Illuminating lamp data transmission control method

Abstract

The invention is suitable for the technical field of data transmission, and provides an illumination lamp data transmission control method, which comprises the following steps of: acquiring data, state data and physiological health data by an illumination lamp; different priorities are set for each type of data, and different data are processed by adopting corresponding compression strategies; a multi-hop transmission ad hoc network is established between the lighting lamp and other nearby lighting lamps, and a network topology structure is dynamically adjusted; the lighting lamp evaluates an optimal sequence of various transmission paths transmitted to the monitoring center based on real-time information in the ad hoc network, and sets corresponding transmission paths and transmission strategies for different data according to priorities; the lighting lamp transmits the data with different priorities to the monitoring center hop by hop through a selected transmission path according to a set transmission strategy; and the monitoring center receives the data of the lighting lamps and carries out corresponding processing according to the priority of the data. According to the invention, the problems of stability, real-time performance and priority management of data transmission in an existing complex mine environment are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a lighting fixture data transmission control method. Background Art

[0002] In complex environments such as mines, lighting equipment not only undertakes lighting tasks, but also increasingly integrates data collection and transmission functions, such as monitoring environmental parameters (temperature, humidity, gas concentration, etc.), working status data (lighting equipment status, battery power, etc.) and physiological health data (miners' heart rate, body temperature, etc.). These data are crucial to ensure the safety of miners, and can provide real-time feedback to the monitoring center to help managers respond in a timely manner. However, mine environments usually have complex terrain and communication signal obstacles. Traditional wireless communication technologies are easily affected by interference, signal attenuation and other problems when used in mines, resulting in unstable data transmission and failure to guarantee the real-time and reliability of data.

[0003] At the same time, existing data transmission methods usually rely on fixed network architectures and often cannot flexibly adapt to the changing conditions in the mine environment, especially the frequent movement of miners at work, and it is difficult for fixed network nodes to achieve full coverage. Especially in deep mines or complex mine tunnel structures, the coverage and stability of the signal are seriously affected, resulting in the inability to guarantee the real-time and integrity of data transmission. At the same time, existing communication technologies are difficult to effectively adapt to the mobility of miners, and the switching and adaptive mechanisms of transmission links are relatively lagging, which can easily cause data loss or transmission delays. This problem makes it impossible for traditional data transmission methods to effectively cope with the challenges of complex mine environments.

[0004] In addition, the types and importance of data vary, and the impact and urgency of different types of data on the system also vary. Important data (such as physiological health data) may be delayed during data transmission, which reduces the system's emergency response capabilities and processing efficiency. Therefore, how to ensure the efficiency, reliability and real-time performance of important data during transmission is still an urgent problem to be solved. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a lighting fixture data transmission control method to fundamentally solve the problems of stability, real-time and priority management of data transmission in the complex environment of existing mines.

[0006] According to an embodiment of the present invention, a lighting fixture data transmission control method is provided, wherein the lighting fixture is connected and communicated with a receiving device worn by a user, and the method includes:

[0007] The lighting fixture collects environmental data of the current location, status data during operation, and receives and stores physiological health data collected by a receiving device worn by the user;

[0008] Different priorities are set for each type of data according to the characteristics of the collected data, and corresponding compression strategies are used to process different data according to the priorities, among which the priorities of physiological health data, environmental data, and status data are set in descending order;

[0009] Based on the Mesh network protocol, lighting fixtures automatically establish a multi-hop transmission ad hoc network with other nearby lighting fixtures, and dynamically adjust the network topology according to the lighting fixtures' geographical location, signal strength, mobility and load conditions;

[0010] The lighting fixture evaluates the preferred order of various transmission paths transmitted to the monitoring center in real time based on the real-time information in the ad hoc network, and sets corresponding transmission paths and transmission strategies for different data according to the priority. The real-time information includes signal strength, node load and hop count information.

[0011] The lighting fixture transmits data of different priorities to the monitoring center hop by hop through the transmission path selected in the ad hoc network according to the set transmission strategy;

[0012] The monitoring center receives data from lighting fixtures through the ad hoc network and processes the data accordingly based on its priority.

[0013] In addition, the lighting fixture data transmission control method according to the above embodiment of the present invention may also have the following additional technical features:

[0014] Furthermore, the step of processing different data using corresponding compression strategies according to priorities includes:

[0015] Lighting fixtures do not compress high-priority physiological health data;

[0016] Lighting fixtures use wavelet transform to perform multi-scale decomposition and moderate compression on medium-priority environmental data;

[0017] The lighting fixture utilizes wavelet transform to perform multi-scale decomposition and highly compress or uncompress low-priority status data.

[0018] Furthermore, the lighting fixture uses wavelet transform to perform multi-scale decomposition and moderate compression on the medium-priority environmental data, including:

[0019] Lighting fixtures pre-process medium-priority environmental data by filtering, denoising or mean smoothing;

[0020] The lighting fixture uses discrete wavelet transform to perform multi-scale decomposition on the pre-processed environmental data, decomposing the comprehensive data into low-frequency components and high-frequency components at different scales;

[0021] The lighting fixture performs threshold processing on the high-frequency components and removes coefficients below the preset threshold;

[0022] The lighting fixture recombines the processed low-frequency components and high-frequency components through inverse wavelet transform to generate compressed environmental data.

[0023] Furthermore, the step of automatically establishing a multi-hop transmission ad hoc network with other nearby lighting fixtures based on the Mesh network protocol includes:

[0024] After the lighting fixture is started, it automatically scans the network information of other lighting fixtures around it, and the network information includes geographical location, signal strength, and load status;

[0025] The lighting fixture broadcasts its own network information to other lighting fixtures around it;

[0026] The lighting fixtures select the best neighbor node based on the signal strength, load conditions and geographical location of each lighting fixture;

[0027] The lighting fixtures establish communication connections with the selected optimal neighbor nodes, exchange their respective information through the Mesh network protocol, and form a preliminary network topology structure;

[0028] The lighting fixture automatically selects the optimal transmission path according to the current network topology and its own geographical location, and establishes a multi-hop transmission connection with at least one neighboring node in the self-organizing network.

[0029] Furthermore, the step of dynamically adjusting the network topology according to the geographical location, signal strength, movement status and load condition of the lighting fixtures includes:

[0030] The lighting fixture automatically detects the signal strength and load of the neighboring nodes connected to it periodically or according to network changes;

[0031] Lighting fixtures determine the relative position relationship by monitoring the geographic location of themselves and neighboring nodes in real time;

[0032] The lighting fixtures evaluate the stability and transmission efficiency of the current network topology according to the signal strength, geographical location, mobility and load of each neighboring node;

[0033] When the network stability or transmission efficiency is lower than the preset threshold, the lighting fixture dynamically selects the best neighbor node according to the geographical location, signal strength and load of each neighbor node, and re-establishes the connection to adjust the network topology;

[0034] Lighting fixtures dynamically adjust their connection relationships with other nodes based on the signal strength, load conditions, and mobility status of each neighboring node;

[0035] The lighting fixture broadcasts the updated network topology information to the surrounding nodes to synchronously update the topology of the entire ad hoc network.

[0036] Furthermore, the step of the lighting fixture evaluating in real time the preferred order of various transmission paths transmitted to the monitoring center based on the real-time information in the ad hoc network includes:

[0037] The lighting fixture monitors the signal strength between it and each neighboring node in real time and evaluates the transmission quality of each path based on the signal strength;

[0038] Lighting fixtures evaluate the load of neighboring nodes connected to them in real time to determine the processing capacity and network pressure of each node;

[0039] The lighting fixture calculates the number of hops required for each path to reach the monitoring center based on the current network topology and evaluates the transmission efficiency of each path;

[0040] The lighting fixture comprehensively evaluates the comprehensive performance of each path based on the signal strength, load and hop count information of each neighboring node, and determines the preferred ranking of various transmission paths;

[0041] When network conditions change, lighting fixtures re-evaluate and update the preferred order of various transmission paths based on new signal strength, load conditions, and hop count information.

[0042] Furthermore, the step of setting corresponding transmission paths and transmission strategies for different data according to priorities includes:

[0043] Setting the transmission path of high-priority physiological health data as the optimal transmission path in the preferred sorting, and setting the transmission strategy as real-time transmission;

[0044] The transmission path of the medium-priority environmental data is set as the suboptimal transmission path in the preferred order, and the transmission strategy is set as scheduled transmission;

[0045] The transmission path of the low-priority status data is set as a non-critical transmission path in the preferred order, and the transmission strategy is set as delayed transmission or batch package transmission.

[0046] Furthermore, the step of transmitting the data of different priorities to the monitoring center hop by hop through the transmission path selected in the ad hoc network according to the set transmission strategy comprises:

[0047] The lighting fixture selects the optimal transmission path in the ad hoc network and uses a real-time transmission strategy to preferentially transmit high-priority physiological health data hop by hop to the monitoring center;

[0048] The lighting fixture selects the suboptimal transmission path in the ad hoc network and uses a timed transmission strategy to transmit the medium-priority environmental data hop by hop to the monitoring center;

[0049] The lighting fixtures select non-critical transmission paths in the ad hoc network and use delayed transmission or batch package transmission strategies to preferentially transmit low-priority status data hop by hop to the monitoring center.

[0050] Furthermore, the monitoring center receives data from the lighting fixtures through the ad hoc network and performs corresponding processing according to the priority of the data, including the following steps:

[0051] The monitoring center receives various data transmitted from the lighting fixtures through the ad hoc network;

[0052] The monitoring center determines the time for processing and analysis based on the priority of various data, and detects whether there are abnormal values ​​or abnormal data exceeding the preset threshold during processing and analysis;

[0053] When the monitoring center detects abnormal data, it automatically issues an alarm, locates the relevant lighting fixtures based on the abnormal data, and triggers corresponding emergency measures.

[0054] Furthermore, the step of locating the position of the relevant lighting fixture according to the abnormal data includes:

[0055] The monitoring center builds a complete network topology based on the node information of lighting fixtures in the self-organizing network and records the relative position and connection relationship of each node;

[0056] The monitoring center calculates the relative position of each lighting fixture based on the connection relationship of each lighting fixture in the network topology and identifies the distance and direction between related nodes;

[0057] The monitoring center calculates the absolute position of each lighting fixture based on the distance between nodes, relative position relationship and the position of known reference points;

[0058] The monitoring center regularly updates the network topology and lighting fixture locations, and dynamically adjusts the lighting fixture locations based on changes in the ad hoc network;

[0059] When the monitoring center detects abnormal data, the monitoring center determines the abnormal lighting fixture that caused the abnormality based on the identification information in the abnormal data;

[0060] The monitoring center locates the position of abnormal lighting fixtures based on the calculated position information of each lighting fixture.

[0061] The lighting fixture data transmission control method provided by the embodiment of the present invention establishes an ad hoc network by using the Mesh network protocol. The lighting fixture can automatically establish a multi-hop transmission network with other lighting fixtures around it to achieve reliable and stable data transmission. In the case of frequent node movement, the lighting fixture can dynamically adjust the network topology to maintain good communication quality. By setting different priorities (the priorities of physiological health data, environmental data, and status data are from high to low), it is ensured that high-priority key data (such as physiological health data) can be transmitted and processed in real time, while low-priority status data can be delayed or processed in batches, thereby improving the resource utilization efficiency of the lighting fixture and optimizing the overall transmission performance. By real-time evaluation of the signal strength, node load and Hop number information, lighting fixtures can select the optimal transmission path and strategy according to the data priority and real-time network conditions, avoiding bottlenecks in data transmission and improving the emergency response capability and stability of lighting fixtures; different compression strategies are adopted according to data of different priorities, and high-priority data (such as physiological health data) is not compressed to ensure its real-time transmission; and appropriate compression methods are used for medium and low priority data (such as environmental data, status data) to reduce bandwidth occupancy and improve data transmission efficiency; after receiving the data from the lighting fixtures, the monitoring center can analyze and process the data in a timely manner according to the priority of the data, thereby improving the real-time and accuracy of mine safety assurance; and solving the problems of stability, real-time and priority management of data transmission in the complex environment of existing mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a flow chart of a lighting fixture data transmission control method in a first embodiment of the present invention;

[0063] The following specific implementations will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0064] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0065] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0067] Embodiment 1

[0068] See also Figure 1 , which shows a lighting fixture data transmission control method in a first embodiment of the present invention. For the sake of convenience, only the parts related to the embodiment of the present invention are shown. The lighting fixture data transmission control method provided by the embodiment of the present invention includes:

[0069] Step S10, the lighting fixture collects environmental data of the current location, status data during operation, and receives and stores physiological health data collected by a receiving device worn on the user;

[0070] Among them, in one embodiment of the present invention, the method is applied to a lighting fixture, and the lighting fixture is connected and communicated with a receiving device worn on the user. Specifically, the receiving device is worn on the user and includes multiple sensors for collecting various physiological health data of the user, wherein the physiological health data includes but is not limited to heart rate, blood oxygen saturation, body temperature, blood pressure, electrocardiogram, etc. At this time, the physiological health data collected by its receiving device can be any one or more combinations of heart rate, blood oxygen saturation, body temperature, blood pressure, and electrocardiogram, which is determined according to the type of sensor actually set by the receiving device, and is not specifically limited here. Among them, the receiving device can be a wearable device such as a smart bracelet, a smart watch, a chest strap, a helmet, etc., which is set according to actual use needs, and is not specifically limited here. At this time, the data collected by each sensor in the receiving device is preliminarily processed by the built-in processing unit to obtain various physiological health data, and is transmitted to the lighting fixture through a wireless communication module (such as a Bluetooth module, a LoRa module, a Zigbee module, a WiFi module, etc.). Therefore, the communication module in the lighting fixture can receive and store various physiological health data collected by the receiving device connected to the communication in real time, and save the physiological health data at each time point for subsequent processing and judgment. Of course, optionally, the receiving device and the lighting fixture can also be connected and communicated through wired communication, which is specifically set according to actual use needs and is not specifically limited here.

[0071] Furthermore, in one embodiment of the present invention, various sensors are provided on the lighting fixtures for collecting data, including but not limited to light sensors, temperature sensors, humidity sensors, dust concentration sensors, and combustible gas sensors. Therefore, the above sensors can detect the environmental parameters of the current location, such as light intensity, temperature, humidity, dust concentration and combustible gas concentration.

[0072] Furthermore, in one embodiment of the present invention, various sensors are provided in the lighting fixture to collect status data of the lighting fixture when it is working, wherein the status data includes but is not limited to battery status, node temperature, communication quality information, node load information, operation log, network status and location status, wherein the battery status is a key factor affecting the operating time of the lighting fixture and the availability of network nodes; the node temperature can reflect the health status of the lighting fixture, such as overheating due to long-term operation may cause equipment failure; the communication quality information includes the signal quality of the node (such as signal strength RSSI) and the communication status with neighboring nodes, which is used to evaluate whether the current network is stable or whether the transmission path needs to be adjusted; the node load information is the amount of data processed by the lighting fixture or the number of relay tasks; the operation log is the operation record of the lighting fixture, such as whether the lighting fixture is abnormally restarted, the software update status, etc.; the network status is the network connection status of the lighting fixture, such as how many neighboring nodes are connected, the health status of the communication link, etc.; the location status is used to locate the position and movement status of the lighting fixture.

[0073] Step S20, setting different priorities for each type of data according to the characteristics of the collected data, and using corresponding compression strategies to process different data according to the priorities, wherein the priorities of physiological health data, environmental data, and status data are set to be sorted in descending order;

[0074] Among them, in one embodiment of the present invention, all data collected by the lighting fixture are classified. Common data types include physiological health data, environmental data and status data. Each data has different characteristics and importance. Specifically, physiological health data (such as heart rate, blood oxygen concentration, body temperature, etc.) is usually key information for monitoring the health status of users, so it has a higher priority. Environmental data (such as temperature and humidity, gas concentration, etc.) affects the safety of miners and belongs to medium priority data. It needs to be transmitted in time, but the urgency is slightly lower than that of physiological health data. Status data (such as the working status of lighting fixtures, battery power, etc.) is important for the normal operation of the system, but it can usually be transmitted at a lower priority, and delayed transmission will not affect real-time safety. Therefore, different priorities are set for each data according to the characteristics of the collected data. At this time, the priorities of physiological health data, environmental data, and status data are set to be sorted from high to low, that is, physiological health data is set to high priority, environmental data is set to medium priority, and status data is set to low priority.

[0075] Further, different data are processed using corresponding compression strategies according to the priority, which includes the following specific steps:

[0076] Lighting fixtures do not compress high-priority physiological health data;

[0077] Lighting fixtures use wavelet transform to perform multi-scale decomposition and moderate compression on medium-priority environmental data;

[0078] The lighting fixture utilizes wavelet transform to perform multi-scale decomposition and highly compress or uncompress low-priority status data.

[0079] Specifically, lighting fixtures do not compress high-priority physiological health data. Specifically, high-priority data (such as heart rate, body temperature and other physiological health data of miners) is closely related to the life safety of miners and has extremely high real-time requirements. Although compression processing can reduce the amount of data, it will bring certain processing delays and data loss risks. Therefore, direct transmission can maximize the timeliness of data and ensure that the monitoring center can obtain and respond to these data as quickly as possible. At the same time, generally speaking, the single collection volume of physiological health data will not be particularly large (for example, heart rate and body temperature are usually simple numerical values), and the size of the data packet is small. Therefore, even without compression, the network burden of direct transmission will not be very large. In contrast, real-time is more critical. Furthermore, any compression algorithm may cause a certain degree of distortion or information loss. For physiological health data, this distortion may affect the judgment of the health status of miners, so it is more inclined not to compress such data in the transmission to ensure the integrity and accuracy of the data.

[0080] Furthermore, the lighting fixture uses wavelet transform to perform multi-scale decomposition and moderate compression on the medium-priority environmental data, wherein wavelet transform is a mathematical tool for converting data from the time domain to the frequency domain, and can analyze the local characteristics of the signal in both the time domain and the frequency domain. Compared with other common data compression methods (such as Fourier transform or standard lossless compression algorithm), wavelet transform can effectively reduce redundant information while maintaining data integrity. The lighting fixture uses wavelet transform to perform multi-scale decomposition and moderate compression on the medium-priority environmental data, and the specific steps include:

[0081] Lighting fixtures pre-process medium-priority environmental data by filtering, denoising or mean smoothing;

[0082] The lighting fixture uses discrete wavelet transform to perform multi-scale decomposition on the pre-processed environmental data, decomposing the comprehensive data into low-frequency components and high-frequency components at different scales;

[0083] The lighting fixture performs threshold processing on the high-frequency components and removes coefficients below the preset threshold;

[0084] The lighting fixture recombines the processed low-frequency components and high-frequency components through inverse wavelet transform to generate compressed environmental data.

[0085] Specifically, before performing wavelet transform on the data, the environmental data needs to be preprocessed to remove noise or smooth the data. The lighting fixture can apply a low-pass filter or a Gaussian filter to remove high-frequency noise in the data. The low-pass filter can retain the low-frequency part of the signal and reduce the impact of burst noise. Alternatively, the lighting fixture can perform sliding window processing on the data to replace each data point with the average of its neighboring data points to achieve the purpose of smoothing the data. Its preprocessing helps to reduce the volatility of the data, making the subsequent wavelet transform more accurate.

[0086] Furthermore, on the pre-processed environmental data, the discrete wavelet transform (DWT) is used to perform multi-scale decomposition on the environmental data. The discrete wavelet transform usually selects an appropriate wavelet basis function for decomposition, among which common wavelet basis functions include Haar wavelet, Daubechies wavelet, etc. The lighting fixture divides the environmental data into low-frequency components and high-frequency components of different scales through multi-scale decomposition. Each level of wavelet decomposition will divide the data into low-frequency components (approximate coefficients) and high-frequency components (detail coefficients). The low-frequency component reflects the overall trend or smooth part of the data and is suitable for describing the main characteristics of the data. The high-frequency component contains local detail information of the data, such as sudden changes, noise, etc. At this time, the decomposition process will continue recursively, and the low-frequency component will be decomposed again until the required decomposition level is reached. For example, if decomposed into 3 layers, the comprehensive data will be decomposed into 3 low-frequency components of different scales and 3 corresponding high-frequency components. Specifically, the discrete wavelet transform (DWT) uses two types of filters, low-pass filters and high-pass filters, to process the signal. The low-pass filter retains the low-frequency part of the signal (i.e., the smooth feature) and generates the approximate coefficient by downsampling. The high-pass filter extracts the high-frequency part of the signal (i.e., details with dramatic changes) and generates detail coefficients through downsampling. The specific operation is to convolve the input signal with the filter and downsample the result (usually a multiple of 2), where the purpose of downsampling is to reduce the amount of data while maintaining the main characteristics of the signal. At this time, the signal is gradually decomposed into low-frequency components and high-frequency components by filtering and downsampling the signal multiple times. Each decomposition will perform the next round of filtering and downsampling on the low-frequency components until the signal is decomposed into frequency components of multiple scales (i.e., approximation coefficients and detail coefficients at different levels).

[0087] Furthermore, high-frequency components usually contain noise and unimportant details, so threshold processing is needed to remove unnecessary information. Specifically, lighting fixtures screen high-frequency components according to a preset threshold (such as a fixed threshold or an adaptive threshold, common methods include soft threshold processing and hard threshold processing), where coefficients below the threshold are regarded as noise or unimportant information. Among them, hard threshold processing directly sets the high-frequency coefficients below the threshold to zero, while the coefficients greater than the threshold remain unchanged. Soft threshold processing sets the coefficients below the threshold to zero, and at the same time subtracts the threshold from the coefficients greater than the threshold to make it smoother. Its soft threshold processing can reduce the "oscillation" phenomenon during reconstruction and ensure the continuity of the data. At this time, the high-frequency components after threshold processing will be greatly simplified, effectively removing smaller noise components, removing unnecessary details, and retaining high-frequency details that have a greater impact on the signal, thereby achieving the effect of data compression.

[0088] Further, after the high-frequency component is threshold processed, the lighting fixture will recombine the low-frequency component and the processed high-frequency component. The specific step is to gradually recombine the low-frequency and high-frequency components of each scale through inverse discrete wavelet transform to reconstruct the compressed environmental data. Specifically, the process of inverse wavelet transform is to upsample the detail coefficients and approximate coefficients of each layer, and recombine the signal through low-pass filter and high-pass filter. The inverse transform step is to upsample the detail coefficients after threshold processing and the unprocessed approximate coefficients (by inserting zeros between the data) to restore them to the same length as the previous layer. The upsampled signal is filtered using the filter opposite to that during decomposition, and the approximate coefficients and detail coefficients of each layer are merged. This process is repeated until the length of the original signal is restored. Since the irrelevant information in the high-frequency component is removed, the compressed data has a lower redundancy, and the low-frequency part of the data retains more original information. Therefore, the compressed data retains the main information while greatly reducing the amount of data. Therefore, wavelet transform can effectively compress a large amount of data without losing key information, and is suitable for self-organizing networks with limited bandwidth.

[0089] Furthermore, wavelet compression is performed on medium-priority environmental data for the following reasons. First, environmental data (such as temperature, humidity, gas concentration, etc.) are usually collected continuously, and the data volume may be large. In order to reduce network burden and transmission delay, compressing such data is very effective. Second, although environmental data is important, it does not require extremely high real-time performance like high-priority physiological health data. The compression method of wavelet transform can meet medium transmission requirements while ensuring data integrity and compression effect. Third, wavelet transform is particularly suitable for multi-scale signal decomposition, which can compress such numerical data well while retaining important information features. While removing high-frequency noise, environmental data can retain key data to ensure the data analysis effect after transmission. By comparing the size of the original data and the compressed data, the lighting fixture can evaluate the compression ratio in real time to ensure the storage efficiency after data compression. Since the amount of compressed data is small, the bandwidth demand and transmission delay during transmission can be reduced, especially when multi-node transmission is performed through an ad hoc network, the compressed data transmission is more efficient. Furthermore, the wavelet transform can provide both time domain and frequency domain information of the signal, and can capture transient changes and local features in the signal, which is particularly suitable for sudden fluctuations in data in the mine environment (such as sudden changes in environmental data), so that the wavelet transform can effectively compress unimportant detail data while retaining key information. At the same time, the mine environment is complex, and the signal is easily interfered by noise. The multi-scale analysis characteristics of the wavelet transform enable it to effectively separate the different frequency components of the signal, allowing the data to be analyzed at different scales, which is particularly suitable for processing sensor data mixed with high-frequency noise and low-frequency important information. At the same time, the compression process has its own denoising function, thereby improving data quality. At the same time, compared with the Fourier transform, which can only process periodic signals, the wavelet transform is more suitable for processing non-stationary signals (such as irregular environmental parameters in mines), making it perform better in mine sensor data compression. At the same time, because the wavelet transform can effectively remove redundant information and noise while maintaining the main characteristics of the signal, it can achieve a higher compression ratio while ensuring high data fidelity. For a large amount of sensor data that needs to be transmitted frequently, it can significantly reduce the transmission load and improve network transmission efficiency.

[0090] Furthermore, the lighting fixture uses wavelet transform to perform multi-scale decomposition and high compression on low-priority status data, or does not perform compression processing. The lighting fixture uses wavelet transform to perform multi-scale decomposition and high compression on low-priority status data, which can refer to the above-mentioned compression processing of medium-priority environmental data, and will not be repeated here. The difference between medium compression and high compression lies in threshold processing. For medium compression, it can perform low-threshold processing on high-frequency coefficients to remove most of the tiny, high-frequency noise; and for high compression, it can perform high-threshold processing on high-frequency coefficients to largely discard low-frequency and part of high-frequency information.

[0091] At the same time, the lighting fixtures may not compress the low-priority status data. The main reason is that the low-priority status data is relatively small, and this type of data is collected regularly and the data volume is small. If these data are compressed, the effect of compression may not be obvious, but it will increase the processing complexity and delay. At the same time, this type of data has a very low requirement for transmission delay and allows a longer transmission time. Therefore, there is no need to occupy more computing resources for compression, and it can be directly transmitted at the appropriate time through the self-organizing network. At the same time, since the transmission requirements of low-priority status data are low, if it is compressed, it may cause unnecessary computing overhead and waste computing resources. It is simpler and more efficient to directly transmit such a small amount of data.

[0092] Step S30, the lighting fixture automatically establishes a multi-hop transmission ad hoc network with other nearby lighting fixtures based on the Mesh network protocol, and dynamically adjusts the network topology according to the geographical location, signal strength, mobility and load of the lighting fixture;

[0093] In one embodiment of the present invention, each lighting fixture is equipped with a wireless communication module (such as a LoRa module, a Zigbee module or a low-power Bluetooth module) to support self-organizing network communication with other nearby lighting fixtures based on the Mesh network protocol. The lighting fixtures use the wireless communication module to perform wireless communication between nodes to form a multi-node self-organizing network (Meshnetwork). The core of the self-organizing network lies in its multi-hop transmission mechanism, that is, data can be transmitted from one node to another until it finally reaches the target node (such as a monitoring center). Even if the direct connection is disconnected, the data can still be relayed through other lighting fixture nodes.

[0094] Specifically, the steps of the lighting fixture automatically establishing a multi-hop transmission ad hoc network with other nearby lighting fixtures based on the Mesh network protocol include:

[0095] After the lighting fixture is started, it automatically scans the network information of other lighting fixtures around it, and the network information includes geographical location, signal strength, and load status;

[0096] The lighting fixture broadcasts its own network information to other lighting fixtures around it;

[0097] The lighting fixtures select the best neighbor node based on the signal strength, load conditions and geographical location of each lighting fixture;

[0098] The lighting fixtures establish communication connections with the selected optimal neighbor nodes, exchange their respective information through the Mesh network protocol, and form a preliminary network topology structure;

[0099] The lighting fixture automatically selects the optimal transmission path according to the current network topology and its own geographical location, and establishes a multi-hop transmission connection with at least one neighboring node in the self-organizing network.

[0100] Specifically, when the lighting fixture is started, the built-in wireless communication module will be initialized and enter the scanning mode to listen to the network information broadcast by other lighting fixtures around. The lighting fixture will continuously listen to the broadcast frames (Beacon), which contain the network information of other lighting fixtures, wherein the network information includes the geographical location, signal strength (RSSI), and load conditions, wherein the geographical location is the geographical location information located by the coordinate position preset during installation or based on the GPS module of the lighting fixture. The signal strength is used to judge the communication quality of the neighboring nodes according to the strength indication of the wireless signal. The load condition is used to indicate the network load condition of each lighting fixture, such as the number of processing tasks, the bandwidth occupied by data transmission, etc. After the lighting fixture is started and completes the scanning of the surrounding network information, the lighting fixture needs to broadcast its own network information for use by other lighting fixtures. After receiving the network information from other lighting fixtures, the lighting fixture needs to calculate and evaluate according to the signal strength, load condition and geographical location of each lighting fixture to select the optimal neighbor node. Specifically, the signal strength of each neighbor node received by the lighting fixture is an important parameter to determine the communication quality. The signal strength can be measured by the RSSI value of the wireless communication module, where a stronger signal usually indicates a more reliable communication link. The lighting fixture evaluates the distance to neighboring nodes by comparing the geographic coordinates, where nodes that are closer are more likely to be the preferred path. The lighting fixture compares the load of each neighboring node (such as the amount of data currently being processed, CPU load, etc.) and selects the neighboring node with a lighter load to avoid congestion and delay. At this time, the weighted value of each neighboring node is obtained by weighting the signal strength, load and geographic location with different weight factors, and finally the optimal neighboring node is determined. When the lighting fixture selects the optimal neighboring node, it establishes a communication connection with the node through the Mesh network protocol. At this time, the lighting fixture sends a connection request packet (Connection Request) to the optimal neighboring node, and the neighboring node responds with an acknowledgement packet (Acknowledgement) to complete the connection establishment. After the connection is established, the two lighting fixtures exchange more detailed information through the Mesh network protocol, such as the connection stability between nodes, information on the data transmission path, and the topology of other neighboring nodes. When the lighting fixture establishes communication connections with multiple neighboring nodes, the preliminary Mesh network topology begins to take shape. At this time, each node will upload its own information and the information of its connected neighboring nodes to the self-organizing network, gradually forming a complete network topology structure in a local area. At this time, the lighting fixture constantly monitors the network status of the surrounding nodes and uses the broadcast mechanism of network information to obtain the latest node status in real time. Before each communication, the transmission path is recalculated based on the real-time status of the current network to ensure the selection of the optimal path. After the lighting fixture selects the optimal transmission path, it will establish a multi-hop transmission connection with one or more neighboring nodes.

[0101] Furthermore, the above-mentioned step of dynamically adjusting the network topology structure according to the geographical location, signal strength, movement status and load condition of the lighting fixtures includes:

[0102] The lighting fixture automatically detects the signal strength and load of the neighboring nodes connected to it periodically or according to network changes;

[0103] Lighting fixtures determine the relative position relationship by monitoring the geographic location of themselves and neighboring nodes in real time;

[0104] The lighting fixtures evaluate the stability and transmission efficiency of the current network topology according to the signal strength, geographical location, mobility and load of each neighboring node;

[0105] When the network stability or transmission efficiency is lower than the preset threshold, the lighting fixture dynamically selects the best neighbor node according to the geographical location, signal strength and load of each neighbor node, and re-establishes the connection to adjust the network topology;

[0106] Lighting fixtures dynamically adjust their connection relationships with other nodes based on the signal strength, load conditions, and mobility status of each neighboring node;

[0107] The lighting fixture broadcasts the updated network topology information to the surrounding nodes to synchronously update the topology of the entire ad hoc network.

[0108] Specifically, lighting fixtures need to automatically evaluate the connection quality with neighboring nodes periodically or when network changes are detected. Specifically, the wireless communication module of the lighting fixture sets a scheduled task (such as every 10 seconds) to send a probe signal (Probe) or receive a broadcast frame from a neighboring node to obtain the current signal strength (RSSI) and other node load conditions in real time. At this time, each lighting fixture measures its own CPU utilization, data transmission bandwidth occupancy and other parameters, and includes this information in the broadcast network information packet. After receiving the network information packet, other nodes can obtain the real-time load status of neighboring nodes. Each lighting fixture reflects the stability of the communication link in real time by detecting wireless signal quality indicators such as RSSI value or link quality indication (LQI). When the signal strength drops significantly, the corresponding adjustment mechanism is triggered.

[0109] Furthermore, lighting fixtures monitor their geographic location and relative position relationship in real time. In order to accurately evaluate the relative position relationship, each lighting fixture needs to have location awareness. This can be achieved in the following ways: Method 1 is to regularly obtain its own geographic location information through the built-in GPS module. Method 2 is to obtain relative position information through signal triangulation of fixed nodes such as base stations and routers. Method 3 is for each lighting fixture to regularly broadcast its own geographic location information and receive the geographic location of neighboring nodes in real time. Combined with its mobile status (such as real-time data from an accelerometer or GPS), the change in relative position can be inferred.

[0110] Furthermore, the lighting fixture evaluates the stability and transmission efficiency of the current network topology according to the signal strength, geographical location, mobile status and load of each neighboring node. The communication quality of the current link is judged by regularly measuring the RSSI value with the neighboring node. The stronger the signal strength, the more stable the link. The transmission efficiency is evaluated by tracking the transmission time and packet loss rate of the data packet. The lighting fixture can record the delay information of multiple communications and judge the availability of the current link in combination with the load of the neighboring node. If the geographical location of a neighboring node changes, or its mobile status shows that the node is far away, it will affect the long-term stability of the network. Based on the above factors, the lighting fixture can predict the potential risks of the topology.

[0111] Furthermore, when the lighting fixture detects that the network stability or transmission efficiency is lower than a preset threshold, it is necessary to automatically select a new neighbor node and adjust the topology. Specifically, a set of thresholds are preset, including the lower limit of signal strength, the upper limit of transmission delay, the upper limit of load, etc. Once the parameters of a link exceed these thresholds, the process of reselecting neighbor nodes is triggered. The lighting fixture recalculates the optimal connection node based on the signal strength, load condition, geographical location and other parameters of the surrounding neighbor nodes. Commonly used selection algorithms include the shortest path calculation based on the Dijkstra algorithm and the load balancing algorithm. The shortest path calculation based on the Dijkstra algorithm selects the path with the least hops and the best communication quality by analyzing the links between nodes in the entire topology; and the load balancing algorithm gives priority to nodes with lighter loads and stronger signals to reduce network congestion and transmission delays. Once the new neighbor node is determined, the lighting fixture reconnects with it through the Mesh protocol and updates the transmission path.

[0112] Furthermore, as neighboring nodes and topology structures change dynamically, lighting fixtures need to adjust their connection relationships with other nodes in real time. If the current connection link is no longer stable (such as signal weakening or load increase), the lighting fixture can lower the priority of the link and give priority to the new stable path. For links that no longer meet the transmission conditions, the lighting fixture can actively disconnect and establish a more suitable connection based on the new network status. The lighting fixture can also actively adjust the connection strategy through scheduled tasks (such as every few minutes) or according to changes in node status to ensure network stability.

[0113] Furthermore, when the topology of the lighting fixture changes, the updated network topology information needs to be broadcast to other nodes to ensure that the entire self-organizing network maintains consistent topology information. Specifically, the lighting fixture packages the newly selected neighbor nodes, signal strength, geographic location information, and load conditions into network update information. The lighting fixture then uses the broadcast mechanism of the Mesh protocol to send this update information to the surrounding neighbor nodes. After receiving it, these neighbor nodes will update their own network topology and further propagate the updated information to other nodes until the entire network is synchronized. At the same time, the lighting fixture can confirm that the update information has been successfully received and processed by receiving feedback messages (ACK) from neighbor nodes. If some nodes are not updated in time, the network can continue to send broadcasts to ensure the consistency of topology information.

[0114] Step S40, the lighting fixture evaluates the preferred order of various transmission paths transmitted to the monitoring center in real time based on the real-time information in the ad hoc network, and sets corresponding transmission paths and transmission strategies for different data according to the priority, wherein the real-time information includes signal strength, node load and hop count information;

[0115] In one embodiment of the present invention, the step of evaluating in real time the preferred order of various transmission paths transmitted to the monitoring center by the lighting fixture based on the real-time information in the ad hoc network includes:

[0116] The lighting fixture monitors the signal strength between it and each neighboring node in real time and evaluates the transmission quality of each path based on the signal strength;

[0117] Lighting fixtures evaluate the load of neighboring nodes connected to them in real time to determine the processing capacity and network pressure of each node;

[0118] The lighting fixture calculates the number of hops required for each path to reach the monitoring center based on the current network topology and evaluates the transmission efficiency of each path;

[0119] The lighting fixture comprehensively evaluates the comprehensive performance of each path based on the signal strength, load and hop count information of each neighboring node, and determines the preferred ranking of various transmission paths;

[0120] When network conditions change, lighting fixtures re-evaluate and update the preferred order of various transmission paths based on new signal strength, load conditions, and hop count information.

[0121] Specifically, each lighting fixture detects the signal strength of the surrounding neighboring nodes periodically or during communication. The collected signal strength data is used to dynamically evaluate the communication quality between neighboring nodes. The higher the signal strength, the better the quality of data transmission and the lower the packet loss rate. Furthermore, each lighting fixture should not only pay attention to the signal strength, but also need to understand the load of neighboring nodes in real time. The load includes the current processing capacity of the node (such as CPU usage) and the usage of communication bandwidth. At this time, the lighting fixture obtains the load information of each node by regularly querying the status of neighboring nodes. The load information can be collected through heartbeat packets or status data. The processing capacity of nodes with higher loads may be limited, and data transmission may be delayed or failed, so nodes with lower loads are more suitable as relay nodes on the transmission path. Furthermore, the lighting fixture calculates the number of hops required for each path to the monitoring center according to the current network topology. Specifically, the routing algorithm of the self-organizing network, such as AODV (on-demand distance vector routing protocol) or Dijkstra algorithm, is used to calculate the number of hops for each possible path. The number of hops is an important parameter for path optimization. Reducing the number of hops can reduce the delay of data transmission and increase the transmission speed. Furthermore, by comprehensively considering the signal strength, load condition and number of hops, the lighting fixture can use a weighted algorithm to evaluate the comprehensive transmission performance of each path. Specifically, the weights of various parameters (signal strength, load condition, number of hops) are set, and the scores of the paths are calculated. At this time, the lighting fixture comprehensively evaluates the pros and cons of each path, and determines the preferred ranking of various transmission paths based on the scores. The weight values ​​can be dynamically adjusted according to the actual needs of the current network, such as increasing the load weight when the node load is large, or increasing the signal strength weight when the signal fluctuates greatly. Furthermore, when network conditions change, the lighting fixture adjusts the preferred ranking of various transmission paths in real time. Changes in network conditions may include fluctuations in the signal strength of neighboring nodes, increases and decreases in load, or changes in network topology (such as some nodes being offline). Specifically, the lighting fixture recalculates the comprehensive scores of each path periodically or when it senses changes in network conditions (such as decreased signal strength, increased node load).

[0122] Furthermore, the above step of setting corresponding transmission paths and transmission strategies for different data according to priorities includes:

[0123] Setting the transmission path of high-priority physiological health data as the optimal transmission path in the preferred sorting, and setting the transmission strategy as real-time transmission;

[0124] The transmission path of the medium-priority environmental data is set as the suboptimal transmission path in the preferred order, and the transmission strategy is set as scheduled transmission;

[0125] The transmission path of the low-priority status data is set as a non-critical transmission path in the preferred order, and the transmission strategy is set as delayed transmission or batch package transmission.

[0126] Specifically, for high-priority physiological health data, the optimal path is dynamically selected through the self-organizing network, and real-time transmission is performed with the lowest delay. Ensuring that the data can be quickly and reliably transmitted to the monitoring center when network conditions permit, and timely responding to possible security incidents, helps to ensure the timely transmission of emergency data and optimize the use of bandwidth. It should be pointed out that if the optimal transmission path is blocked, the lighting fixture automatically reselects the backup path to ensure the reliability of transmission. For medium-priority environmental data, when the network load is moderate, it is transmitted according to the predetermined time window to ensure a certain degree of real-time performance, but it will not occupy too much network bandwidth. Its transmission may be a fixed periodic transmission or a timed transmission triggered on demand to avoid excessive occupation of network resources. For low-priority status data, delayed transmission or batch transmission is used to delay transmission when the network load is heavy or in non-emergency situations, or multiple status data are merged and batched when the network load is low. It can ensure that low-priority data does not occupy too much network bandwidth, reduce network load, ensure the reasonable allocation of network resources, and optimize the use of overall network resources. At the same time, by selecting the transmission paths for different data through preferential sorting, network resources can be dynamically adjusted to ensure that high-priority data obtains the optimal transmission path, while low-priority data is flexibly scheduled according to network conditions, which helps reduce network congestion and data transmission delays.

[0127] Step S50, the lighting fixture transmits the data of different priorities to the monitoring center hop by hop through the transmission path selected in the ad hoc network according to the set transmission strategy;

[0128] In one embodiment of the present invention, the lighting fixture allocates different data to respective set transmission paths according to priority, and transmits the data hop by hop to the monitoring center through the multi-hop mechanism in the ad hoc network according to various set transmission strategies. Specifically, the implementation steps include:

[0129] The lighting fixture selects the optimal transmission path in the ad hoc network and uses a real-time transmission strategy to preferentially transmit high-priority physiological health data hop by hop to the monitoring center;

[0130] The lighting fixture selects the suboptimal transmission path in the ad hoc network and uses a timed transmission strategy to transmit the medium-priority environmental data hop by hop to the monitoring center;

[0131] The lighting fixtures select non-critical transmission paths in the ad hoc network and use delayed transmission or batch package transmission strategies to preferentially transmit low-priority status data hop by hop to the monitoring center.

[0132] It should be pointed out that before data transmission, the lighting fixtures package various data separately and convert them into a data packet format suitable for network transmission, where the data packet usually includes a data header, data content, checksum, etc. The data header contains necessary metadata, such as source node ID (lighting fixture), target node ID (monitoring center), data packet sequence number and other information to ensure the correct identification and sorting of data in the network.

[0133] Furthermore, each lighting fixture is used as a node, and the Mesh network protocol is used to implement hop-by-hop transmission. The lighting fixtures allocate different data to their own set transmission paths according to priority, and send the data to neighboring nodes. After receiving the data, the intermediate node checks the target node information in its data header, confirms its next hop destination, and then forwards the data packet to the next node.

[0134] Furthermore, each intermediate node that receives data checks the status of the current transmission path and decides whether to continue forwarding data along the established path, or dynamically adjust the path to adapt to the new network environment. Specifically, when an intermediate node receives a data packet, it first reads the destination address of the data packet to see if the data packet needs to be passed to the next hop node. Or if the network status of the current neighbor node changes (such as decreased signal strength, increased load), the node will dynamically adjust the path based on the real-time evaluation results and select a new neighbor node for forwarding.

[0135] Furthermore, when the data packet finally reaches the monitoring center, the monitoring center node identifies the source through the information in the packet header and reassembles the packet. If a packet is lost or erroneous during transmission, the monitoring center can detect the lost part through the packet sequence number and initiate a retransmission request.

[0136] Among them, during the hop-by-hop data transmission process, the network may be affected by signal interference, node failure and other problems, so it is necessary to implement an error detection and retransmission mechanism to ensure the integrity and reliability of the data. When receiving data, each specific node will check the integrity of the data through the checksum in the data packet. If data corruption or packet loss is found, the node will request the upstream node to resend the data packet. If a serious error or interruption occurs in a transmission path, the lighting fixture will re-evaluate the network status and select a new path for data transmission to ensure that the data can finally reach the monitoring center successfully.

[0137] Step S60, the monitoring center receives data from the lighting fixtures through the ad hoc network and performs corresponding processing according to the priority of the data;

[0138] In one embodiment of the present invention, the monitoring center receives data from lighting fixtures through an ad hoc network, and performs corresponding processing according to the priority of the data, including:

[0139] The monitoring center receives various data transmitted from the lighting fixtures through the ad hoc network;

[0140] The monitoring center determines the time for processing and analysis based on the priority of various data, and detects whether there are abnormal values ​​or abnormal data exceeding the preset threshold during processing and analysis;

[0141] When the monitoring center detects abnormal data, it automatically issues an alarm, locates the relevant lighting fixtures based on the abnormal data, and triggers corresponding emergency measures.

[0142] Specifically, each lighting fixture in the ad hoc network transmits data to the monitoring center hop by hop through the selected path. The monitoring center receives data packets from multiple lighting fixtures from different transmission paths. The monitoring center identifies the data packets through the metadata in the data packet header (such as the source lighting fixture ID, data packet sequence number, and timestamp). The monitoring center parses the received data to obtain various data. When parsing the data, the monitoring center stores and archives different categories of data according to the data type and the ID information of the source node, in preparation for subsequent analysis.

[0143] Furthermore, the monitoring center conducts real-time comprehensive evaluation and processing of various received data, and determines the time for processing and analysis according to the priority of various data. Specifically, high-priority physiological health data is processed in real time; medium-priority environmental data is processed routinely; and low-priority status data is processed in batches or delayed to ensure that the processing process meets the actual application requirements. Further, when processing and analyzing each data, it is detected whether there is an abnormal situation. The monitoring center pre-sets a series of thresholds or rules to determine the normal range of different types of data. For example, the reasonable range of temperature, humidity, and air quality, the normal working power range of lighting fixtures, or the normal values ​​of users' health indicators (heart rate, blood pressure, etc.). The monitoring center conducts real-time monitoring by continuously analyzing various types of data. If the data is detected to be beyond the normal range or abnormal fluctuations, such as abnormal increase in lighting fixture power consumption, excessively high ambient temperature, or abnormal user physiological indicators, the monitoring center marks these data as abnormal data. The analysis process of different data sources (environment, status, health) can be independent, or a multi-dimensional comprehensive evaluation can be performed through a machine learning model. For example, by analyzing the association between health data and environmental data, it can be determined whether the user's health indicators are abnormal due to a bad environment (such as high temperature). At this time, through real-time monitoring, the monitoring center can use various algorithms (such as threshold detection, trend analysis, and abnormal point detection algorithms) to determine whether the data is abnormal. Among them, threshold detection is that the monitoring center sets multiple preset thresholds for environmental data, equipment status data, and physiological health data. When the data exceeds these thresholds, it is considered to be abnormal. For example, when the temperature exceeds a certain set value or the working voltage of the lighting fixture is unstable, the monitoring center triggers an abnormal alarm. Trend analysis is to analyze the trend of data changes over time. The monitoring center can detect that even if the data is temporarily in the normal range, if some data has a trend of continuous increase or decrease, it can also issue an early warning. Abnormal point detection is to use statistical methods or machine learning technology to model historical data. The monitoring center can detect whether certain data points deviate significantly from the normal mode, and then determine whether it is an abnormal situation.

[0144] Furthermore, when the monitoring center detects abnormal data, it automatically issues an alarm and notifies relevant personnel or systems to handle it. Specifically, the monitoring center will issue a high-decibel sound alarm, and detailed information about the abnormal miner or abnormal area (such as miner ID, location, abnormal type, etc.) will be displayed on the screen. The monitoring center records the abnormal data in a log and generates detailed alarm information, including the type of abnormal data, value, cause of the abnormality (such as exceeding the threshold or trend abnormality), source node, etc. At the same time, through the preset alarm mechanism, the monitoring center will automatically send notifications to operators, such as text messages, emails, or application push, to notify mine managers, rescue teams, and relevant safety managers to ensure that relevant personnel can respond in a timely manner.

[0145] Furthermore, based on the source node information contained in the abnormal data, the monitoring center can quickly locate the location where the abnormality occurred and determine which lighting fixture or area needs special attention. The abnormal data contains the unique ID and geographic location data of the lighting fixture. The monitoring center uses this information to find the specific location of the lighting fixture in the network topology map.

[0146] Furthermore, when abnormal data is detected and an alarm is issued, the monitoring center can automatically trigger preset emergency measures according to the type of abnormality. For equipment abnormalities, such as overload or failure of lighting fixtures, the monitoring center can automatically switch to backup equipment or reduce the load to prevent accidents. For environmental abnormalities, such as excessive temperature or deterioration of air quality, the monitoring center can automatically adjust the air conditioning or ventilation system, or shut down the power system in a specific area, or issue an emergency evacuation notice to prevent the accident from further expanding. For user health abnormalities, such as abnormal heart rate and blood pressure, the monitoring center can notify nearby medical personnel or initiate emergency rescue measures, and provide them with the specific location of the abnormal lighting fixtures and the health status of the users who use them, so that the rescue team can take quick action.

[0147] Furthermore, the step of locating the position of the relevant lighting fixture according to the abnormal data includes:

[0148] The monitoring center builds a complete network topology based on the node information of lighting fixtures in the self-organizing network and records the relative position and connection relationship of each node;

[0149] The monitoring center calculates the relative position of each lighting fixture based on the connection relationship of each lighting fixture in the network topology and identifies the distance and direction between related nodes;

[0150] The monitoring center calculates the absolute position of each lighting fixture based on the distance between nodes, relative position relationship and the position of known reference points;

[0151] The monitoring center regularly updates the network topology and lighting fixture locations, and dynamically adjusts the lighting fixture locations based on changes in the ad hoc network;

[0152] When the monitoring center detects abnormal data, the monitoring center determines the abnormal lighting fixture that caused the abnormality based on the identification information in the abnormal data;

[0153] The monitoring center locates the position of abnormal lighting fixtures based on the calculated position information of each lighting fixture.

[0154] Specifically, each lighting fixture regularly broadcasts its own network information to neighboring nodes, including device ID, signal strength, load status, etc. The neighboring nodes pass this information to the monitoring center and summarize it into a complete network view. At this time, the monitoring center organizes the node information into a graph structure, in which each lighting fixture is a node, the connection relationship is represented as an edge, and the signal strength between neighboring nodes is recorded. By analyzing the connection relationship, signal strength and other factors, the monitoring center can draw the relative position of each node in the network to form a complete network topology diagram. The monitoring center infers the distance between each lighting fixture and its neighbors based on the received signal strength. By analyzing the number of neighbors and signal strength of each node, the monitoring center can infer the relative distance between multiple nodes, thereby roughly determining their position relationship. Based on the relative position and neighbor relationship, the monitoring center calibrates the position of other nodes through reference nodes with known positions. Based on the relative distance and direction between nodes, combined with known geographic information, the monitoring center can calculate the absolute geographic location of all lighting fixtures and record them in the database. Each lighting fixture updates its position and neighbor node information regularly or when it moves, and sends these updated information to the monitoring center. The monitoring center recalculates the network topology based on the new node information and signal strength data, and updates the location information of all nodes in real time. After receiving the abnormal data, the monitoring center quickly queries the location information of the lamp through the lamp ID in the abnormal data packet. If the abnormal data involves multiple lamps, the system will mark the locations of these lamps in the network topology map and draw the affected area. The monitoring center finds the node of the abnormal lighting fixture from the network topology map and displays its specific location based on the absolute geographical location calculated previously. If the abnormal lighting fixture is in a mobile state, the monitoring center will also dynamically locate it based on its latest location information and update the abnormal location in a timely manner.

[0155] Furthermore, in one embodiment of the present invention, after the step of the monitoring center locating the position of the abnormal lighting fixture according to the calculated position information of each lighting fixture, the following steps are included:

[0156] When the monitoring center detects that the abnormal data of the abnormal lighting fixture is physiological health data, the monitoring center determines each target neighboring node near the abnormal lighting fixture according to the network topology;

[0157] The monitoring center sends control instructions to each target neighboring node through the self-organizing network, so that the lighting fixtures of the target neighboring nodes send out alarm information, and the alarm information includes flashing, color change or sound prompt.

[0158] Specifically, when the monitoring center detects that the abnormal data of the abnormal lighting fixture is physiological health data, the monitoring center determines that all lighting fixtures that are close to the abnormal lighting fixture are target neighboring nodes by analyzing the relative position of the abnormal lighting fixture and the connected neighboring nodes in the network topology map. The target neighboring node is a lighting fixture that is close to the abnormal lighting fixture in space or network, and may be a lighting fixture located in the same area. Further, the monitoring center sends a control instruction to the target neighboring node through the self-organizing network to trigger a corresponding alarm signal. The control instruction is transmitted through the relay node in the self-organizing network to ensure that it can reach each target neighboring node, and the control instruction content includes the alarm type (such as flashing, color change or sound prompt). At this time, the lighting fixture of the target neighboring node sends an alarm message according to the control instruction of the monitoring center, and the alarm information includes but is not limited to flashing, color change or sound prompt. Specifically, the lighting fixture of the target neighboring node flashes quickly at a predetermined frequency to attract the attention of the user. Or the lighting fixture of the target neighboring node changes color, for example, from conventional white light to red, yellow, etc., to display a warning state. Alternatively, the lighting fixtures of the target neighboring nodes may be combined with a sound output device to emit a warning sound, further enhancing the alarm effect.

[0159] Furthermore, in one embodiment of the present invention, after the step of the monitoring center sending the control instruction to each target neighboring node through the ad hoc network, the following step is further included:

[0160] The monitoring center dynamically adjusts the control instructions sent to each target neighboring node according to the relative position changes between the lighting fixtures of the target neighboring node and the abnormal lighting fixtures, so as to adjust the intensity or mode of the alarm information.

[0161] Specifically, the monitoring center monitors the location information of the target neighboring nodes in real time through the signal strength change in the self-organizing network or other positioning means, and calculates the relative position change of the target neighboring nodes relative to the abnormal lighting fixtures (such as the moving distance, angle change). At this time, by analyzing the relative position change between the lighting fixtures of the target neighboring nodes and the abnormal lighting fixtures, it can be determined whether the nearby users are approaching the abnormal lighting fixtures, and the control instructions sent to each target neighboring node are dynamically adjusted accordingly to adjust the intensity or mode of the alarm information, thereby gradually guiding the users using each target neighboring node to approach or move away from the abnormal lighting fixtures. When the user using the lighting fixture of the target neighboring node gradually approaches the abnormal lighting fixture, the monitoring center dynamically adjusts the control instructions to gradually increase the intensity of the alarm signal. For example, the flashing frequency increases, or the color changes from a soft warning color to a more eye-catching danger signal. On the contrary, if the user is moving away from the abnormal lighting fixture, the alarm signal is controlled to gradually weaken to avoid unnecessary interference. Furthermore, when the monitoring center detects that a user using a lighting fixture of a target neighboring node approaches an abnormal lighting fixture to a preset distance (for example, within 5 meters), the monitoring center increases the flashing frequency or brightness of the abnormal lighting fixture and issues a more significant alarm, prompting the user that he or she is approaching the target area and needs to take further measures (such as first aid, risk avoidance).

[0162] Furthermore, in one embodiment of the present invention, the method further comprises:

[0163] When the monitoring center detects that the abnormal data of the abnormal lighting fixture returns to normal, the monitoring center stops sending control instructions to each target neighboring node through the self-organizing network, so that the lighting fixtures of each target neighboring node return to standard lighting.

[0164] Furthermore, when the monitoring center detects that the abnormal data of the abnormal lighting fixture is environmental data, the monitoring center determines each target neighboring node near the abnormal lighting fixture according to the network topology; the monitoring center sends control instructions to each target neighboring node through the self-organizing network, so that the lighting fixture of the target neighboring node sends an alarm message, wherein the alarm message includes flashing, color change or sound prompt. The monitoring center dynamically adjusts the control instructions sent to each target neighboring node according to the relative position change between the lighting fixture of the target neighboring node and the abnormal lighting fixture, so as to adjust the intensity or mode of the alarm message. It should be pointed out that when the abnormal data is physiological health data, the monitoring center sends control instructions so that users using the lighting fixtures of the target neighboring node can provide corresponding guidance and rescue according to the alarm information. When the abnormal data is environmental data, the control instructions sent by the monitoring center are used to enable users using the lighting fixtures of the target neighboring node to escape from the abnormal environment area according to the alarm information. The control process of the monitoring center can refer to the above, and the control process when the abnormal data is environmental data will not be repeated here.

[0165] In summary, the lighting fixture data transmission control method in the above-mentioned embodiment of the present invention, by using the Mesh network protocol to establish an ad hoc network, the lighting fixture can automatically establish a multi-hop transmission network with other lighting fixtures around it, so as to achieve reliable and stable data transmission, and in the case of frequent node movement, the lighting fixture can dynamically adjust the network topology to maintain good communication quality; by setting different priorities (the priorities of physiological health data, environmental data, and status data are from high to low), it is ensured that high-priority critical data (such as physiological health data) can be transmitted and processed in real time, while low-priority status data can be delayed or processed in batches, thereby improving the resource utilization efficiency of the lighting fixture and optimizing the overall transmission performance; by real-time evaluation of the signal strength and node status in the network Based on the load and hop information, lighting fixtures can select the optimal transmission path and strategy according to the data priority and the real-time situation of the network, avoiding bottlenecks in data transmission and improving the emergency response capability and stability of lighting fixtures. Different compression strategies are adopted according to data of different priorities. High-priority data (such as physiological health data) is not compressed to ensure its real-time transmission. For medium and low priority data (such as environmental data and status data), appropriate compression methods are adopted to reduce bandwidth occupancy and improve data transmission efficiency. After receiving the data from the lighting fixtures, the monitoring center can analyze and process the data in time according to the priority of the data, thereby improving the real-time and accuracy of mine safety assurance. It solves the problems of stability, real-time and priority management of data transmission in the complex environment of existing mines.

[0166] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0167] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A lighting fixture data transmission control method, characterized in that: The lighting fixture is connected and communicated with a receiving device worn by a user, and the method includes: The lighting fixture collects environmental data of the current location, status data during operation, and receives and stores physiological health data collected by a receiving device worn by the user; Different priorities are set for each type of data according to the characteristics of the collected data, and corresponding compression strategies are used to process different data according to the priorities, among which the priorities of physiological health data, environmental data, and status data are set in descending order; Based on the Mesh network protocol, lighting fixtures automatically establish a multi-hop transmission ad hoc network with other nearby lighting fixtures, and dynamically adjust the network topology according to the lighting fixtures' geographical location, signal strength, mobility and load conditions; The lighting fixture evaluates the preferred order of various transmission paths transmitted to the monitoring center in real time based on the real-time information in the ad hoc network, and sets corresponding transmission paths and transmission strategies for different data according to the priority. The real-time information includes signal strength, node load and hop count information. The lighting fixture transmits data of different priorities to the monitoring center hop by hop through the transmission path selected in the ad hoc network according to the set transmission strategy; The monitoring center receives data from lighting fixtures through the ad hoc network and processes the data accordingly based on its priority.

2. The lighting fixture data transmission control method according to claim 1, characterized in that: The step of using corresponding compression strategies to process different data according to priority includes: Lighting fixtures do not compress high-priority physiological health data; Lighting fixtures use wavelet transform to perform multi-scale decomposition and moderate compression on medium-priority environmental data; The lighting fixture utilizes wavelet transform to perform multi-scale decomposition and highly compress or uncompress low-priority status data.

3. The lighting fixture data transmission control method according to claim 2, characterized in that: The step of the lighting fixture using wavelet transform to perform multi-scale decomposition and moderate compression on the medium-priority environmental data includes: Lighting fixtures pre-process medium-priority environmental data by filtering, denoising or mean smoothing; The lighting fixture uses discrete wavelet transform to perform multi-scale decomposition on the pre-processed environmental data, decomposing the comprehensive data into low-frequency components and high-frequency components at different scales; The lighting fixture performs threshold processing on the high-frequency components and removes coefficients below the preset threshold; The lighting fixture recombines the processed low-frequency components and high-frequency components through inverse wavelet transform to generate compressed environmental data.

4. The lighting fixture data transmission control method according to claim 1, characterized in that: The steps of automatically establishing a multi-hop transmission ad hoc network with other nearby lighting fixtures based on the Mesh network protocol include: After the lighting fixture is started, it automatically scans the network information of other lighting fixtures around it, and the network information includes geographical location, signal strength, and load status; The lighting fixture broadcasts its own network information to other lighting fixtures around it; The lighting fixtures select the best neighbor node based on the signal strength, load conditions and geographical location of each lighting fixture; The lighting fixtures establish communication connections with the selected optimal neighbor nodes, exchange their respective information through the Mesh network protocol, and form a preliminary network topology structure; The lighting fixture automatically selects the optimal transmission path according to the current network topology and its own geographical location, and establishes a multi-hop transmission connection with at least one neighboring node in the self-organizing network.

5. The lighting fixture data transmission control method according to claim 4, characterized in that: The step of dynamically adjusting the network topology structure according to the geographical location, signal strength, movement status and load condition of the lighting fixture comprises: The lighting fixture automatically detects the signal strength and load of the neighboring nodes connected to it periodically or according to network changes; Lighting fixtures determine the relative position relationship by monitoring the geographic location of themselves and neighboring nodes in real time; The lighting fixtures evaluate the stability and transmission efficiency of the current network topology according to the signal strength, geographical location, mobility and load of each neighboring node; When the network stability or transmission efficiency is lower than the preset threshold, the lighting fixture dynamically selects the best neighbor node according to the geographical location, signal strength and load of each neighbor node, and re-establishes the connection to adjust the network topology; Lighting fixtures dynamically adjust their connection relationships with other nodes based on the signal strength, load conditions, and mobility status of each neighboring node; The lighting fixture broadcasts the updated network topology information to the surrounding nodes to synchronously update the topology of the entire ad hoc network.

6. The lighting fixture data transmission control method according to claim 1, characterized in that: The step of evaluating the preferred order of various transmission paths transmitted to the monitoring center in real time based on the real-time information in the ad hoc network comprises: The lighting fixture monitors the signal strength between it and each neighboring node in real time and evaluates the transmission quality of each path based on the signal strength; Lighting fixtures evaluate the load of neighboring nodes connected to them in real time to determine the processing capacity and network pressure of each node; The lighting fixture calculates the number of hops required for each path to reach the monitoring center based on the current network topology and evaluates the transmission efficiency of each path; The lighting fixture comprehensively evaluates the comprehensive performance of each path based on the signal strength, load and hop count information of each neighboring node, and determines the preferred ranking of various transmission paths; When network conditions change, lighting fixtures re-evaluate and update the preferred order of various transmission paths based on new signal strength, load conditions, and hop count information.

7. The lighting fixture data transmission control method according to claim 6, characterized in that: The step of setting corresponding transmission paths and transmission strategies for different data according to priorities includes: Setting the transmission path of high-priority physiological health data as the optimal transmission path in the preferred sorting, and setting the transmission strategy as real-time transmission; The transmission path of the medium-priority environmental data is set as the suboptimal transmission path in the preferred order, and the transmission strategy is set as scheduled transmission; The transmission path of the low-priority status data is set as a non-critical transmission path in the preferred order, and the transmission strategy is set as delayed transmission or batch package transmission.

8. The lighting fixture data transmission control method according to claim 7, characterized in that: The step of transmitting the data of different priorities to the monitoring center hop by hop through the transmission path selected in the ad hoc network according to the set transmission strategy comprises: The lighting fixture selects the optimal transmission path in the ad hoc network and uses a real-time transmission strategy to preferentially transmit high-priority physiological health data hop by hop to the monitoring center; The lighting fixture selects the suboptimal transmission path in the ad hoc network and uses a timed transmission strategy to transmit the medium-priority environmental data hop by hop to the monitoring center; The lighting fixtures select non-critical transmission paths in the ad hoc network and use delayed transmission or batch package transmission strategies to preferentially transmit low-priority status data hop by hop to the monitoring center.

9. The lighting fixture data transmission control method according to claim 1, characterized in that: The monitoring center receives data from the lighting fixtures through the ad hoc network and performs corresponding processing according to the priority of the data, including: The monitoring center receives various data transmitted from the lighting fixtures through the ad hoc network; The monitoring center determines the time for processing and analysis based on the priority of various data, and detects whether there are abnormal values ​​or abnormal data exceeding the preset threshold during processing and analysis; When the monitoring center detects abnormal data, it automatically issues an alarm, locates the relevant lighting fixtures based on the abnormal data, and triggers corresponding emergency measures.

10. The lighting fixture data transmission control method according to claim 9, characterized in that: The step of locating the position of the relevant lighting fixture according to the abnormal data comprises: The monitoring center builds a complete network topology based on the node information of lighting fixtures in the self-organizing network and records the relative position and connection relationship of each node; The monitoring center calculates the relative position of each lighting fixture based on the connection relationship of each lighting fixture in the network topology and identifies the distance and direction between related nodes; The monitoring center calculates the absolute position of each lighting fixture based on the distance between nodes, relative position relationship and the position of known reference points; The monitoring center regularly updates the network topology and lighting fixture locations, and dynamically adjusts the lighting fixture locations based on changes in the ad hoc network; When the monitoring center detects abnormal data, the monitoring center determines the abnormal lighting fixture that caused the abnormality based on the identification information in the abnormal data; The monitoring center locates the position of abnormal lighting fixtures based on the calculated position information of each lighting fixture.

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