Unmanned aerial vehicle equipment access management and scheduling method

Abstract

The invention discloses an unmanned aerial vehicle equipment access management and scheduling method, and relates to the technical field of cloud computing and big data. Comprising the following steps: step 1, creating a standardized access interface of unmanned aerial vehicle equipment; 2, collecting data in real time in the task execution process of the unmanned aerial vehicle equipment, preprocessing the collected data, comprehensively processing the preprocessed data from different unmanned aerial vehicle equipment by adopting a data fusion algorithm, and generating a state model of the unmanned aerial vehicle equipment; the method comprises the steps of 1, analyzing current available unmanned aerial vehicle equipment based on a state model by using an optimization algorithm, and dynamically adjusting resource allocation of the unmanned aerial vehicle equipment to execute a corresponding task, 4, monitoring execution state information of the unmanned aerial vehicle equipment in real time and obtaining feedback information, and 5, after the task is completed, evaluating and analyzing the unmanned aerial vehicle equipment and generating a task report.

Description

Technical Field

[0001] The invention discloses a method for access management and scheduling of unmanned aerial vehicle equipment, and relates to the technical fields of cloud computing and big data. Background Art

[0002] With the rapid development of drone technology and the continuous expansion of application scenarios, the industry's demand for unmanned equipment is also growing. Drones have performed well in inspection tasks in the fields of electricity, transportation, petrochemicals, etc., but the existing unmanned equipment management system generally has problems such as poor equipment compatibility, low scheduling efficiency, and uneven resource utilization. Existing systems can often only support specific models of equipment and are difficult to cope with diverse market demands. Therefore, there is an urgent need for a new management platform that can support the access and coordinated management of multi-model and multi-load unmanned equipment to meet the needs of different inspection tasks. According to market research data, the unmanned equipment market is expected to grow at an average annual rate of 20% in the next five years. With the increasing demand in the fields of power inspection, environmental monitoring, traffic management, etc., efficient management and scheduling systems will become the key to improving the utilization rate of unmanned equipment and reducing operating costs. Industry experts predict that intelligent unmanned equipment management systems will occupy an important position in future market competition. Summary of the invention

[0003] In view of the problems of the prior art, the present invention provides a method for access management and scheduling of UAV equipment, which realizes efficient integration and resource optimization of UAV equipment and provides comprehensive support for inspection tasks in various industries.

[0004] The specific scheme proposed by the present invention is:

[0005] The present invention provides a method for access management and scheduling of unmanned aerial vehicle equipment, comprising:

[0006] Step 1: Create a standardized access interface for drone devices, so that the standardized access interface covers data transmission protocols, defines control command formats, and provides a status feedback mechanism.

[0007] Register the connected drone devices based on the cloud management platform and generate a unique device ID based on the drone device information for subsequent management and scheduling.

[0008] Perform initial configuration on connected drone devices and verify the functions of drone devices;

[0009] Step 2: Collect data in real time during the UAV equipment's mission execution. The collected data includes location information, sensor data, and status information. Preprocess the collected data and use data fusion algorithms to comprehensively process the preprocessed data from different UAV equipment to generate a state model of the UAV equipment.

[0010] Step 3: Define and classify tasks, use optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjust the resource allocation of drone equipment to perform corresponding tasks.

[0011] Step 4: Monitor the execution status information of the drone equipment in real time and obtain feedback information, and adjust the resource allocation of the drone equipment according to the execution status information and feedback information.

[0012] Step 5: After the mission is completed, conduct an evaluation and analysis of the drone equipment and generate a mission report.

[0013] Furthermore, in step 1 of the method for access management and scheduling of unmanned aerial vehicle equipment, the accessed unmanned aerial vehicle equipment is registered, including: filling in relevant information, including equipment model, load capacity, sensor configuration,

[0014] Perform initial configuration on connected drone devices, including configuration parameters, task priority, and communication methods.

[0015] Furthermore, the sensor data collected in step 2 of the method for access management and scheduling of unmanned aerial vehicle equipment includes temperature data, humidity data, and video images, and the collected status information includes the power and signal strength of the unmanned aerial vehicle equipment;

[0016] Preprocess the collected data, including data cleaning, noise removal and format conversion, to ensure the accuracy and consistency of the data for subsequent analysis;

[0017] The pre-processed data from different UAV devices are processed comprehensively to generate a state model of the UAV device, including: using a Kalman filter algorithm or a particle filter algorithm to process the pre-processed data and generate a state model.

[0018] Furthermore, in step 3 of the method for access management and scheduling of unmanned aerial vehicle equipment, tasks are defined and classified, including defining inspection tasks, where the inspection tasks involve task types, task areas, time requirements, and required equipment types.

[0019] Generate task descriptions based on the information input by the user, and classify tasks according to the task descriptions;

[0020] Use optimization algorithms to analyze currently available equipment based on state models, including: using genetic algorithms, ant colony algorithms, or machine learning algorithms to analyze the status of currently available drone equipment based on state models, and obtain drone equipment status, task priority, and time constraint information.

[0021] Based on the analysis results, the task is assigned to the most suitable drone equipment, and the task status is updated in real time to ensure that the task can proceed smoothly.

[0022] The present invention also provides a UAV equipment access management and scheduling device, including an interface management module, a data management module, a task management module, a monitoring feedback module and a report generation module.

[0023] The interface management module creates a standardized access interface for drone equipment, which covers data transmission protocols, defines control command formats, and provides a status feedback mechanism.

[0024] Register the connected drone devices based on the cloud management platform and generate a unique device ID based on the drone device information for subsequent management and scheduling.

[0025] Perform initial configuration on connected drone devices and verify the functions of drone devices;

[0026] The data management module collects data in real time during the UAV equipment's mission execution. The collected data includes location information, sensor data, and status information. The collected data is pre-processed and the pre-processed data from different UAV equipment is comprehensively processed using a data fusion algorithm to generate a state model of the UAV equipment.

[0027] The task management module defines and classifies tasks, uses optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjusts the resource allocation of drone equipment to perform corresponding tasks.

[0028] The monitoring and feedback module monitors the execution status information of the drone equipment in real time and obtains feedback information, and adjusts the resource allocation of the drone equipment according to the execution status information and feedback information.

[0029] After the report generation module completes the task, it conducts an evaluation and analysis of the drone equipment and generates a task report.

[0030] Furthermore, the interface management module of the drone device access management and scheduling device registers the connected drone device, including: filling in relevant information, including device model, load capacity, sensor configuration,

[0031] Perform initial configuration on connected drone devices, including configuration parameters, task priority, and communication methods.

[0032] Furthermore, the sensor data collected by the data management module of the UAV equipment access management and scheduling device includes temperature data, humidity data, and video images, and the collected status information includes the power and signal strength of the UAV equipment;

[0033] Preprocess the collected data, including data cleaning, noise removal and format conversion, to ensure the accuracy and consistency of the data for subsequent analysis;

[0034] The pre-processed data from different UAV devices are processed comprehensively to generate a state model of the UAV device, including: using a Kalman filter algorithm or a particle filter algorithm to process the pre-processed data and generate a state model.

[0035] Furthermore, the task management module of the UAV equipment access management and scheduling device defines tasks and classifies tasks, including defining inspection tasks, which involve task types, task areas, time requirements, and required equipment types.

[0036] Generate task descriptions based on the information input by the user, and classify tasks according to the task descriptions;

[0037] Use optimization algorithms to analyze currently available equipment based on state models, including: using genetic algorithms, ant colony algorithms, or machine learning algorithms to analyze the status of currently available drone equipment based on state models, and obtain drone equipment status, task priority, and time constraint information.

[0038] Based on the analysis results, the task is assigned to the most suitable drone equipment, and the task status is updated in real time to ensure that the task can proceed smoothly.

[0039] The benefits of the present invention are:

[0040] 1. Improve resource utilization: Through intelligent scheduling algorithms, dynamic scheduling of equipment can be achieved, equipment idleness and repeated use can be reduced, and resources can be utilized to the maximum extent.

[0041] 2. Improve inspection efficiency: realize multi-device collaborative operation, improve inspection speed and accuracy, and shorten task completion time.

[0042] 3. Reduce operating costs: By optimizing equipment management and scheduling, reduce manual intervention and resource waste, and reduce inspection costs.

[0043] 4. Enhance system flexibility: support access to multiple models of equipment to meet the diverse needs of different customers and industries, and improve the adaptability and scalability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0046] Example 1

[0047] The present invention provides a method for access management and scheduling of unmanned aerial vehicle equipment, comprising:

[0048] Step 1: Create a standardized access interface for drone devices, so that the standardized access interface covers data transmission protocols, defines control command formats, and provides status feedback mechanisms. Drone devices include fixed-wing drones, multi-rotor drones, and ground robots.

[0049] Register the connected drone equipment based on the cloud management platform, including: filling in relevant information, including equipment model, load capacity, sensor configuration, and generating a unique device ID based on the drone equipment information for subsequent management and scheduling.

[0050] Perform initial configuration on the connected drone equipment, including configuration of parameters, task priority, and communication methods. Verify the functions of the drone equipment and ensure that the equipment can operate normally after connection.

[0051] Step 2: Collect data in real time while the drone device is performing its mission. The collected data includes location information, sensor data, and status information. The sensor data includes temperature data, humidity data, and video images. The collected status information includes the power level and signal strength of the drone device.

[0052] The collected data are preprocessed, including data cleaning, noise removal and format conversion, to ensure the accuracy and consistency of the data for subsequent analysis.

[0053] The Kalman filter algorithm or the particle filter algorithm is used to process the preprocessed data and generate a state model.

[0054] Step 3: Define and classify tasks, use optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjust the resource allocation of drone equipment to perform corresponding tasks.

[0055] Defining tasks and classifying them may include defining inspection tasks, which involve task types, task areas, time requirements, and required equipment types.

[0056] Generate task descriptions based on the information input by the user, and classify tasks according to the task descriptions;

[0057] Use optimization algorithms to analyze currently available equipment based on state models, including: using genetic algorithms, ant colony algorithms or machine learning algorithms to analyze the status of currently available drone equipment based on state models, and obtain drone equipment status, task priority and time constraint information, such as equipment power, current task load, working status, etc. Task priority: Sort inspection tasks according to their urgency and importance. Time constraints ensure that tasks are completed within the specified time.

[0058] Based on the analysis results, the task is assigned to the most suitable drone equipment, and the task status is updated in real time to ensure that the task can proceed smoothly.

[0059] Step 4: Monitor the execution status information of the drone equipment in real time and obtain feedback information, and adjust the resource allocation of the drone equipment according to the execution status information and feedback information.

[0060] Establish real-time communication with unmanned equipment through wireless network to monitor the flight status, sensor data and mission progress of the equipment. Users can view real-time data on the cloud management platform to keep abreast of the equipment's operating status.

[0061] Thresholds can be set to monitor the status of equipment in real time. Once an abnormality is detected, such as signal loss, low battery, task delay, etc., an alarm is triggered immediately and corresponding processing is performed, such as rescheduling the task or dispatching backup equipment to ensure the smooth progress of the task.

[0062] Step 5: After the mission is completed, conduct an evaluation and analysis of the drone equipment and generate a mission report.

[0063] When the mission is completed, the drone equipment will automatically return to the starting position and generate a mission completion status report, which contains detailed data and results of the mission execution for subsequent analysis.

[0064] Data storage and analysis: The data during the task execution process is stored, and users can analyze historical data to evaluate equipment performance, task execution efficiency and inspection quality. Feedback can be provided for each inspection task, and task scheduling and equipment management strategies can be continuously optimized based on user feedback to improve the overall service quality.

[0065] Example 2

[0066] The present invention also provides a UAV equipment access management and scheduling device, including an interface management module, a data management module, a task management module, a monitoring feedback module and a report generation module.

[0067] The interface management module creates a standardized access interface for drone equipment, which covers data transmission protocols, defines control command formats, and provides a status feedback mechanism.

[0068] Register the connected drone devices based on the cloud management platform and generate a unique device ID based on the drone device information for subsequent management and scheduling.

[0069] Perform initial configuration on connected drone devices and verify the functions of drone devices;

[0070] The data management module collects data in real time during the UAV equipment's mission execution. The collected data includes location information, sensor data, and status information. The collected data is pre-processed and the pre-processed data from different UAV equipment is comprehensively processed using a data fusion algorithm to generate a state model of the UAV equipment.

[0071] The task management module defines and classifies tasks, uses optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjusts the resource allocation of drone equipment to perform corresponding tasks.

[0072] The monitoring and feedback module monitors the execution status information of the drone equipment in real time and obtains feedback information, and adjusts the resource allocation of the drone equipment according to the execution status information and feedback information.

[0073] After the report generation module completes the task, it conducts an evaluation and analysis of the drone equipment and generates a task report.

[0074] As the information interaction and execution process between the modules of the above-mentioned device are based on the same concept as the embodiment of the method of the present invention, the specific contents can be found in the description of the embodiment of the method of the present invention and will not be repeated here.

[0075] Likewise, the benefits of the device of the present invention are:

[0076] 1. Improve resource utilization: Through intelligent scheduling algorithms, dynamic scheduling of equipment can be achieved, equipment idleness and repeated use can be reduced, and resources can be utilized to the maximum extent.

[0077] 2. Improve inspection efficiency: realize multi-device collaborative operation, improve inspection speed and accuracy, and shorten task completion time.

[0078] 3. Reduce operating costs: By optimizing equipment management and scheduling, reduce manual intervention and resource waste, and reduce inspection costs.

[0079] 4. Enhance system flexibility: support access to multiple models of equipment to meet the diverse needs of different customers and industries, and improve the adaptability and scalability of the system.

[0080] It should be noted that not all steps and modules in the above-mentioned processes and device structures are necessary, and some steps or modules can be ignored according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The system structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or some components in multiple independent devices may be implemented together.

[0081] The above-described embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A method for access management and scheduling of unmanned aerial vehicle equipment, characterized in that include: Step 1: Create a standardized access interface for drone devices, so that the standardized access interface covers data transmission protocols, defines control command formats, and provides a status feedback mechanism. Register the connected drone devices based on the cloud management platform and generate a unique device ID based on the drone device information for subsequent management and scheduling. Perform initial configuration on connected drone devices and verify the functions of drone devices; Step 2: Collect data in real time during the UAV equipment's mission execution. The collected data includes location information, sensor data, and status information. Preprocess the collected data and use data fusion algorithms to comprehensively process the preprocessed data from different UAV equipment to generate a state model of the UAV equipment. Step 3: Define and classify tasks, use optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjust the resource allocation of drone equipment to perform corresponding tasks. Step 4: Monitor the execution status information of the drone equipment in real time and obtain feedback information, and adjust the resource allocation of the drone equipment according to the execution status information and feedback information. Step 5: After the mission is completed, conduct an evaluation and analysis of the drone equipment and generate a mission report.

2. A method for access management and scheduling of unmanned aerial vehicle equipment according to claim 1, characterized in that In step 1, register the connected drone device, including: filling in relevant information, including device model, load capacity, sensor configuration, Perform initial configuration on connected drone devices, including configuration parameters, task priority, and communication methods.

3. The method for access management and scheduling of unmanned aerial vehicle equipment according to claim 1 is characterized in that The sensor data collected in step 2 includes temperature data, humidity data, and video images, and the collected status information includes the power and signal strength of the drone equipment; Preprocess the collected data, including data cleaning, noise removal and format conversion, to ensure the accuracy and consistency of the data for subsequent analysis; The pre-processed data from different UAV devices are processed comprehensively to generate a state model of the UAV device, including: using a Kalman filter algorithm or a particle filter algorithm to process the pre-processed data and generate a state model.

4. The method for access management and scheduling of unmanned aerial vehicle equipment according to claim 1 is characterized in that In step 3, tasks are defined and classified, including inspection tasks. Inspection tasks involve task type, task area, time requirements, and required equipment types. Generate task descriptions based on the information input by the user, and classify tasks according to the task descriptions; Use optimization algorithms to analyze currently available equipment based on state models, including: using genetic algorithms, ant colony algorithms, or machine learning algorithms to analyze the status of currently available drone equipment based on state models, and obtain drone equipment status, task priority, and time constraint information. Based on the analysis results, the task is assigned to the most suitable drone equipment, and the task status is updated in real time to ensure that the task can proceed smoothly.

5. A drone equipment access management and scheduling device, characterized in that It includes interface management module, data management module, task management module, monitoring feedback module and report generation module. The interface management module creates a standardized access interface for drone equipment, which covers data transmission protocols, defines control command formats, and provides a status feedback mechanism. Register the connected drone devices based on the cloud management platform and generate a unique device ID based on the drone device information for subsequent management and scheduling. Perform initial configuration on connected drone devices and verify the functions of drone devices; The data management module collects data in real time during the UAV equipment's mission execution. The collected data includes location information, sensor data, and status information. The collected data is pre-processed and the pre-processed data from different UAV equipment is comprehensively processed using a data fusion algorithm to generate a state model of the UAV equipment. The task management module defines and classifies tasks, uses optimization algorithms to analyze currently available drone equipment based on the state model, and dynamically adjusts the resource allocation of drone equipment to perform corresponding tasks. The monitoring and feedback module monitors the execution status information of the drone equipment in real time and obtains feedback information, and adjusts the resource allocation of the drone equipment according to the execution status information and feedback information. After the report generation module completes the task, it conducts an evaluation and analysis of the drone equipment and generates a task report.

6. The UAV equipment access management and scheduling device according to claim 5 is characterized in that The interface management module registers the connected drone device, including: filling in relevant information, including device model, load capacity, sensor configuration, Perform initial configuration on connected drone devices, including configuration parameters, task priority, and communication methods.

7. The UAV equipment access management and scheduling device according to claim 5 is characterized by: The sensor data collected by the data management module include temperature data, humidity data, and video images, and the collected status information includes the power and signal strength of the drone equipment; Preprocess the collected data, including data cleaning, noise removal and format conversion, to ensure the accuracy and consistency of the data for subsequent analysis; The pre-processed data from different UAV devices are processed comprehensively to generate a state model of the UAV device, including: using a Kalman filter algorithm or a particle filter algorithm to process the pre-processed data and generate a state model.

8. The device for managing and scheduling access to unmanned aerial vehicle equipment according to claim 5 is characterized in that The task management module defines and categorizes tasks, including inspection tasks. Inspection tasks involve task type, task area, time requirements, and required equipment types. Generate task descriptions based on the information input by the user, and classify tasks according to the task descriptions; Use optimization algorithms to analyze currently available equipment based on state models, including: using genetic algorithms, ant colony algorithms, or machine learning algorithms to analyze the status of currently available drone equipment based on state models, and obtain drone equipment status, task priority, and time constraint information. Based on the analysis results, the task is assigned to the most suitable drone equipment, and the task status is updated in real time to ensure that the task can proceed smoothly.

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