Unmanned aerial vehicle sharing management method and system

Abstract

The invention provides an unmanned aerial vehicle sharing management method and system, and relates to the technical field of unmanned aerial vehicle sharing management, and the method comprises the steps: calculating heuristic information according to the time and place of reservation, the type of an unmanned aerial vehicle, and the position, state and maintenance condition of the unmanned aerial vehicle, and the heuristic information is the distance from the unmanned aerial vehicle to the reservation; for each ant, the next food source to be served is determined according to the pheromone concentration and heuristic information, each ant constructs a path, and the path represents a reservation sequence served by the ant; after all ants complete path construction, according to the total cost of each path, the pheromone matrix is updated, iteration is repeated to obtain a finally determined distribution scheme, and according to the finally determined distribution scheme, a corresponding unmanned aerial vehicle is distributed to each reservation; and according to the final unmanned aerial vehicle distribution scheme, the sharing platform sets use rules and cost standards of the unmanned aerial vehicles. The use efficiency of the unmanned aerial vehicle is improved, and the operation cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of drone sharing management, and in particular to a drone sharing management method and system. Background Art

[0002] With the rapid increase in the number of drones, traditional management methods that rely on manual registration, approval, and monitoring are no longer sufficient. This method is not only inefficient and wastes a lot of manpower and resources, but is also prone to management loopholes caused by human error, posing risks to the safe operation of drones.

[0003] More critically, current management methods lack effective information sharing mechanisms. Information such as the real-time status, location, and usage of drone resources cannot be effectively transmitted between different users and managers, leading to uneven resource allocation and low utilization. For example, some regions may experience an oversupply of drones, while others may experience a shortage. This information asymmetry not only hinders the efficient use of drones but also limits the wider application of drone technology. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention proposes a drone sharing management method and system, which not only improves the speed and efficiency of emergency response, but also reduces casualties and property losses.

[0005] In order to solve the above technical problems, the technical solutions of the present invention are as follows: In a first aspect, a method for sharing and managing drones is provided, the method comprising: Provide a drone sharing platform and allow users to book and use drones through the sharing platform; Establish a user account system on the sharing platform to record users' reservation, usage and payment information; Based on the final drone allocation plan, the sharing platform sets the drone usage rules and fee standards; Create a pheromone matrix representing the pheromone concentrations from each drone to each reservation, initially set to a uniform distribution. Here, drones are ants and reservations are food sources. Based on the time, location, and drone type of the reservation, as well as the drone's location, status, and maintenance, calculate a heuristic, which is the distance from the drone to the reservation. Each ant determines the next food source to serve based on pheromone concentration and heuristic information. Each ant constructs a path that represents the sequence of reservations it serves. Once all ants have completed path construction, the pheromone matrix is updated based on the total cost of each path. This process is repeated to arrive at a final allocation plan, which is then used to assign a drone to each reservation. According to the final UAV allocation plan, the sharing platform sets the usage rules and fee standards for UAVs.

[0006] The user confirms the reservation information and pays the corresponding fee. The sharing platform records the user's payment situation and completes the calculation and collection of the fee. The sharing platform designates a corresponding UAV for the user to use according to the reservation information paid by the user. During the user's use of the UAV, the sharing platform monitors the status and location of the UAV in real time. After the use is over, the UAV is returned through the sharing platform, and the calculation of the usage fee ends.

[0007] Furthermore, for each ant, the next food source to be served is determined according to the pheromone concentration and heuristic information, including: For each ant, according to the pheromone concentration and heuristic information, through determine the next food source to be served; Among them, represents at time , the probability that ant chooses to move from node to node ; represents at time , the pheromone concentration on the path from node to node ; represents the heuristic information from node to node , which is inversely proportional to the reciprocal of the distance between the two nodes; is the parameter of the importance of pheromone; is the parameter of the importance of heuristic information; represents the set of nodes that ant has not visited yet; represents the visibility on the path from node to node , which represents the reciprocal of the distance between node and node ; is a parameter; represents at time , the congestion degree of the path related to node that ant and has visited, which is a value between 0 and 1, where 0 means the path is completely uncongested and 1 means the path is completely blocked; is a parameter; represents at time , from node to node The pheromone concentration on the path; Indicates from node To node The heuristic information, which is directly proportional to the reciprocal of the distance between two nodes; Indicates from node To node The visibility on the path; Indicates at time The ant Has visited the congestion degree of the path related to nodes And Is a value between 0 and 1; Represents the current ant The node where it is located; Represents the ant The next possible selected node; Is the index of the ant; Is the index of another node.

[0008] Furthermore, according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards of the drones, and publicizes the usage rules and fee standards on the sharing platform, including: Analyze the reservation information, including the type of drone, reservation duration, reservation frequency, and formulate the usage rules and fee standards of the drones; Enter the formulated usage rules and fee standards into the background management system of the sharing platform, and automatically calculate the fees according to the usage duration and fee standards; Add a page for usage rules and fee standards to the user interface of the sharing platform, and publicize the usage rules and fee standards on the sharing platform.

[0009] Furthermore, when the user confirms the reservation information and pays the corresponding fees, the sharing platform records the payment situation of the user, and completes the calculation and collection of the fees, including: The user views and selects the drone reservation information on the sharing platform, including the reservation time, location, and drone model; The sharing platform automatically calculates the total fees to be paid according to the reservation duration, drone model selected by the user, and the set fee standards; According to the calculated total fees to be paid, the user selects the payment method and completes the payment operation according to the guidance of the payment interface; After the payment is successful, the sharing platform records the payment information in the payment record form, including the payment time, payment method, payment amount information, and settles with the payment service provider to determine that the payment amount is transferred to the account of the sharing platform, completing the calculation and collection of the fees.

[0010] Further, the sharing platform designates a corresponding drone for the user to use according to the reservation information paid by the user, including: The sharing platform collects the status information of currently available drones, including the real-time position, performance parameters, maintenance status, and last use time of the drones; The sharing platform extracts the reservation information of the user, including the reservation time, reservation location, and estimated use time; According to the status information of the drones, the sharing platform calculates an availability score for each drone; Compare the performance requirements in the user's reservation information with the availability scores of each drone to determine a list of drones; Calculate the straight-line distance between the user's reservation location and the current position of each available drone, and calculate a comprehensive matching degree for each drone based on the availability score and distance factor of the drone; According to the comprehensive matching degree, the sharing platform selects a drone from the list of drones for the user to use.

[0011] Further, the calculation formula for the availability score is: ; Wherein, represents the availability score; , represent weight coefficients; represents the performance of the drone; , represent weights; represents the remaining time; represents the total time; represents the maintenance status; represents the linear rate of performance decay; represents the acceleration of the decay rate; represents the time since the last maintenance; represents the maintenance interval.

[0012] Further, the calculation formula for the straight-line distance between the reservation location and the current position of each available drone is: ; Wherein, represents the straight-line distance between the reservation location and the current position of each available drone; represents the radius of the earth; represents the difference in latitude between the reservation location and the current position of the drone; represents the latitude of the reservation location; represents the latitude of the current position of the drone; represents the difference in longitude between the reservation location and the current position of the drone; represents the arcsine function.

[0013] Furthermore, the comprehensive matching degree calculation formula is as follows: ; Wherein, represents the comprehensive matching degree; represents the usability score; represents the weight; represents the usage time impact factor; represents the performance of the drone; represents the configuration score impact factor; represents the distance between the drone and the user's reserved location; represents the distance weight; represents the energy consumption impact factor; Maintenance status impact factor; represents the distance impact factor; represents the load capacity impact factor.

[0014] In a second aspect, a drone sharing management system includes: An acquisition module, which is used to provide a drone sharing platform and allow users to reserve and use drones through the sharing platform; establish a user account system on the sharing platform to record users' reservation, usage, and payment information; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones; create a pheromone matrix representing the pheromone concentration of each drone to each reservation, which is initially set to be evenly distributed, where the drones are ants and the reservation information is the food source; calculate the heuristic information according to the reservation time, location, and drone type, as well as the location, status, and maintenance conditions of the drones, and the heuristic information is the distance from the drone to the reservation; for each ant, determine the next food source to be served according to the pheromone concentration and heuristic information, and each ant will construct a path, and the path represents the reservation sequence served by the ant; when all ants have completed path construction, update the pheromone matrix according to the total cost of each path, and repeat the iteration to obtain the final determined allocation plan, and allocate the corresponding drone to each reservation according to the final determined allocation plan; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones and publicizes the usage rules and fee standards on the sharing platform; A processing module, which is used for users to confirm the reservation information and pay the corresponding fees, the sharing platform records the payment situation of users, and completes the calculation and collection of fees; the sharing platform designates the corresponding drone for users to use according to the reservation information paid by users; during the period when users use the drones, the sharing platform monitors the status and location of the drones in real time, and when the use is over, conducts the return operation of the drones through the sharing platform and ends the calculation of the usage fees; A scheduling module, used to automatically allocate and schedule drones, and cooperate closely with the processing module to perform intelligent scheduling based on drone position and status factors; A user management module, used to handle user operations, including registering new users, user logins, and personal information management, and manage user permissions; A payment processing module, used to handle the cost settlement and payment process for drone use, and cooperate with the processing module to determine the correct calculation and timely collection of fees; An order management module, used to receive and respond to user requests for drone use, track the status of each order, and work in coordination with the scheduling module and the processing module to determine that the drone completes the tasks specified by the user.

[0015] Thirdly, a computing device includes: One or more processors; A storage device, used to store one or more programs, which when executed by the one or more processors cause the one or more processors to implement the described method.

[0016] Fourthly, a computer-readable storage medium stores a program, which when executed by a processor implements the described method.

[0017] The above solution of the present invention has at least the following beneficial effects: Through the sharing platform, drone resources are utilized more effectively. Different users can reserve and use drones according to their own needs, avoiding the idle and waste of resources. At the same time, through the intelligent allocation algorithm, it can be ensured that drones can serve each reservation more efficiently, further improving the resource utilization rate.

[0018] For users, there is no need to purchase and maintain expensive drone equipment. They only need to reserve through the sharing platform and pay the corresponding fees to use the drones. This greatly reduces the user's usage cost and improves the convenience of use.

[0019] The sharing platform monitors the status and position of drones in real time, and can timely discover and handle potential safety problems. At the same time, through the unified management and maintenance of drones, their performance and safety can be ensured, reducing the risks caused by equipment failures.

[0020] This sharing management method helps to promote the popularization and development of the drone industry. By reducing the usage threshold and cost, more individuals and enterprises can access drone technology, thus promoting the innovation and progress of related technologies and applications.

[0021] Users can easily reserve and use drones through a sharing platform without worrying about the purchase, maintenance, and management of the equipment. At the same time, functions such as real-time monitoring and return operations provided by the platform also enhance the user experience. Sharing drones reduces the number of drones owned by individuals, thereby reducing resource consumption and waste generation. This meets the current social demands for environmental protection and sustainable development. Description of the Drawings

[0022] Figure 1 It is a schematic flow chart of a drone sharing management method provided by an embodiment of the present invention.

[0023] Figure 2 It is a schematic diagram of a drone sharing management system provided by an embodiment of the present invention. Detailed Embodiment

[0024] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0025] As Figure 1 shown, an embodiment of the present invention proposes a drone sharing management method, and the method includes the following steps: Step 1, provide a drone sharing platform and allow users to reserve and use drones through the sharing platform; Step 2, establish a user account system on the sharing platform to record users' reservation, usage, and payment information; Step 3, create a pheromone matrix to represent the pheromone concentration of each drone to each reservation, which is initially set to a uniform distribution. Among them, the drone is an ant, and the reservation information is a food source; according to the reservation time, location, and drone type, as well as the location, status, and maintenance of the drone, calculate the heuristic information, and the heuristic information is the distance from the drone to the reservation; for each ant, determine the next food source to be served according to the pheromone concentration and heuristic information, and each ant will construct a path, and the path represents the reservation sequence served by the ant; when all ants have completed path construction, update the pheromone matrix according to the total cost of each path, repeat the iteration to obtain the finally determined allocation plan, and allocate the corresponding drone to each reservation according to the finally determined allocation plan; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for the drones; Step 4, the user confirms the reservation information and pays the corresponding fee, the sharing platform records the user's payment situation, and completes the calculation and collection of the fee; Step 5: The sharing platform designates a corresponding drone for the user according to the reservation information paid by the user. Step 6: During the user's use of the drone, the sharing platform monitors the status and location of the drone in real time. After the use is completed, the user returns the drone through the sharing platform, and the calculation of the usage fee ends.

[0026] In the embodiment of the present invention, through the sharing platform, the drone resources are utilized more effectively. Different users can reserve and use drones according to their own needs, avoiding the idle and waste of resources. At the same time, through the intelligent allocation algorithm, it can be ensured that the drones can serve each reservation more efficiently, further improving the resource utilization rate. For users, there is no need to purchase and maintain expensive drone equipment. They only need to reserve through the sharing platform and pay the corresponding fees to use the drones. This greatly reduces the user's usage cost and improves the convenience of use. The sharing platform monitors the status and location of the drones in real time, and can discover and handle potential safety problems in a timely manner. At the same time, through the unified management and maintenance of the drones, their performance and safety can be ensured, reducing the risks caused by equipment failures. This sharing management method helps to promote the popularization and development of the drone industry. By reducing the usage threshold and cost, more individuals and enterprises can access drone technology, thus promoting the innovation and progress of related technologies and applications. Users can easily reserve and use drones through the sharing platform without worrying about the purchase, maintenance, and management of the equipment. At the same time, functions such as real-time monitoring and return operations provided by the platform also enhance the user's usage experience. Shared drones reduce the number of drones owned by individuals, thus reducing resource consumption and waste generation. This meets the current social requirements for environmental protection and sustainable development.

[0027] In a preferred embodiment of the present invention, the above Step 1, providing a drone sharing platform and allowing users to reserve and use drones through the sharing platform, may include: Build a drone sharing platform, which should have basic functions such as user registration, login, reservation, payment, and usage monitoring. The platform integrates multiple drone resources to ensure that drones of different models and performances can meet the needs of different users. Users register on the sharing platform, fill in necessary personal information, and create an account. After successful registration, users can log in to the platform using their accounts. After logging in, users can browse the available drone resources on the platform and select a suitable drone for reservation according to their needs. When making a reservation, the usage time and location need to be specified. The platform reviews the user's reservation request. Once the review is passed, the user will receive a reservation success notification and needs to complete the payment within the specified time. Payment methods can include credit cards, Alipay, WeChat Pay, etc.

[0028] At the appointed time and place, the user can obtain the drone by virtue of the reservation information and identity verification. During the use process, the platform will monitor the status and location of the drone in real time to ensure safe use. After the use is completed, the user needs to return the drone to the designated location and conduct necessary inspections. The platform will settle the fees according to factors such as the use time and drone model, and deduct the corresponding fees from the user's account. The platform needs to regularly maintain and service the drone to ensure its good performance and safety and reliability. The platform should provide user support services, answer questions encountered by users during the use process, and provide assistance and guidance. The platform should collect and analyze user usage data to optimize the allocation of drone resources, improve service quality, and enhance the user experience.

[0029] In a preferred embodiment of the present invention, step 2, establishing a user account system on the sharing platform and recording the user's reservation, usage, and payment information may include: The user fills in personal information on the sharing platform, such as name, email address, mobile phone number, etc., and sets an account password to complete the registration process. To ensure account security, the platform will send verification information to the email or mobile phone provided by the user, and the user needs to complete the verification according to the prompts. The user can log in to their account to view and modify personal information, such as password reset, binding or unbinding payment methods, etc. After logging in, the user can view all available drone resources on the platform, including information such as drone models, performance parameters, usage fees, etc. After the user selects a favorite drone, they need to submit a reservation application, including key information such as the reserved time period and usage location. The platform reviews the user's reservation application. Once the review is passed, the reservation information will be recorded in the user's account, and a corresponding reservation confirmation notice will be generated.

[0030] During the reserved time period, the user arrives at the designated usage location and receives the drone after passing identity verification. During the user's use of the drone, the platform will monitor information such as the flight status and location of the drone in real time to ensure safe use. Each use of the user will be recorded in detail, including information such as use time, location, and drone status, for convenient subsequent query and management. According to factors such as the drone model used by the user and the use time, the platform will automatically calculate the fees to be paid. The user can choose various payment methods (such as credit card, Alipay, WeChat Pay, etc.) to pay the fees, and the payment information will be securely encrypted and recorded in the user's account. The user logs in to their account to view all payment records, including detailed information such as payment time, payment amount, and payment method. Sensitive data such as the user's personal information, reservation records, usage records, and payment records are protected and stored and transmitted using encryption technology. Only authorized personnel can access sensitive data to ensure data security and privacy.

[0031] In a preferred embodiment of the present invention, for each ant, the next food source to be served is determined based on the pheromone concentration and heuristic information, including: For each ant, according to the pheromone concentration and heuristic information, Identify the next food source to serve; in, Indicates at time ,Ant Select slave nodes Move to Node probability; Indicates at time , from the node To Node pheromone concentration along the path; Represents a slave node To Node The heuristic information is proportional to the inverse of the distance between two nodes; It is a parameter of the importance of pheromone; is a parameter of the importance of heuristic information; Represents ants The set of nodes that have not been visited yet; Represents a slave node To Node Visibility on the path, indicating that the node and nodes The reciprocal of the distance between is a parameter; Indicates at time ,Ant Nodes that have been visited and The congestion of the associated path is a value between 0 and 1, where 0 means the path is completely uncongested and 1 means the path is completely blocked; is a parameter; Indicates at time , from the node To Node pheromone concentration along the path; Represents a slave node To Node The heuristic information is proportional to the inverse of the distance between two nodes; Represents a slave node To Node Visibility on the path; Indicates at time ,Ant Nodes that have been visited and The congestion degree of the relevant path is a value between 0 and 1; represents the current ant at the node where it is located; represents the ant for the next possible selected node; is the index of the ant; is the index of another node.

[0032] In the embodiment of the present invention, this method realizes the optimized allocation of UAV resources by simulating the process of ants looking for food. The ant algorithm is a heuristic algorithm that can find an approximate optimal solution among multiple possible solutions, so as to ensure that UAVs can be efficiently and reasonably allocated to each reservation. This method has strong adaptability. By updating the pheromone concentration and heuristic information, the algorithm can adjust the allocation scheme of UAVs in real time to adapt to the changing reservation requirements and UAV states. Through the intelligent allocation algorithm, it can be ensured that UAVs can respond to reservation requirements more quickly, reduce waiting time and empty flight time, thereby improving the overall efficiency of the system. Users can quickly and conveniently reserve UAVs through the sharing platform, and through the intelligent allocation algorithm, it can be ensured that users can obtain UAV services in the shortest time, greatly improving the user experience. By optimizing the allocation and management of UAVs, the idle time and maintenance cost of UAVs can be reduced, thereby reducing the operating cost of the sharing platform.

[0033] In a preferred embodiment of the present invention, step 3 above, when specifically applied, may include: Create a two-dimensional pheromone matrix, where the elements represent the pheromone concentration of each UAV (ant) to each reservation (food source). At the beginning of the algorithm, the elements of this matrix are initialized to uniformly distributed values, meaning that the initial attraction of all paths is the same.

[0034] Calculate the heuristic information. The heuristic information is based on specific knowledge of the problem to help guide the search process. In this scenario, the heuristic information is the distance from the UAV to the reservation; according to the time, location and type of the reservation, as well as the current position, status and maintenance situation of the UAV, calculate the straight-line distance or estimated flight time from each UAV to each reservation as the heuristic information. This information helps the ant (UAV) to be more inclined to select a reservation that is closer or easier to reach during the search process.

[0035] Ant path construction. Each ant (representing a UAV) starts to construct its own path. The path represents the sequence of reservations served by the UAV. For each ant, according to its current position (starting node), use the pheromone matrix and heuristic information to calculate the probability of selecting the next reservation (food source). According to the calculated selection probability, randomly determine the reservation that the ant will serve next.

[0036] The ant continues this process until it constructs a complete sequence of reservation services or meets other stopping conditions (such as reaching the maximum number of reservations); when all ants have completed their path construction, the algorithm evaluates the total cost of each path (such as total flight time, total distance, etc.); according to the cost of the path, the pheromone matrix is updated. More pheromone is added to the paths with lower costs, while the pheromone on the paths with higher costs is reduced or evaporated. This update process mimics the behavior of real ants releasing pheromones when searching for food, making the better paths more likely to be selected in subsequent iterations.

[0037] Repeat the above ant path construction and pheromone update process multiple times (i.e., iterate) until the stopping condition is met (such as reaching the maximum number of iterations). In each iteration, the algorithm tries to find a more optimized drone allocation scheme; according to the finally determined pheromone matrix and heuristic information, corresponding drones are allocated for each reservation. Usually, the path with the highest pheromone concentration and the best heuristic information (i.e., the shortest distance or the lowest cost) is selected to allocate drones.

[0038] Through the above process, step 3 can utilize the self-organization and positive feedback characteristics of the ant algorithm to find an approximately optimal drone allocation scheme, thus effectively meeting the needs of multiple reservations.

[0039] In a preferred embodiment of the present invention, for step 3 above, according to the final drone allocation scheme, the sharing platform sets the usage rules and fee standards for the drones and publicizes the usage rules and fee standards on the sharing platform, which may include: Step 31, analyze the reservation information, including the type of drone, reservation duration, and reservation frequency, and formulate the usage rules and fee standards for the drones; Step 32, input the formulated usage rules and fee standards into the background management system of the sharing platform, and automatically calculate the fees according to the usage duration and fee standards; Step 33, add a page for the usage rules and fee standards to the user interface of the sharing platform, and publicize the usage rules and fee standards on the sharing platform.

[0040] In the embodiments of the present invention, the sharing platform first collects and analyzes the reservation information of users, including the type of drones reserved by users, the reservation duration, and the reservation frequency. Through data analysis, the platform can understand the demand patterns and preferences of users, providing a basis for formulating reasonable usage rules and fee standards. Based on the analysis of the reservation information, the platform formulates corresponding usage rules, such as the usage time period of drones, the usage scope, and safety operation specifications. At the same time, different fee standards are set according to factors such as the type of drones, maintenance costs, and market demand. The formulated usage rules and fee standards are entered into the background management system of the sharing platform. This system can automatically calculate the fees to be paid according to the reservation duration selected by the user and the type of drones selected, in accordance with the set fee standards. On the user interface of the sharing platform, dedicated pages for usage rules and fee standards are added. Users can clearly view the usage rules and corresponding fee standards of various drones on these pages to make appropriate choices.

[0041] By publicizing the usage rules and fee standards, the transparency of the platform is increased, ensuring that users can clearly understand the fees they pay and the services they enjoy. This helps to build user trust and improve the fairness and credibility of the platform. Based on the analysis of the reservation information, the platform can more accurately match user needs and optimize resource allocation. By setting reasonable fee standards, it can encourage users to use drone resources more efficiently and reduce waste. The automated fee calculation and management system improves the operation efficiency of the platform, reducing human errors and costs. Clear usage rules and fee standards also help to reduce additional costs caused by misunderstandings or disputes. The clear display on the user interface enables users to easily understand and use the services, enhancing the user experience. This helps to attract more users and promote the sustainable development of the platform.

[0042] In a preferred embodiment of the present invention, in step 4 above, where the user confirms the reservation information and pays the corresponding fees, and the sharing platform records the payment situation of the user and completes the calculation and collection of the fees, it may include: Step 41, the user views and selects the drone reservation information on the sharing platform, including the reservation time, location, and drone model; Step 42, the sharing platform automatically calculates the total fees to be paid according to the reservation duration selected by the user, the drone model, and the set fee standards; Step 43, according to the calculated total fees to be paid, the user selects a payment method and completes the payment operation according to the guidance on the payment interface; Step 44, after the payment is successful, the sharing platform records the payment information in the payment record form, including the payment time, payment method, and payment amount information, and settles with the payment service provider to determine that the payment amount is transferred to the account of the sharing platform, completing the calculation and collection of the fees.

[0043] In an embodiment of the present invention, users can view all reservable drone information on the sharing platform, including available time slots, pick-up locations, and different drone models. According to their own needs, users can select a suitable reservation time, location, and drone model on the platform. After the user selects the reservation duration and drone model, the sharing platform will automatically calculate the total fee that the user should pay based on this information and the fee standard set in the background. This calculation process is real-time, and users can view the detailed fee breakdown before confirming the reservation information. Based on the calculated total fee, users can choose a payment method suitable for themselves, such as credit card, Alipay, WeChat Pay, etc. The user enters the payment password according to the prompts on the payment interface. After successful payment, the sharing platform will immediately update the payment status and record the relevant payment information (such as payment time, payment method, payment amount, etc.) in the payment record table. At the same time, the sharing platform will settle accounts with the payment service provider to ensure that the payment amount is correctly transferred to the platform's account.

[0044] Users can complete the entire process from reservation to payment on one platform without having to jump to other applications or websites, improving the convenience of use. Automated fee calculation reduces the trouble of manual calculation by users and makes the reservation process more efficient. Through the system's automatic calculation, the accuracy of fee calculation can be ensured, avoiding disputes caused by human calculation errors. Automated management of payment records also improves the accuracy of accounts, facilitating subsequent financial reconciliation and auditing. The payment process, in cooperation with well-known payment service providers, ensures the security and reliability of transactions. Encrypted storage and transmission of payment information ensure the security of user data. The smooth reservation and payment process enhances the overall user experience, making users more willing to use the services of the sharing platform. Detailed payment records and transparent fee calculation also enhance users' trust in the platform.

[0045] In a preferred embodiment of the present invention, for step 5 above, where the sharing platform designates a corresponding drone for the user to use according to the user's payment reservation information, it may include: Step 51, the sharing platform collects the status information of currently available drones, including the real-time location, performance parameters, maintenance status, and last use time of the drones; Step 52, the sharing platform extracts the user's reservation information, including the reservation time, reservation location, and estimated use time; Step 53, based on the status information of the drones, the sharing platform calculates an availability score for each drone; Step 54, compare the performance requirements in the user's reservation information with the availability scores of each drone to determine the drone list; Step 55: Calculate the straight-line distance between the user's reservation location and the current position of each available drone, and calculate a comprehensive matching degree for each drone based on the drone's availability score and the distance factor. Step 56: Based on the comprehensive matching degree, the sharing platform selects drones from the drone list for the user to use.

[0046] In the embodiment of the present invention, the sharing platform first collects the status information of all currently available drones. These status information include: the real-time position of the drone, performance parameters (such as flight speed, payload capacity, battery life, etc.), maintenance status (such as whether maintenance is required, the last maintenance time, etc.), and the last use time. Then, the platform extracts the user's reservation information, mainly including the reservation time, reservation location (i.e., the drone extraction or use location), and the estimated use time. According to the collected drone status information, the platform calculates an availability score for each drone. This score is based on various factors, such as the drone's performance parameters, maintenance status, battery life, and the idle time since the last use. The platform compares the performance requirements in the user's reservation information (such as flight speed, payload requirements, etc.) with the availability score of each drone. Only the drones that meet the user's performance requirements will be included in the candidate list. For each drone in the candidate list, the platform calculates the straight-line distance between the user's reservation location and the current position of the drone. Combining the availability score of the drone and the distance factor, a comprehensive matching degree is calculated for each drone. This comprehensive matching degree reflects the distance of the drone from the user's reservation location and the availability of the drone itself while meeting the user's needs. Finally, according to the level of the comprehensive matching degree, the sharing platform selects the most suitable drone from the drone list for the user to use. The drone with the highest matching degree will be assigned to this user to ensure that their needs are met.

[0047] Through the automated drone selection and matching process, it reduces manual intervention and decision-making time, and improves the efficiency of drone scheduling. Considering various factors such as the performance, maintenance status, and location of the drone comprehensively, it ensures the optimal allocation of resources, meets the user's needs while reducing unnecessary transportation and waiting time. Users can obtain drone services that meet their needs faster and more accurately, improving user satisfaction and experience. Through intelligent scheduling and management, it reduces the empty running time and maintenance costs of the drone, and improves the overall operation efficiency. It can dynamically adjust the allocation of drones according to the actual situation, respond to emergencies and demand changes, and improve the flexibility and adaptability of the system.

[0048] In a preferred embodiment of the present invention, the calculation formula for the availability score is: ; Wherein, represents the availability score; , represents the weight coefficient; represents the performance of the drone; , represents the weight; represents the remaining time; represents the total time; represents the maintenance status; represents the linear rate of performance decay; represents the acceleration of the decay rate; represents the time since the last maintenance; represents the maintenance interval.

[0049] In an embodiment of the present invention, represents the performance of the drone, including factors such as flight speed and payload capacity. The higher the performance, the higher the availability score of the drone will be correspondingly. represents the remaining flight time of the drone, while represents its total flight time. This ratio reflects the proportion of time the drone can still be used and has a direct impact on the availability score. represents the maintenance status of the drone. A good maintenance status means higher reliability, thus enhancing the availability score. At the same time, the formula takes into account the time since the last maintenance and the maintenance interval , as well as the linear rate of performance decay and the acceleration of the decay rate , to more accurately evaluate the impact of the maintenance status on the drone's availability.

[0050] Among them, the performance of the drone is calculated by the formula: ; Among them, , , and are weights; , and are the actual position coordinates of the drone in the flight test; , and are the target position coordinates of the drone; is the maximum allowable position deviation; n is the number of test points, that is, the number of data points collected in the flight test; is the actual flight time of the drone; is the maximum flight time of the drone; is the weight currently carried by the drone; is the maximum weight that the drone can carry; is the actual response time of the drone to control commands; is the maximum allowed response time.

[0051] Performance of the drone Ensures that users can obtain drones with excellent performance, thereby improving the efficiency and success rate of task execution. The remaining flight time of the drone and the total time The ratio can ensure that users obtain drones with sufficient endurance, reducing the risk of task interruption due to insufficient power. Good maintenance status means that the drone is more reliable and safe, can reduce the probability of failure, and improve user trust and satisfaction. By considering the usage time of the drone since its last maintenance , the possible performance degradation can be predicted, thus ensuring that users obtain drones in good condition. Temperature and the temperature coefficient , , The impact on the performance of the drone can provide users with the most suitable drone under different environmental conditions, ensuring the stability and efficiency of task execution.

[0052] In a preferred embodiment of the present invention, the formula for calculating the straight-line distance between the reservation location and the current position of each available drone is: ; where, represents the straight-line distance between the reservation location and the current position of each available drone; represents the radius of the earth; represents the difference in latitude between the reservation location and the current position of the drone; represents the latitude of the reservation location; represents the latitude of the current position of the drone; represents the difference in longitude between the reservation location and the current position of the drone; represents the arcsine function.

[0053] In an embodiment of the present invention, represents the difference in latitude between the reservation location and the current position of the drone. represents the difference in longitude between the reservation location and the current position of the drone. reflects the impact of latitude change on the straight-line distance. reflects the impact of longitude change on the straight-line distance at different latitudes. Taking the square root of the above sum and then applying the arcsine function Calculate the angle corresponding to this value. This angle reflects the included angle between two rays from the center of the Earth to the reserved location and the position of the drone. Finally, multiply this angle by the radius of the Earth , to obtain the straight-line distance between the reserved location and the current position of the drone . This is because the Earth can be approximately regarded as a sphere, and the shortest distance between two points on the spherical surface (i.e., the great circle distance) can be calculated by the product of the central angle of the sphere and the radius of the Earth.

[0054] By calculating the distance between the reserved location and the drone, the flight path of the drone can be planned more effectively. This avoids unnecessary flights and time waste, and improves the overall work efficiency. When multiple drones perform tasks simultaneously, the distance that each drone reaches the reserved location can be accurately evaluated, so as to reasonably allocate tasks, ensure that the nearest drone is dispatched first, and reduce energy consumption and flight time. In emergency situations, such as search and rescue missions, quickly determining the straight-line distance between the drone and the incident location is crucial. This formula can provide accurate distance information in the first time to help decision-makers respond quickly. Precise distance calculation helps the drone avoid potential collisions with other obstacles or aircraft during flight, thus enhancing flight safety. Accurate distance assessment helps reduce unnecessary flight mileage, thereby reducing fuel consumption and maintenance costs. In the delivery service, customers expect faster delivery times. By accurately calculating the distance through this formula, the delivery time can be more accurately estimated, thus enhancing customer satisfaction.

[0055] In a preferred embodiment of the present invention, the comprehensive matching degree calculation formula is:[[]] ; wherein, represents the comprehensive matching degree; represents the availability score; represents the weight; represents the usage time impact factor; represents the performance of the drone; represents the configuration score impact factor; represents the distance between the drone and the user's reserved location; represents the distance weight; represents the energy consumption impact factor; Maintenance status impact factor; represents the distance impact factor; represents the load capacity impact factor.

[0056] In the embodiment of the present invention, the availability score reflects the usable state of the drone, such as whether it is in good working condition, whether it needs maintenance, etc. The weight Indicates the importance of this factor in the overall assessment. If usability is crucial, the weight will be relatively high. Usage time impact factor Considers the time the drone has been used, which may affect its remaining lifespan and performance. The performance of the drone Reflects the performance metrics of the drone, such as flight speed, stability, etc. Configuration scoring impact factor Then reflects the hardware configuration of the drone, such as camera quality, sensor accuracy, etc. The distance between the drone and the user's appointed location Is a key factor as it directly affects the time for the drone to reach the appointed location and energy consumption. Distance weight Reflects the importance of distance in the overall matching degree. For tasks that require quick response, this weight may be higher. Energy consumption impact factor Considers the energy consumption situation of the drone during mission execution. Maintenance status impact factor Reflects the maintenance history and quality of the drone, which have an impact on performance and reliability. Distance impact factor Further adjusts the impact of distance on the overall matching degree, especially when considering the sensitivity of different tasks to distance. Payload capacity impact factor Then reflects the ability of the drone to carry equipment or supplies.

[0057] When applied specifically, the calculation process of the usability score (A): Determine the evaluation indicators: Working status, check whether the drone is in normal working condition without faults or damages.

[0058] Maintenance records, check the maintenance history of the drone to understand whether there are frequent repairs or major faults.

[0059] Component condition, evaluate the condition and remaining lifespan of the drone's key components (such as batteries, engines, propellers, etc.).

[0060] Software update, confirm whether the drone's software system is the latest version and whether there are known security risks.

[0061] Set weights and scoring criteria for each indicator: For example, the working status may account for the largest weight as it directly affects whether the drone can be immediately put into use. The maintenance records may have a medium weight as they reflect the reliability and maintenance cost of the drone. The weights of component condition and software update may be lower, but they are still factors to be considered when evaluating usability.

[0062] Conduct actual evaluation: Conduct on-site inspections for each indicator or query relevant data records. Score each indicator according to the preset scoring criteria. For example, a good working condition may receive full marks, minor repairs may result in a certain deduction of points, and major repairs may lead to a greater deduction of points. Multiply the score of each indicator by its corresponding weight. Add up all the weighted scores to obtain the availability score (A) of the drone.

[0063] When specifically applied, the calculation process of the usage time impact factor: First, determine the total designed flight duration of the drone, for example, it is 2000 flight hours; then, record how many hours the drone has flown so far, for example, it has flown 800 hours. The usage time impact factor can be calculated in the following way: Subtract the flown duration from the total designed flight duration, and then divide by the total designed flight duration, that is, (2000 - 800) / 2000 = 0.6. The larger this value, the longer the remaining service life of the drone.

[0064] The calculation process of the configuration score impact factor: List the main hardware configurations of the drone, such as: high-definition camera, high-precision GPS, etc.; according to the advancement and importance of each hardware, determine the corresponding value for each hardware, for example, if the camera is very advanced, it corresponds to 9 points, and if the GPS accuracy is average, it corresponds to 7 points; add up the scores of all hardware to obtain the total configuration score, for example, 9 points for the camera plus 7 points for the GPS equals 16 points. Finally, this total score can be converted into the configuration score impact factor. For example, the highest possible configuration score is 30 points, then the configuration score impact factor of the current drone is 16 / 30.

[0065] The calculation process of the energy consumption impact factor: Under the same flight conditions, test the power consumption of the drone when flying 100 kilometers. Assume it consumes 2 degrees of electricity. Determine a standard energy consumption value, for example, the average power consumption of similar drones when flying 100 kilometers is 2.5 degrees of electricity. The energy consumption impact factor is the standard energy consumption value divided by the actual energy consumption value, that is, 2.5 / 2 = 1.25. A value greater than 1 indicates that the energy consumption performance of this drone is better.

[0066] The calculation process of the distance impact factor: Determine the actual distance between the drone and the reserved location, for example, it is 50 kilometers. Set the maximum distance the drone can fly, for example, it is 100 kilometers. The distance impact factor can be calculated by dividing the maximum distance it can fly by (the maximum distance it can fly plus the actual distance), that is, 100 / (100 + 50) = 0.67. The larger this value, the smaller the impact of distance on the mission.

[0067] The calculation process of the load capacity impact factor: Determine the maximum takeoff weight of the drone, for example, it is 10 kg. Determine the weight of the equipment that the drone needs to carry for this mission, for example, it is 4 kg. The load capacity impact factor can be calculated by (maximum takeoff weight minus mission load weight) divided by the maximum takeoff weight, that is, (10 - 4) / 10 = 0.6. The larger this value is, the greater the load margin of the drone in this mission.

[0068] By calculating the comprehensive matching degree, the most suitable drone for performing a specific mission can be quickly and accurately identified. This avoids the traditional manual screening and comparison process and improves the efficiency of mission allocation. The formula comprehensively considers multiple factors such as the availability, performance, configuration, and distance of the drone to ensure the optimal allocation of resources. This helps to reduce resource waste and improve the overall operation efficiency. Since the comprehensive matching degree formula can comprehensively evaluate the performance indicators of the drone, the selected drone is more likely to successfully complete the mission. This reduces the risk of mission failure and improves the success rate of the mission. The comprehensive matching degree score provided by the formula provides a quantitative and objective reference basis for decision-makers, reduces the error caused by subjective judgment, and enhances the accuracy and scientific nature of decision-making. By precisely matching the most suitable drone to perform the mission, unnecessary flights and repeated attempts can be reduced, thereby reducing operating costs such as fuel consumption and maintenance costs. In the service industry, such as drone delivery, selecting the most suitable drone through the comprehensive matching degree can complete customer orders faster and more accurately, thereby improving customer satisfaction.

[0069] As Figure 2 shown, an embodiment of the present invention further provides a drone sharing management system 20, including: An acquisition module 21 is used to provide a drone sharing platform, allowing users to reserve and use drones through the sharing platform; establish a user account system on the sharing platform to record users' reservation, usage, and payment information; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones; create a pheromone matrix representing the pheromone concentration from each drone to each reservation, initially set to a uniform distribution, where the drones are ants and the reservation information is the food source; calculate the heuristic information based on the reservation time, location, and drone type, as well as the drone's location, status, and maintenance situation, and the heuristic information is the distance from the drone to the reservation; for each ant, determine the next food source to serve based on the pheromone concentration and heuristic information, and each ant constructs a path, which represents the sequence of reservations served by the ant; when all ants have completed path construction, update the pheromone matrix according to the total cost of each path, and repeat the iteration to obtain the final determined allocation plan, and allocate the corresponding drone to each reservation according to the final determined allocation plan; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones and publicizes the usage rules and fee standards on the sharing platform; A processing module 22 is used for users to confirm reservation information and pay the corresponding fees. The sharing platform records the users' payment situation and completes the calculation and collection of fees; the sharing platform designates the corresponding drone for the user to use according to the reservation information paid by the user; during the user's use of the drone, the sharing platform monitors the status and location of the drone in real time. After the use ends, the drone is returned through the sharing platform and the calculation of the usage fee ends; A scheduling module 23 is used for automatically allocating and scheduling drones and closely cooperating with the processing module to perform intelligent scheduling according to drone location and status factors; A user management module 24 is used to handle users' operations, including registering new users, user login, and personal information management, and manage user permissions; A payment processing module 25 is used to handle the fee settlement and payment process for drone use and cooperate with the processing module to determine the correct calculation and timely collection of fees; An order management module 26 is used to receive and respond to users' requests for using drones, track the status of each order, and cooperate with the scheduling module and the processing module to determine that the drone completes the tasks specified by the user.

[0070] It should be noted that this system corresponds to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0071] An embodiment of the present invention further provides a computing device, including: a processor and a memory storing a computer program. When the computer program is run by the processor, the above-mentioned method is executed. All implementation manners in the above method embodiments are applicable to this embodiment and can also achieve the same technical effects.

[0072] An embodiment of the present invention further provides a computer-readable storage medium storing instructions. When the instructions are run on a computer, the computer is caused to execute the above-mentioned method. All implementation manners in the above method embodiments are applicable to this embodiment and can also achieve the same technical effects.

[0073] The above are the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for shared management of unmanned aerial vehicles, characterized in that, The method includes: Providing a drone sharing platform and allowing users to reserve and use drones through the sharing platform; Establishing a user account system on the sharing platform to record users' reservation, usage, and payment information; Creating a pheromone matrix representing the pheromone concentration of each drone to each reservation, initially set to a uniform distribution, where the drones are ants and the reservation information is the food source; calculating heuristic information based on the reservation time, location, and drone type, as well as the drone's position, status, and maintenance situation, and the heuristic information is the distance from the drone to the reservation; For each ant, determining the next food source to serve based on the pheromone concentration and heuristic information, and each ant constructs a path, where the path represents the sequence of reservations served by the ant; after all ants have completed path construction, update the pheromone matrix according to the total cost of each path, and repeat the iteration to obtain the finally determined allocation plan, and allocate the corresponding drone to each reservation according to the finally determined allocation plan; According to the finally determined drone allocation plan, the sharing platform sets the usage rules and fee standards for the drones; The user confirms the reservation information and pays the corresponding fee, the sharing platform records the user's payment situation, and completes the calculation and collection of the fee; The sharing platform designates the corresponding drone for the user to use according to the reservation information paid by the user; During the user's use of the drone, the sharing platform monitors the status and location of the drone in real time. After the use is over, the drone is returned through the sharing platform, and the calculation of the usage fee ends.

2. The drone sharing management method according to claim 1, wherein For each ant, determining the next food source to serve based on the pheromone concentration and heuristic information, including: For each ant, based on the pheromone concentration and heuristic information, determine the next food source to serve through ​ in, Indicates at time ,Ant Select slave nodes Move to Node probability; Indicates at time , from the node To Node pheromone concentration along the path; Represents a slave node To Node The heuristic information is proportional to the inverse of the distance between two nodes; It is a parameter of the importance of pheromone; is a parameter of the importance of heuristic information; Represents ants The set of nodes that have not been visited yet; Represents a slave node To Node Visibility on the path, indicating that the node and nodes The reciprocal of the distance between is a parameter; Indicates at time ,Ant Nodes that have been visited and The congestion of the associated path is a value between 0 and 1, where 0 means the path is completely uncongested and 1 means the path is completely blocked; is a parameter; Indicates at time , from the node To Node pheromone concentration along the path; Represents a slave node To Node The heuristic information is proportional to the inverse of the distance between two nodes; Represents a slave node To Node Visibility on the path; Indicates at time ,Ant Nodes that have been visited and The congestion of the associated path is a value between 0 and 1; Represents the current ant The node where it is located; Representing ants The next possible node to be selected; is the index of ants; is the index of another node.

3. The drone sharing management method according to claim 2, wherein According to the finally determined drone allocation plan, the sharing platform sets the usage rules and fee standards for the drones and publicizes the usage rules and fee standards on the sharing platform, including: Analyzing the reservation information, including the drone type, reservation duration, and reservation frequency, and formulating the usage rules and fee standards for the drones; Entering the formulated usage rules and fee standards into the background management system of the sharing platform and automatically calculating the fee according to the usage duration and fee standards; Adding a page for the usage rules and fee standards to the user interface of the sharing platform and publicizing the usage rules and fee standards on the sharing platform.

4. The drone sharing management method according to claim 3, wherein The user confirms the reservation information and pays the corresponding fee, the sharing platform records the user's payment situation, and completes the calculation and collection of the fee, including: The user views and selects the drone reservation information on the sharing platform, including the reservation time, location, and drone model; The sharing platform automatically calculates the total fee to be paid according to the selected reservation duration, drone model, and set fee standards; According to the calculated total fee to be paid, the user selects a payment method and completes the payment operation according to the instructions on the payment interface; After the payment is successful, the sharing platform records the payment information in the payment record table, including the payment time, payment method, and payment amount information, and settles with the payment service provider to determine that the payment amount is transferred to the account of the sharing platform, completing the calculation and collection of the fee.

5. The drone sharing management method according to claim 4, characterized in that, The sharing platform designates the corresponding drone for the user to use according to the reservation information paid by the user, including: The sharing platform collects the status information of currently available drones, including the real-time location, performance parameters, maintenance status, and last usage time of the drones; The sharing platform extracts the reservation information of users, including the reservation time, reservation location, and estimated usage time; Based on the status information of the drones, the sharing platform calculates an availability score for each drone; Compare the performance requirements in the user reservation information with the availability scores of each drone to determine a list of drones; Calculate the straight-line distance between the user reservation location and the current location of each available drone, and calculate a comprehensive matching degree for each drone based on the availability score of the drone and the distance factor; Based on the comprehensive matching degree, the sharing platform selects drones from the drone list for users to use.

6. The drone sharing management method according to claim 5, wherein The calculation formula for the availability score is: ; Among them, represents the usability score; , represents the weight coefficient; represents the performance of the drone; , , represent the weights; represents the remaining time; represents the total time; represents the maintenance status; represents the linear rate of performance decay; represents the acceleration of the decay rate; represents the time since the last maintenance; represents the maintenance interval.

7. The drone sharing management method according to claim 6, wherein The calculation formula for the straight-line distance between the reservation location and the current location of each available drone is: ; Among them, represents the straight-line distance between the reservation location and the current position of each available drone; represents the radius of the Earth; represents the difference in latitude between the reservation location and the current position of the drone; represents the latitude of the reservation location; represents the latitude of the current position of the drone; represents the difference in longitude between the reservation location and the current position of the drone; represents the arcsine function.

8. The drone sharing management method according to claim 7, wherein The calculation formula for the comprehensive matching degree is: ; Among them, represents the comprehensive matching degree; represents the usability score; represents the weight; represents the usage time impact factor; represents the performance of the drone; represents the configuration score impact factor; represents the distance between the drone and the user's appointment location; represents the distance weight; represents the energy consumption impact factor; maintenance status impact factor; represents the distance impact factor; represents the load capacity impact factor.

9. A drone sharing management system, characterized in that, Applied to the method described in any one of claims 1 to 8, including: An acquisition module, used to provide a drone sharing platform and allow users to reserve and use drones through the sharing platform; establish a user account system on the sharing platform to record users' reservation, usage, and payment information; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones; create a pheromone matrix representing the pheromone concentration of each drone to each reservation, initially set to a uniform distribution, where the drones are ants and the reservation information is the food source; calculate the heuristic information according to the reservation time, location, and drone type, as well as the location, status, and maintenance of the drones, and the heuristic information is the distance from the drone to the reservation; for each ant, determine the next food source to serve according to the pheromone concentration and heuristic information, and each ant will construct a path, and the path represents the sequence of reservations served by the ant; when all ants have completed path construction, update the pheromone matrix according to the total cost of each path, repeat the iteration to obtain the final determined allocation plan, and allocate the corresponding drones to each reservation according to the final determined allocation plan; according to the final drone allocation plan, the sharing platform sets the usage rules and fee standards for drones and publicizes the usage rules and fee standards on the sharing platform; A processing module, used for users to confirm the reservation information and pay the corresponding fees, the sharing platform records the payment situation of users, and completes the calculation and collection of fees; the sharing platform designates the corresponding drones for users to use according to the reservation information paid by users; during the period when users use drones, the sharing platform monitors the status and location of drones in real time, and when the use ends, returns the drones through the sharing platform and ends the calculation of usage fees; A scheduling module, used for automatically allocating and scheduling drones, and closely cooperating with the processing module to perform intelligent scheduling according to drone location and status factors; A user management module, used to handle user operations, including registering new users, user login, and personal information management, and manage user permissions; A payment processing module, which is used to handle the fee settlement and payment process for the use of the drone, and cooperate with the processing module to determine the correct calculation and timely collection of fees; An order management module, which is used to receive and respond to the user's request for using the drone, track the status of each order, and work together with the scheduling module and the processing module to determine that the drone completes the tasks specified by the user.

10. A computing device, characterized in that, Comprising: One or more processors; A storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the method according to any one of claims 1 to 8.

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