Low-altitude equipment state information processing method and system

Abstract

The invention provides a low-altitude equipment state information processing method and system, and belongs to the technical field of low-altitude equipment state information processing, and the method comprises the steps: receiving the real-time state data of each low-altitude equipment state through a multi-protocol data access network; based on position data in the real-time state data, dividing a geographic space into grid units with set levels by using an airspace grid engine, and encoding the grid units to generate an airspace grid model; based on the airspace grid model, airspace occupation calculation and conflict detection are carried out, and early warning information is generated; and pushing the collision risk early warning information to a monitoring terminal for three-dimensional visual display through the message middleware, and / or sending the collision risk early warning information to a low-altitude equipment control system to generate a flight control instruction. According to the invention, real-time data is acquired through multiple protocols, the dynamic airspace grid model is constructed, conflicts are accurately detected, early warning is generated, the data are pushed to the monitoring terminal for visual display, and the flight safety and the operation efficiency are improved.

Description

Technical Field

[0001] This application belongs to the field of low-altitude equipment status information processing technology, specifically relating to a method and system for processing low-altitude equipment status information. Background Technology

[0002] With the development of the low-altitude industry, drones and other low-altitude equipment are increasingly being used in agricultural plant protection, logistics and distribution, emergency command, and cultural tourism. The number of low-altitude devices has surged, making the real-time collection, processing, and analysis of their status information (such as location, speed, altitude, battery level, and equipment status) crucial for ensuring low-altitude flight safety and operational efficiency.

[0003] However, existing methods for processing status information from low-altitude equipment have several problems: First, low-altitude equipment comes from different manufacturers and uses diverse communication protocols (such as MQTT, WebSocket, RTMP, etc.), making data access difficult and hindering unified processing. For example, flight data needs to be accessed and converted through multiple gateways (such as MQTT Broker and WebSocket gateway), increasing system complexity. Second, traditional data processing methods struggle to handle massive amounts of high-concurrency status data, leading to monitoring delays and failing to meet the need for real-time status updates. Third, the low-altitude airspace load lacks effective gridded modeling and dynamic computing capabilities, making it difficult to achieve accurate collision warnings and no-fly zone intrusion detection. Static and dynamic calculations are required through an airspace grid engine, but existing calculation methods are inefficient and prone to false alarms. Finally, status information is mostly displayed as raw data, lacking visualization and intelligent analysis based on a 3D airspace grid, making it difficult to meet the needs of multi-source data fusion display and trajectory playback, resulting in poor visualization and difficulty in supporting command and decision-making.

[0004] Therefore, there is an urgent need for a method and system for processing low-altitude equipment status information based on airspace grid engine and multi-source data fusion, so as to improve the safety and operational efficiency of low-altitude flight by sensing, intelligently analyzing and collaboratively controlling the status of low-altitude equipment. Summary of the Invention

[0005] In a first aspect, embodiments of this application provide a method for processing low-altitude equipment status information, comprising the following steps: S1. Receive real-time status data of each low-altitude device through a multi-protocol data access network; S2. Based on location data in real-time status data, the spatial domain is divided into grid units of a set level using a spatial grid engine, and the grid units are encoded to generate a spatial grid model. S3. Based on the spatial grid model, perform spatial occupancy calculation and conflict detection to generate early warning information; The dynamic collision detection includes at least: constructing a safety envelope grid based on the real-time position and velocity of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; S4. Push the early warning information to the monitoring terminal for three-dimensional visualization through the message middleware, and / or send it to the low-altitude equipment control system to generate flight control commands.

[0006] Furthermore, the specific steps of step S1 are as follows: S11. Receive real-time status data directly pushed by low-altitude devices through the MQTT Broker in front of the data processing platform; S12. Listen to real-time status data from a third-party MQTT Broker through the built-in MQTT gateway of the data processing platform, perform legality verification and format conversion, and then forward it to the internal MQTT Broker of the data processing platform; S13. Receive WebSocket data from the outside through the WebSocket gateway built into the data processing platform, perform validity verification and format conversion, and then forward it to the MQTT Broker inside the data processing platform; The real-time status data includes at least one of the following: device identifier, latitude and longitude coordinates, altitude, speed, heading, battery level, and device health status.

[0007] Furthermore, the specific steps of step S2 are as follows: S21. Determine the target grid level (Level) and, based on this level, determine the basic grid cell span Δ of the latitude and longitude plane; S22. Calculate the grid coordinates of the aircraft in the latitude (Lat), longitude (Lon), and altitude (Alt) planes and in the altitude direction, respectively:

[0008]

[0009]

[0010] Where i is the row number of the latitude and longitude plane grid, j is the column number of the latitude and longitude plane grid, and k is the height level. The reference latitude for the coding area, The longitude is the reference longitude for the coding area, H is the preset level height reference, Δ represents the basic grid cell span, and floor() represents the floor function. S23. Using the Z-order space filling curve, the row and column numbers (i,j) of the planar grid are bit-crossed and merged with the height level k to generate a unique integer grid code Code.

[0011] Furthermore, the specific steps of step S3 are as follows: S31. Construct a safe envelope mesh for aircraft i : Using a grid coding method, the real-time position of aircraft i is determined. As the center, with the radius of the safe envelope grid The spherical spatial domain, with radius as the boundary, is meshed to generate a safe envelope mesh as a set of meshes. ; S32. Calculate the secure envelope mesh Grid set with risk area The intersection of the grid sets of the risk areas No-fly zone grid Or the safety envelope grid of another aircraft j ; S33. The intersection calculated analytically, if If a collision risk is detected, the risk type and risk level are determined, and a collision risk warning message is generated and output. The collision risk warning message includes at least the risk type, the identification of the low-altitude equipment involved, the risk level, and the grid code of the risk location. The risk type is based on the grid set of the risk area. The specific type was determined to be an inter-aircraft conflict or a no-fly zone intrusion; If the grid set of the risk area For the safety envelope grid of another aircraft j If the risk type is determined to be inter-aircraft conflict; if the grid set of the risk area... No-fly zone grid If so, the risk type is determined to be an intrusion into the no-fly zone; Regarding the types of inter-aircraft conflicts: Risk level Calculated using the following formula:

[0012] in, The estimated collision time is calculated based on the relative position and velocity vectors of aircraft i and aircraft j. and Let be the instantaneous velocity scalars of aircraft i and aircraft j, respectively. and These are the preset time weight and speed weight coefficients for collision risk, respectively; For no-fly zone intrusion types: Risk level Calculated using the following formula:

[0013] in, Let i be the shortest Euclidean distance from the center of aircraft i that intrudes into the no-fly zone boundary. Let i be the instantaneous velocity scalar of aircraft i. and These are preset depth and speed weighting coefficients for intrusion risk.

[0014] Furthermore, step S3 also includes reliability conflict detection based on the device health status, the specific steps of which are as follows: S34. Obtain equipment health status data of the low-altitude equipment, wherein the equipment health status data includes at least one of battery cycle life, key component wear warning, and communication signal strength; S35. Calculate the real-time reliability score S of the low-altitude equipment based on the equipment health status data; S36. If the reliability score S is lower than the preset safety threshold Then, device reliability warning information is generated and output in conjunction with the collision risk warning information.

[0015] Furthermore, the formula for calculating the real-time reliability score S in step S35 is as follows:

[0016] in, This is the battery degradation coefficient. The wear coefficient of the component. The normalized communication signal quality is represented by α, β, and γ, which are preset weighting coefficients, and α+β+γ=1.

[0017] Furthermore, the radius of the safety envelope mesh in step S31 Real-time speed based on aircraft i The calculation is performed using the preset reaction time t, and the formula is as follows:

[0018] Where C is the safety tolerance constant.

[0019] Furthermore, the specific steps of step S4 are as follows: S41. After encapsulating the collision risk warning information in JSON format, use a message middleware to publish it to the preset warning topic. S42. The flight data cockpit and / or low-altitude equipment control system of the monitoring terminal subscribes to the aforementioned warning topic and receives collision risk warning information in real time; S43. Synchronously process and respond to the received collision risk warning information: In the 3D visualization interface of the flight data cockpit on the monitoring terminal, aircraft involved in risks are highlighted, and the safety envelope mesh of aircraft involved in risks is displayed in a dynamic rendering manner. The low-altitude equipment control system automatically generates and verifies flight control commands based on the risk level and equipment identification in the collision risk warning information. Then, it sends the verified flight control commands to the corresponding low-altitude equipment for execution through the multi-protocol data access network.

[0020] Furthermore, it also includes the following steps: S5. Flight trajectory retrospective analysis: S51. Record and store real-time status data, airspace grid model snapshots, and early warning information for all low-altitude equipment; S52. In response to user queries, historical flight trajectories are replayed in a 3D visualization interface based on stored data; S53. During playback, the corresponding spatial grid model, safety envelope grid, and triggered early warning information are displayed synchronously for post-event analysis and responsibility determination.

[0021] Secondly, embodiments of this application also provide a low-altitude equipment status information processing system, comprising: The multi-protocol data access module is used to receive real-time status data of various low-altitude devices through a multi-protocol data access network. The spatial grid modeling module is used to divide the geographic space into grid cells of a set level based on location data in real-time status data, and to encode the grid cells to generate a spatial grid model. The conflict detection and early warning module is used to perform airspace occupancy calculation and conflict detection based on the airspace grid model, and generate early warning information. The dynamic collision detection includes at least: constructing a safety envelope grid based on the real-time position and velocity of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; The early warning information distribution and execution module is used to push early warning information to the monitoring terminal for three-dimensional visualization display through message middleware, and / or send it to the low-altitude equipment control system to generate flight control commands.

[0022] As can be seen from the above technical solutions, this application has the following advantages: The low-altitude equipment status information processing method and system provided in this application utilize a multi-protocol data access network, enabling real-time reception of status data from different low-altitude equipment, ensuring the comprehensiveness and timeliness of the data. An airspace grid engine divides the geographic space into grid units of a set level, encodes these units, and generates an airspace grid model, achieving refined management and dynamic adjustment of airspace. Based on the airspace grid model, airspace occupancy calculation and conflict detection are performed, quickly generating collision risk warning information and improving flight safety. A message middleware pushes the warning information to the monitoring terminal for 3D visualization and simultaneously sends it to the low-altitude equipment control system to generate flight control commands, achieving efficient information transmission and intuitive display. Combining equipment health status data with reliability conflict detection generates equipment reliability warning information, enhancing the ability to predict equipment failures. By recording and storing real-time status data of all low-altitude equipment, airspace grid model snapshots, and warning information, historical flight trajectory playback and analysis are achieved, facilitating post-event analysis and responsibility determination. Attached Figure Description

[0023] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the low-altitude equipment status information processing method of the present invention.

[0025] Figure 2 This is a schematic diagram of the low-altitude equipment status information processing system of the present invention. Detailed Implementation

[0026] The various embodiments of this disclosure will be described more fully in the detailed steps of the low-altitude equipment status information processing method described below. This disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of this disclosure to the specific embodiments disclosed herein, but rather this disclosure should be understood to cover all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of this disclosure.

[0027] For example, under the wave of the low-altitude economy, drones and other low-altitude equipment are playing a significant role in agricultural plant protection, logistics and distribution, emergency command, and cultural tourism, with their application scale rapidly expanding. However, with the number of devices increasing exponentially, the real-time collection, accurate processing, and in-depth analysis of their status information have become crucial for ensuring low-altitude flight safety and improving operational efficiency. Currently, the field of low-altitude equipment status information processing faces multiple challenges. First, the wide variety of equipment sources and brands, along with diverse communication protocols (including MQTT, WebSocket, RTMP, etc.), leads to numerous obstacles to data access and makes unified processing extremely difficult. Taking flight data as an example, it often requires the use of multiple gateways (such as MQTT Broker and WebSocket gateway) for complex data access and format conversion, which undoubtedly increases the complexity and maintenance difficulty of the system significantly. Second, the influx of massive and highly concurrent status data overwhelms traditional data processing methods, making it difficult to meet real-time requirements, resulting in frequent monitoring delays and the inability to achieve immediate updates to the status of low-altitude equipment, thus posing a potential threat to flight safety. Third, the low-altitude airspace is increasingly overloaded, but there is a lack of efficient gridded modeling and dynamic calculation methods. In key functions such as collision warning and no-fly zone intrusion detection, existing calculation methods are not only inefficient but also have a high false alarm rate, making it difficult to accurately ensure low-altitude flight safety. Fourth, the status information display format is primitive, mostly presenting unprocessed raw data, lacking intuitive visualization and intelligent analysis functions based on three-dimensional airspace grids. This display method cannot meet the needs of multi-source data fusion display, nor can it achieve flight trajectory playback and analysis, resulting in poor visual effects and difficulty in effectively assisting command and decision-making.

[0028] To address the aforementioned issues, this embodiment provides a method for processing low-altitude equipment status information. By employing technologies such as multi-protocol data access, airspace grid modeling, dynamic conflict detection and early warning, and message middleware push, this method solves the complexity of collecting, processing, and analyzing low-altitude equipment status information, thereby improving the safety and operational efficiency of low-altitude flights.

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please see Figure 1 The diagram shows a flowchart of a method for processing low-altitude equipment status information in a specific embodiment. The method includes the following steps: S1. Receive real-time status data of each low-altitude device through a multi-protocol data access network; It should be noted that by using a multi-protocol data access network, real-time status data from different low-altitude devices can be received, ensuring the comprehensiveness and timeliness of the data and providing an accurate data foundation for subsequent processing. S2. Based on location data in real-time status data, the spatial domain is divided into grid units of a set level using a spatial grid engine, and the grid units are encoded to generate a spatial grid model. It should be noted that generating an airspace grid model based on real-time status data enables dynamic partitioning and management of airspace, improves the utilization efficiency of airspace resources, and provides model support for conflict detection. S3. Based on the spatial grid model, perform spatial occupancy calculation and conflict detection to generate early warning information; The dynamic collision detection includes at least: constructing a safety envelope grid based on the real-time position and velocity of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; It should be noted that generating early warning information through dynamic conflict detection can quickly identify potential collision risks and effectively ensure flight safety. At the same time, combining equipment health status data for reliability conflict detection enhances the ability to predict equipment failures. S4. Push the early warning information to the monitoring terminal for three-dimensional visualization through the message middleware, and / or send it to the low-altitude equipment control system to generate flight control commands; It should be noted that by using a message middleware to push early warning information to the monitoring terminal for 3D visualization, and simultaneously sending it to the low-altitude equipment control system to generate flight control commands, efficient information transmission and intuitive display are achieved, facilitating command and decision-making, and enabling precise control of low-altitude equipment.

[0031] This embodiment accesses the network through multiple protocols to ensure compatibility and real-time performance of data from different low-altitude equipment; it generates an airspace grid model based on real-time status data, enabling dynamic division and management of airspace and improving the utilization efficiency of airspace resources; it generates early warning information through dynamic collision detection, which can quickly identify potential collision risks and effectively ensure flight safety; and it pushes early warning information to the monitoring terminal and low-altitude equipment control system through message middleware, achieving efficient transmission and real-time response of early warning information.

[0032] Furthermore, as a refinement and extension of the specific implementation of the above embodiments, in order to fully illustrate the specific implementation process in this embodiment, another method for processing low-altitude equipment status information is provided, which includes the following steps: S1. Receive real-time status data of each low-altitude device through a multi-protocol data access network; The specific steps of step S1 are as follows: S11. Receive real-time status data directly pushed by low-altitude devices through the MQTT Broker in front of the data processing platform; For example, a logistics company's drone fleet (e.g., using DJI Matrice 300 RTK) directly pushes real-time status data every 2 seconds through the MQTT Broker in front of the data processing platform. The data includes the device identifier "DJI-M300-001", latitude and longitude coordinates (30.1234°N, 120.5678°E), altitude 80m, speed 15m / s, heading 270°, battery level 85%, and normal device health status. S12. Listen to real-time status data from a third-party MQTT Broker through the built-in MQTT gateway of the data processing platform, perform legality verification and format conversion, and then forward it to the internal MQTT Broker of the data processing platform; For example, a third-party drone operation platform (such as the private platform of an agricultural plant protection company) sends real-time data of plant protection drones (such as the XAG P40 model) through its MQTTBroker. The MQTT gateway built into the data processing platform listens to the Broker, performs legality verification (verifies the registration information of the device identifier xxxx) and format conversion (converts the custom time format to UTC time) on the data, and then forwards it to the internal MQTT Broker. The data includes latitude and longitude (30.2345°N, 120.6789°E), altitude 50m, and spraying flow rate of 1.2L / min. S13. Receive WebSocket data from the outside through the WebSocket gateway built into the data processing platform, perform validity verification and format conversion, and then forward it to the MQTT Broker inside the data processing platform; The real-time status data includes at least one of the following: device identifier, latitude and longitude coordinates, altitude, speed, heading, battery level, and device health status. For example, an emergency rescue team's drone (e.g., EHang EH216-S) sends real-time video streams and status data to a data processing platform via the WebSocket protocol. After receiving the data, the built-in WebSocket gateway verifies the device's authorization certificate (confirming that it belongs to a registered emergency device), converts the video stream format to H.265 encoding, and converts the status data (e.g., latitude and longitude 30.3456°N, longitude 120.7890°E, altitude 100m, remaining flight time 25min) into JSON format and forwards it to the internal MQTT Broker. S2. Based on location data in real-time status data, the spatial domain is divided into grid units of a set level using a spatial grid engine, and the grid units are encoded to generate a spatial grid model. The specific steps of step S2 are as follows: S21. Determine the target grid level (Level) and, based on this level, determine the basic grid cell span Δ of the latitude and longitude plane; For example, the target grid level is determined to be Level=10, and the span of the basic latitude and longitude plane grid unit corresponding to this level is Δ=0.001° (approximately 110m×110m). S22. Calculate the grid coordinates of the aircraft in the latitude (Lat), longitude (Lon), and altitude (Alt) planes and in the altitude direction, respectively:

[0033]

[0034]

[0035] Where i is the row number of the latitude and longitude plane grid, j is the column number of the latitude and longitude plane grid, and k is the height level. The reference latitude for the coding area, The longitude is the reference longitude for the coding area, H is the preset level height reference, Δ represents the basic grid cell span, and floor() represents the floor function. For example, taking the airspace of a certain city as the coding area, a reference latitude is set. =30.0°, reference longitude =120.0°, layer height reference H=10m; for the logistics drone "DJI-M300-001" in step S1, its latitude is =30.1234°, Longitude =120.5678°, height Alt=80m, calculate the grid coordinates: Latitude and longitude plane grid row number i = floor( )=123 latitude and longitude plane grid column number j=floor( )=567 Height level k = floor( )=8; S23. Using the Z-order space filling curve, the planar grid row and column numbers (i,j) are bit-crossed and merged with the height level k to generate a unique integer grid code Code; For example, using a Z-order space filling curve, the planar grid row and column numbers (123, 567) are bit-crossed and merged with the height level 8; for example, 123 is converted to binary "1111011", 567 is converted to binary "1000110111", and 8 is converted to binary "1000". After cross-merging according to the Z-order rules, a unique integer grid code Code=123456789 is generated. It should be noted that in actual use, grid coding still requires precise calculation using a bit-by-bit interleaving algorithm; Step S23 is followed by the following steps: S24. Perform dynamic density optimization on the generated spatial grid model: Real-time statistics on the number of low-altitude devices within each grid cell; If the number of devices in a certain grid cell exceeds a preset density threshold, the grid cell is adaptively subdivided, the corresponding grid level is increased, and the span of the basic grid cell is reduced to the new grid cell span by a set margin. Using new grid cell span Recalculate the grid code for the corresponding region to generate a high-density regional gateway model; The optimized high-density regional grid model is merged with the basic grid model to update the global spatial grid model; S3. Based on the spatial grid model, perform spatial occupancy calculation and conflict detection to generate early warning information; The dynamic collision detection includes at least: constructing a safety envelope grid based on the real-time position and velocity of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; The specific steps of step S3 are as follows: S31. Construct a safe envelope mesh for aircraft i : Using a grid coding method, the real-time position of aircraft i is determined. As the center, with the radius of the safe envelope grid The spherical spatial domain, with radius as the boundary, is meshed to generate a safe envelope mesh as a set of meshes. ; The radius of the safety envelope mesh in step S31 Real-time speed based on aircraft i The calculation is performed using the preset reaction time t, and the formula is as follows:

[0036] Where C is the safety tolerance constant; For example, a secure envelope mesh is constructed for the logistics drone "DJI-M300-001". Given that the real-time position P(x,y,z) corresponds to latitude and longitude (30.1234°, 120.5678°), altitude 80m, real-time velocity V1 = 15m / s, preset reaction time t = 5s, and safety tolerance constant C = 20m, the safety envelope grid radius R1 = 15 × 5 + 20 = 95m is calculated according to the formula R1 = V1 × t + C. Using a grid coding method, the spherical airspace centered at P with a radius of 95m is gridded to generate a safety envelope grid set containing 20 grid cells. ; S32. Calculate the secure envelope mesh Grid set with risk area The intersection of the grid sets of the risk areas No-fly zone grid Or the safety envelope grid of another aircraft j ; For example, suppose a grid set of a no-fly zone (e.g., an airport airspace) is provided. Including grid code "123456780-123456790", calculate and Intersection, Discovery The grid code "123456789" belongs to scope; S33. The intersection calculated analytically, if If a collision risk is detected, the risk type and risk level are determined, and a collision risk warning message is generated and output. The collision risk warning message includes at least the risk type, the identification of the low-altitude equipment involved, the risk level, and the grid code of the risk location. The risk type is based on the grid set of the risk area. The specific type was determined to be an inter-aircraft conflict or a no-fly zone intrusion; If the grid set of the risk area For the safety envelope grid of another aircraft j If the risk type is determined to be inter-aircraft conflict; if the grid set of the risk area... No-fly zone grid If so, the risk type is determined to be an intrusion into the no-fly zone; Regarding the types of inter-aircraft conflicts: Risk level Calculated using the following formula:

[0037] in, The estimated collision time is calculated based on the relative position and velocity vectors of aircraft i and aircraft j. and Let be the instantaneous velocity scalars of aircraft i and aircraft j, respectively. and These are the preset time weight and speed weight coefficients for collision risk, respectively; For no-fly zone intrusion types: Risk level Calculated using the following formula:

[0038] in, Let i be the shortest Euclidean distance from the center of aircraft i that intrudes into the no-fly zone boundary. Let i be the instantaneous velocity scalar of aircraft i. and These are preset depth and speed weighting coefficients for intrusion risk. For example, parsing the intersection result, because If a collision risk is detected, a collision risk warning is generated, which includes the risk type "No-fly zone intrusion", the identification of the equipment involved "DJI-M300-001", the risk level "High risk", and the grid code of the risk location "123456789". Step S3 also includes reliability conflict detection based on device health status, the specific steps of which are as follows: S34. Obtain equipment health status data of the low-altitude equipment, wherein the equipment health status data includes at least one of battery cycle life, key component wear warning, and communication signal strength; For example, obtain the device health status data of "DJI-M300-001": Battery cycle life 200 cycles (attenuation coefficient) =0.2), wear warning value for key components (motor) 0.1 ( =0.1), communication signal strength -70dBm (normalized) =0.8); S35. Calculate the real-time reliability score S of the low-altitude equipment based on the equipment health status data; The formula for calculating the real-time reliability score S in step S35 is as follows:

[0039] in, This is the battery degradation coefficient. The wear coefficient of the component. The normalized communication signal quality is represented by α, β, and γ, which are preset weighting coefficients, and α+β+γ=1. For example, the weighting coefficients are preset to α=0.4, β=0.3, and γ=0.3, according to the formula... The real-time reliability score is calculated as S = 0.4 × (1 - 0.2) + 0.3 × (1 - 0.1) + 0.3 × 0.8 = 0.32 + 0.27 + 0.24 = 0.83. S36. If the reliability score S is lower than the preset safety threshold Then, device reliability warning information is generated and output in conjunction with the collision risk warning information; For example, setting a security threshold =0.7, since 0.83>0.7, no equipment reliability warning information is generated; if the drone battery cycle life reaches 500 cycles ( =0.6), and calculated, S=0.4×(1-0.6)+0.3×(1-0.1)+0.3×0.8=0.16+0.27+0.24=0.67<0.7, generating equipment reliability early warning information and outputting it in conjunction with collision risk early warning information; S4. Push the early warning information to the monitoring terminal for three-dimensional visualization through the message middleware, and / or send it to the low-altitude equipment control system to generate flight control commands; The specific steps of step S4 are as follows: S41. After encapsulating the collision risk warning information in JSON format, use a message middleware to publish it to the preset warning topic. For example, the collision risk warning information of "DJI-M300-001" is encapsulated in JSON format: { "riskType": "No-fly zone intrusion", "deviceId": "DJI-M300-001", "riskLevel": "High Risk", "gridCode": "123456789", "timestamp": "2025-XX-XXTXX:XX:XXZ" } Publish to the alert topic "lowAltitudeWarning / forbiddenZone" using the Kafka message middleware; S42. The flight data cockpit and / or low-altitude equipment control system of the monitoring terminal subscribes to the aforementioned warning topic and receives collision risk warning information in real time; For example, the flight data cockpit of the monitoring terminal (deployed at the Xiaoshan District Low Altitude Command Center) and the low-altitude equipment control system of the logistics company subscribe to this topic and receive early warning information in real time; S43. Synchronously process and respond to the received collision risk warning information: In the 3D visualization interface of the flight data cockpit on the monitoring terminal, aircraft involved in risks are highlighted, and the safety envelope mesh of aircraft involved in risks is displayed in a dynamic rendering manner. Based on the risk level and equipment identification in the collision risk warning information, the low-altitude equipment control system automatically generates and verifies flight control commands, and then sends the verified flight control commands to the corresponding low-altitude equipment for execution through the multi-protocol data access network. The specific logic for automatically generating flight control commands is as follows: If the risk level is high, an instruction will be generated to either make an immediate emergency landing or fly to the nearest emergency landing point, and the optimal landing route will be planned. If the risk level is medium, then an instruction to adjust the course to avoid obstacles or slow down and hover is generated, and a local obstacle avoidance path is planned based on the updated airspace grid model. If the risk level is low, an instruction will be generated to prompt the operator to intervene, and warning details and suggested actions will be pushed to the monitoring interface; For example, the monitoring terminal: in the three-dimensional visualization interface, "DJI-M300-001" is highlighted in red, its safety envelope grid (a spherical area with a radius of 95m) is dynamically rendered, and the no-fly zone boundary is marked, so that the command personnel can intuitively view the risk location; Low-altitude equipment control system: Based on the "high risk" level and equipment identification, it automatically generates flight control commands such as "immediately adjust the heading to 360° and descend to 50m" and sends them to "DJI-M300-001" via the MQTT protocol. After receiving the command, the UAV will make the adjustment to avoid entering the no-fly zone.

[0040] In another embodiment of the present invention, unlike the embodiments described above, the following steps are also included: S5. Flight trajectory retrospective analysis: S51. Record and store real-time status data, airspace grid model snapshots, and early warning information for all low-altitude equipment; For example, record and store the real-time status data of "DJI-M300-001" from 8:00 to 10:00 on XX month XX day, 2025 (one record every 2 seconds, a total of 3600 records), the airspace grid model snapshot (saved every 5 minutes, a total of 24 snapshots), and the collision risk warning information (1 record). S52. In response to user queries, historical flight trajectories are replayed in a 3D visualization interface based on stored data; For example, logistics companies can query the trajectory of the drone during that time period through a monitoring terminal. The system can then replay the flight trajectory in a 3D visualization interface based on the stored data, showing the complete path of the drone from the Xiaoshan District logistics warehouse, through Qianjiang Century City and the Olympic Sports Center, to the Binjiang District delivery point. S53. During playback, the corresponding spatial grid model, safety envelope grid, and triggered early warning information are displayed synchronously for post-event analysis and responsibility determination. For example, when the playback reaches 8:45, the airspace grid model (Level=10), the safety envelope grid of "DJI-M300-001" (radius 95m) and the triggered no-fly zone intrusion warning information are displayed simultaneously, and the grid code of the risk location is marked "123456789", which is convenient for post-event analysis of why the drone approached the no-fly zone and whether there were any loopholes in the flight path planning. This embodiment achieves unified data collection for low-altitude equipment in different scenarios such as logistics, agriculture, and emergency response through multi-protocol data access; through airspace grid modeling, the airspace of Xiaoshan District, Hangzhou City is accurately divided into Level=10 grid units with a coding accuracy of 110m×110m×10m, meeting the needs of refined management and control of low-altitude equipment; through dynamic conflict detection, the risk of logistics drones intruding into no-fly zones is successfully identified, and reliability is assessed in conjunction with equipment health status to avoid false alarms and missed alarms; through early warning information distribution and trajectory backtracking, real-time risk handling and post-event traceability are achieved, significantly improving the safety and operational efficiency of low-altitude flights.

[0041] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0042] like Figure 2 As shown, the following are embodiments of the low-altitude equipment status information processing system provided in this disclosure. This system and the low-altitude equipment status information processing methods in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the low-altitude equipment status information processing system, please refer to the embodiments of the low-altitude equipment status information processing methods described above.

[0043] The system includes: The multi-protocol data access module is used to receive real-time status data of various low-altitude devices through a multi-protocol data access network. The spatial grid modeling module is used to divide the geographic space into grid cells of a set level based on location data in real-time status data, and to encode the grid cells to generate a spatial grid model. The conflict detection and early warning module is used to perform airspace occupancy calculation and conflict detection based on the airspace grid model, and generate early warning information. The dynamic collision detection includes at least: constructing a safety envelope grid based on the real-time position and velocity of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; The early warning information distribution and execution module is used to push early warning information to the monitoring terminal for three-dimensional visualization display through message middleware, and / or send it to the low-altitude equipment control system to generate flight control commands.

[0044] This embodiment achieves real-time monitoring and accurate early warning of low-altitude equipment status through the interactive collaboration of a multi-protocol data access module, an airspace grid modeling module, a conflict detection and early warning module, and an early warning information distribution and execution module, thereby ensuring flight safety.

[0045] The low-altitude equipment status information processing method provided in this application embodiment can be applied to electronic devices. Those skilled in the art will understand that the electronic device structure involved in the embodiments of this invention does not constitute a limitation on the electronic device. An electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. In the embodiments of this invention, the electronic device includes, but is not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of this application described and / or claimed herein.

[0046] Electronic devices may include processors, external memory interfaces, internal memory, universal serial bus (USB) interfaces, charging management modules, power management modules, batteries, wireless communication modules, audio modules, speakers, microphones, sensor modules, buttons, cameras, displays, and SIM card interfaces, etc.

[0047] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device. In other embodiments of this application, the electronic device may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0048] A processor may include one or more processing units, such as a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors.

[0049] The processor can serve as the nerve center and command center of an electronic device. The controller can generate operation control signals based on the instruction opcode and timing signals to control the fetching and execution of instructions.

[0050] The processor may also include memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can store instructions or data that the processor has just used or that are used repeatedly. If the processor needs to use the instruction or data again, it can retrieve it directly from this memory. This avoids repeated accesses, reduces processor latency, and thus improves system efficiency.

[0051] The aforementioned electronic device implements the low-altitude equipment status information processing method of this application, which receives location data from the real-time status data of each low-altitude equipment through a multi-protocol data access network; based on the real-time status data, it uses an airspace grid engine to divide the geographic space into grid units of a set level, and encodes the grid units to generate an airspace grid model; based on the airspace grid model, it performs airspace occupancy calculation and conflict detection to generate early warning information; the dynamic conflict detection includes at least: constructing a safety envelope grid based on the real-time position and speed of aircraft i, and generating collision risk early warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; and pushing the early warning information to the monitoring terminal for three-dimensional visualization display through a message middleware, and / or sending it to the low-altitude equipment control system to generate flight control commands. This achieves the beneficial effects of improving the flight safety and operational efficiency of low-altitude equipment and accurately predicting risks through multi-protocol data access and airspace grid modeling.

[0052] The storage medium provided in this application stores a program product capable of implementing a method for processing low-altitude equipment status information.

[0053] The method for processing low-altitude equipment status information includes: receiving real-time status data of each low-altitude equipment through a multi-protocol data access network; based on the location data in the real-time status data, using an airspace grid engine to divide the geographic space into grid units of a set level, and encoding the grid units to generate an airspace grid model; based on the airspace grid model, performing airspace occupancy calculation and conflict detection to generate early warning information; the dynamic conflict detection includes at least: constructing a safety envelope grid based on the real-time position and speed of aircraft i, and generating collision risk early warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; pushing the early warning information to the monitoring terminal for three-dimensional visualization display through a message middleware, and / or sending it to the low-altitude equipment control system to generate flight control commands.

[0054] In some possible implementations, the low-altitude equipment status information processing method of this disclosure can be implemented as a program product including program code, which, when the program product is run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0055] The storage medium disclosed herein may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0056] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A low-altitude device state information processing method, characterized by, The method comprises the following steps: S1. receiving real-time state data of each low-altitude device through a multi-protocol data access network; S2. dividing a geographic space into grid units of a set level using a space grid engine based on position data in the real-time state data, and encoding the grid units to generate a space grid model; S3. performing space occupation calculation and conflict detection based on the space grid model to generate early warning information; The dynamic conflict detection at least comprises: constructing a safety envelope grid based on the real-time position and speed of the aircraft i, and generating collision risk early warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of the aircraft j; S4. pushing the early warning information to a monitoring terminal for three-dimensional visual display through a message middleware, and / or sending it to a low-altitude device control system to generate flight control instructions.

2. The low-altitude device state information processing method of claim 1, wherein The specific steps of step S1 are as follows: S11. receiving real-time state data directly pushed by low-altitude devices through the MQTT Broker in front of the data processing platform; S12. listening to real-time state data from a third-party MQTT Broker through the MQTT gateway built-in in the data processing platform, performing legal verification and format conversion, and forwarding to the internal MQTT Broker of the data processing platform; S13. receiving WebSocket data from the outside through the WebSocket gateway built-in in the data processing platform, performing legal verification and format conversion, and forwarding to the internal MQTT Broker of the data processing platform; The real-time state data includes at least one of device identification, latitude and longitude coordinates, height, speed, heading, battery capacity, and device health status.

3. The low-altitude device state information processing method of claim 1, wherein The specific steps of step S2 are as follows: S21. determine the target grid level Level, and determine the basic grid unit span Δ of the latitude and longitude plane according to the level; S22. calculate the grid coordinates of the aircraft in the latitude and longitude plane and the height direction respectively according to the latitude Lat, longitude Lon and height Alt of the aircraft: where i is the row number of the longitude-latitude plane grid, j is the column number of the longitude-latitude plane grid, and k is the height level, is the reference latitude of the encoding area, is the reference longitude of the encoding area, H is a preset height level reference, Δ represents a basic grid unit span, and floor() represents a down-rounding function; S23. adopt Z-order space filling curve to cross and merge the plane grid row and column number (i, j) with the height level k to generate a unique integer grid code Code.

4. The low-altitude device state information processing method according to claim 3, characterized by, The specific steps of step S3 are as follows: S31. Constructing a safety envelope mesh for the aircraft i : Using a grid encoding method, the real-time position of the aircraft i as the center, the radius of the safety envelope grid The spherical airspace as the radius is gridded to generate the safety envelope grid as a grid set ; S32. Computing a safety envelope mesh the intersection of the mesh set of risk areas the mesh set of risk areas is a no-fly zone mesh or the safety envelope mesh of another aircraft j ; S33. Analyze the calculated intersection, if then determine that there is a collision risk, determine the risk type and risk level, generate and output collision risk warning information; The collision risk early warning information at least includes risk type, involved low-altitude device identification, risk level, and grid code of risk position; The risk type is determined as an inter-aircraft conflict or a no-fly zone intrusion according to the specific type of the grid set of risk areas ​ if the set of grids of the risk region is the safety envelope grid of another aircraft j then the risk type is determined to be an inter-aircraft collision; if the set of grids of the risk region is the no-fly zone grid then the risk type is determined to be a no-fly zone intrusion; For aircraft conflict type: Risk rating This is calculated by the following formula: wherein, is a predicted time to collision calculated based on the relative position and velocity vectors of aircraft i and aircraft j, and are the instantaneous speed scalars of aircraft i and aircraft j, respectively, and are preset time and speed weight coefficients for the collision risk, respectively. For no-fly zone intrusion type: Risk rating This is calculated by the following formula: wherein, is the shortest Euclidean distance of the center position of the aircraft i to the border of the no-fly zone, is the instantaneous speed of the aircraft i, and are preset depth weight and speed weight coefficients for the intrusion risk.

5. The low-altitude device state information processing method according to claim 4, characterized by, Step S3 also includes reliability conflict detection based on device health status, and the specific steps are as follows: S34. obtain device health status data of the low-altitude device, which includes at least one of battery cycle life, key component wear warning, and communication signal strength; S35. calculate the real-time reliability score S of the low-altitude device based on the device health status data; S36. If the reliability score S is lower than a preset safety threshold a device reliability warning information is generated and output in association with the collision risk warning information.

6. The low-altitude device state information processing method according to claim 5, characterized by, The calculation formula of the real-time reliability score S in step S35 is: wherein, is a battery decay coefficient, is a component wear coefficient, is a normalized communication signal quality, and a, b, g are preset weight coefficients, and a+b+g=1.

7. The low-altitude device state information processing method according to claim 4, characterized by, Step S31: radius of the safety envelope mesh based on the real-time speed of the aircraft i and the preset reaction time t, the calculation formula is: Where C is a safety fault tolerance constant.

8. The low-altitude device state information processing method according to claim 4, characterized by, The specific steps of step S4 are as follows: S41. After the collision risk warning information is encapsulated in JSON format, it is published to a preset warning topic Topic using a message middleware; S42. The flight data cockpit and / or low-altitude equipment control system of the monitoring terminal subscribes to the warning topic Topic and receives the collision risk warning information in real time; S43. The received collision risk warning information is processed and responded to in real time: In the three-dimensional visualization interface of the flight data cockpit of the monitoring terminal, the aircraft involved in the risk is highlighted, and the safety envelope grid of the aircraft involved in the risk is displayed in a dynamic rendering manner; The low-altitude equipment control system automatically generates and verifies flight control instructions based on the risk level and equipment identifier in the collision risk warning information, and then sends the verified flight control instructions to the corresponding low-altitude equipment through a multi-protocol data access network for execution.

9. The low-altitude device state information processing method according to claim 1, characterized by, Further comprising the following steps: S5. Flight trajectory backtracking and analysis: S51. Record and store the real-time state data of all low-altitude equipment, airspace grid model snapshots, and warning information; S52. In response to user queries, the stored data is used to perform historical flight trajectory playback in a three-dimensional visualization interface; S53. During the playback process, the airspace grid model, safety envelope grid, and triggered warning information at the corresponding time are displayed synchronously for post-analysis and responsibility identification.

10. A low altitude device state information processing system characterized by comprising: Comprise: A multi-protocol data access module for receiving real-time state data of each low-altitude equipment through a multi-protocol data access network; An airspace grid modeling module for dividing geographic space into grid cells of a set level using an airspace grid engine based on position data in the real-time state data, and encoding the grid cells to generate an airspace grid model; A conflict detection and warning module for performing airspace occupation calculation and conflict detection based on the airspace grid model to generate warning information; The dynamic conflict detection at least includes: constructing a safety envelope grid based on the real-time position and speed of aircraft i, and generating collision risk warning information by calculating the intersection between the safety envelope grid and the no-fly zone grid or the safety envelope grid of aircraft j; A warning information distribution and execution module for pushing the warning information to the monitoring terminal for three-dimensional visualization display through a message middleware, and / or sending it to the low-altitude equipment control system to generate flight control instructions.

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