-type events decreases in that order. The task scheduling unit 204 is used to generate a task scheduling plan based on the priority classification results, so that alarm-type events and behavioral events are sent and executed in a timely manner, while transmission anomaly-type events are sent and executed only during network idle periods.

[0043] like Figure 9As shown in a preferred embodiment of the present invention, the video transmission system for mines further includes a collaborative repair module 500, which includes: The edge caching unit 501 is used to continuously receive and cache video streams from all cameras within its coverage area through a regional edge node, wherein the regional edge node is a data storage device deployed in an underground machine room. The request generation unit 502 is used to generate an auxiliary repair request when it is determined that video repair and uploading are required and the corresponding camera device does not respond. The request includes the time range of the required video segment and the corresponding camera device identifier. The request forwarding unit 503 is used to send the auxiliary repair request to the area edge node to which the camera device belongs, so that the area edge node retrieves and extracts the corresponding complete video segment from its cache and sends it back; The receiving execution unit 504 is used to receive the complete video segment transmitted by the region edge node and perform overlay replacement.

[0044] The above description only details the preferred embodiments of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0045] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0046] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0047] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the disclosure in the specification and embodiments. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A video transmission method for use in mines, characterized in that, The method includes the following steps: Real-time video data and event alarm data are acquired and synchronously correlated to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. The real-time data stream is identified and detected, and a video repair instruction including a specific time range is generated based on the identification and detection results. The time range is the start and end time of the video segment to be repaired. The video repair command is sent to the corresponding camera device downhole, so that the camera device can upload the corresponding video clip stored on it. Upon receiving the video segment, the video data is overwritten and replaced using timestamp alignment and content verification.

2. The video transmission method for mines according to claim 1, characterized in that, The step of acquiring real-time video data and event alarm data and synchronously associating them to obtain a real-time data stream specifically includes: A three-dimensional structural model of the mine is constructed based on geological exploration data and mine construction drawings, and a spatial coordinate database of reflection points in the mine space is established based on the known locations of camera equipment. When acquiring real-time video data from camera equipment, edge detection technology is used to extract reflected images from the video frame. These reflected images are obtained by deploying reflectors at reflection points within the mine and coordinating with visible light sources synchronized with the camera equipment. Based on a three-dimensional structural model and a spatial coordinate database of reflection points, the reflected image is converted into video data from a normal viewing angle through geometric transformation and image reconstruction, and then integrated with the real-time video data, thereby expanding the field of view of the camera device. The processed real-time video data and event alarm data are spatiotemporally aligned to obtain a structured real-time data stream, wherein the event alarm data is obtained through various sensors deployed in the mine.

3. The video transmission method for mines according to claim 1, characterized in that, The steps for identifying and detecting real-time data streams specifically include: The frame sequence number and timestamp interval of real-time video data are checked, and lightweight image analysis is performed to obtain video features, which are used to check for frame loss and screen distortion. The event alarm data is analyzed to obtain signal features, which are then correlated with video features; The associated features are prioritized according to pre-defined rules, with the priority decreasing in the order of alarm events, behavioral events, and transmission anomaly events. Based on the priority classification results, a task scheduling plan is generated so that alarm-type events and behavioral events are issued and executed in a timely manner, while transmission anomaly-type events are issued and executed only during network idle periods.

4. The video transmission method for mines according to claim 3, characterized in that, The prefabrication rules include: When alarm characteristics are detected in the event alarm data, all videos within the corresponding time window are marked as the highest priority event; When abnormal behavior characteristics are identified through video analysis, the video of the time period corresponding to the abnormal behavior is marked as a high-priority event. When an anomaly is detected only at the video transmission level, the real-time video data that is abnormal will be marked as a normal priority event.

5. The video transmission method for mines according to claim 1, characterized in that, The method further includes: The video streams from all cameras within its coverage area are continuously received and cached by the regional edge node, which is a data storage device deployed in the underground machine room; When it is determined that video repair and uploading are required and the corresponding camera device does not respond, an auxiliary repair request is generated. The request includes the time range of the required video segment and the corresponding camera device identifier. The auxiliary repair request is sent to the edge node of the region to which the camera device belongs, so that the edge node retrieves and extracts the corresponding complete video segment from its cache and sends it back; Receive complete video clips transmitted from edge nodes in the receiving area and perform overwrite replacement.

6. The video transmission method for mines according to claim 5, characterized in that, The method further includes: When video repair and uploading are required, the real-time status parameters of the corresponding camera device are queried. The real-time status parameters include the remaining lifespan of the storage medium, the read / write error rate, and the network connection quality. The health status of the camera device is determined based on real-time status parameters stored locally. When its health status is abnormal, ignore the request process to the camera device and directly execute the process of generating an auxiliary repair request and sending it to the regional edge node; After obtaining the complete video segment, integrity is verified by calculating the hash value, and an archive log is recorded after the video is overwritten or replaced.

7. A video transmission system for use in mines, characterized in that, The system includes: The data association module is used to acquire real-time video data and event alarm data and synchronize them to obtain a real-time data stream. The real-time video data is acquired through camera equipment deployed underground, and the event alarm data is acquired through the mine safety system. The real-time video data is stored in the camera equipment in a cyclic overlay manner. The identification and detection module is used to identify and detect the real-time data stream, and generate video repair instructions including a specific time range based on the identification and detection results. The time range is the start and end time of the video segment to be repaired. The repair execution module is used to send video repair instructions to the corresponding camera equipment downhole, so that the camera equipment can upload the corresponding video clips stored in itself; The verification and replacement module is used to overwrite and replace video data by means of timestamp alignment and content verification after receiving the video segment.

8. The video transmission system for mines according to claim 7, characterized in that, The data association module includes: The model building unit is used to build a three-dimensional structural model of the mine based on geological exploration data and mine construction drawings, and to establish a spatial coordinate database of reflection points in the mine space based on the known locations of camera equipment. The image extraction unit is used to extract the reflected image in the video frame using edge detection technology when acquiring real-time video data from the camera equipment. The reflected image is obtained by deploying reflectors at reflection points in the mine and deploying visible light sources synchronized with the camera equipment. The perspective conversion unit is used to convert reflected images into video data from a normal perspective based on a three-dimensional structural model and a spatial coordinate database of reflection points through geometric transformation and image reconstruction, and integrate it with the real-time video data to expand the field of view of the camera device. The spatiotemporal alignment unit is used to spatiotemporally align the processed real-time video data with the event alarm data to obtain a structured real-time data stream. The event alarm data is obtained through various sensors deployed in the mine.

9. The video transmission system for mines according to claim 7, characterized in that, The identification and detection module includes: The inspection and analysis unit is used to check the frame sequence number and timestamp interval of real-time video data, and perform lightweight image analysis to obtain video features, which are used to check for frame loss and screen distortion. The feature association unit is used to parse the event alarm data to obtain signal features and associate them with video features; The priority classification unit is used to classify associated features according to pre-defined rules, with the priority of alarm-type events, behavioral events, and transmission anomaly events decreasing in that order. The task scheduling unit is used to generate a task scheduling plan based on the priority classification results, so that alarm-type events and behavioral events are sent out and executed in a timely manner, while transmission anomaly-type events are sent out and executed only during network idle periods.

10. The video transmission system for mines according to claim 7, characterized in that, The system also includes a collaborative repair module, which includes: An edge caching unit is used to continuously receive and cache video streams from all cameras within its coverage area through a regional edge node, wherein the regional edge node is a data storage device deployed in an underground machine room. The request generation unit is used to generate an auxiliary repair request when it is determined that video repair and uploading are required and the corresponding camera device does not respond. The request includes the time range of the required video segment and the corresponding camera device identifier. The request forwarding unit is used to send the auxiliary repair request to the area edge node to which the camera device belongs, so that the area edge node can retrieve and extract the corresponding complete video segment from its cache and send it back. The receiving execution unit is used to receive complete video segments transmitted from the edge nodes of the region and perform overlay replacement.

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