Low-altitude economy cloud platform service encapsulation and dynamic combination charging system and method

Abstract

The application discloses a low-altitude economy cloud platform service packaging and dynamic combination charging system and method, relates to the technical field of low-altitude economy service management and charging, and comprises the following steps: a service packaging module encapsulates low-altitude core capabilities into standardized APIs and generates documents; a service arrangement module combines services through a visual interface, intelligently analyzes dependencies and provides fault-tolerant compensation; a multi-dimensional charging module collects multi-dimensional resource consumption data and generates detailed account bills; an open gateway and service market module provides unified access and service subscription management; a resource adaptation layer integrates basic capabilities and adapts to heterogeneous devices; a developer ecological support module provides whole-process development and profit sharing support; and a system operation and maintenance module guarantees stable operation and elastic scaling of the platform. The application reduces the development threshold through standardized packaging, accelerates application innovation through visual arrangement, and improves resource utilization efficiency through multi-dimensional charging; the application has high stability and adaptability, and realizes efficient operation and large-scale development of low-altitude economy services.

Description

Low-altitude economic cloud platform service encapsulation and dynamic combination billing system and method Technical Field

[0001] This invention relates to the field of low-altitude economic service management and billing technology, and in particular to a low-altitude economic cloud platform service encapsulation and dynamic combination billing system and method. Background Technology

[0002] With the deep penetration of drones, eVTOL aircraft, and other aircraft into scenarios such as logistics delivery, power line inspection, air travel, and aerial photography for cultural tourism, the low-altitude economy has become an important growth point for the integration of the digital economy and the real economy. To adapt to the diverse needs of low-altitude operations, various low-altitude management platforms have gradually emerged, but the industry as a whole is still in a stage of fragmented development and has not yet formed a standardized and open industrial ecosystem. Existing platforms are mainly divided into two categories: one is a vertically closed platform, which is developed by a single entity such as a logistics company or inspection agency, and is only adapted to its own business scenario. It has a single function but extremely poor scalability, and core resources such as airspace, computing, and communication cannot be shared across entities; the other is a basic management platform, which focuses on basic functions such as airspace application and flight monitoring, and has not standardized and openly output its core capabilities. Third-party developers need to have in-depth knowledge of low-altitude management and multi-system interface specifications in order to develop innovative applications based on the platform.

[0003] The current low-altitude economy faces numerous significant pain points in its technology and operational models. Capability access is extremely difficult. Low-altitude operations involve multiple professional processes, including airspace application, meteorological assessment, path planning, and drone dispatch. Different systems have heterogeneous interfaces and inconsistent standards, requiring developers to invest considerable time learning professional knowledge and interface logic, resulting in long development cycles and high costs. Resource integration is challenging. A single complex task often requires the coordination of multiple resources such as airspace, flight, data, and computing, necessitating integration with multiple independent systems. This high integration complexity easily leads to data inconsistencies and process disruptions. Billing models are too rudimentary. Existing billing methods mostly use fixed charges per flight, monthly, or annually, failing to accurately reflect the actual costs consumed by developers, such as airspace volume, flight mileage, computing resources, and data transmission volume. This hinders optimal resource allocation and makes it difficult to support microservice-based platform operation and commercial monetization. An innovation ecosystem is severely lacking. There is a lack of standardized, self-service low-altitude service markets similar to those in cloud computing. The absence of efficient communication channels between capability providers and application developers limits the speed and breadth of low-altitude application innovation, hindering the large-scale development of the entire industry. These problems make it difficult for existing technologies to meet the needs of large-scale, market-oriented, and ecological development of the low-altitude economy. There is an urgent need to build a standardized and open platform architecture and methodology system for "low-altitude services as products". Summary of the Invention

[0004] The present invention proposes a low-altitude economic cloud platform service encapsulation and dynamic combination billing system and method to solve the problems mentioned in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a low-altitude economic cloud platform service encapsulation and dynamic combination billing system, comprising the following modules:

[0006] The service encapsulation module defines a unified low-altitude service meta-model, adapts to heterogeneous backend systems through the adapter pattern, encapsulates the core low-altitude capabilities into standardized APIs, provides a graphical service designer, and automatically generates complete API documentation.

[0007] The service orchestration module uses a directed acyclic graph to build a service composition workflow model, provides a visual orchestration interface, has a built-in intelligent orchestration engine to parse service dependencies and optimize the execution order, and has fault tolerance mechanisms and compensation transaction processing capabilities.

[0008] The multi-dimensional billing module deploys distributed metering probes to collect consumption data in real time, establishes a billing model that includes a basic rate table and dynamic adjustment factors, supports real-time calculation of service usage fees, and generates multi-dimensional detailed bills and summary bills.

[0009] The open gateway and service marketplace module provides unified API access, identity authentication, permission authentication, traffic control and protocol conversion functions, builds a categorized service marketplace catalog, supports service browsing, retrieval, subscription, trial and evaluation, and integrates protocol management, cost monitoring and budget early warning functions;

[0010] The resource adaptation layer integrates four services: airspace, flight, data, and computing, to achieve the abstraction and standardized output of basic capabilities, and adapts to the interface specifications and operating characteristics of different types of UAVs, eVTOL aircraft, and low-altitude equipment.

[0011] The developer ecosystem support module provides developer registration, real-name authentication, and hierarchical management functions, supports the entire process of application development, testing, deployment, and commercialization, establishes a service call revenue sharing mechanism and community communication platform, and provides technical documentation and case library resources.

[0012] The system operation and maintenance module monitors the operating status, resource usage, and service call quality of each module on the platform in real time. It provides log collection, centralized storage, fault alarms, and rapid location functions. It supports system elastic scaling and load balancing, automatically detects and repairs potential faults, and regularly generates operation and maintenance reports and optimization suggestions.

[0013] Furthermore, it also includes a service metamodel management module, which establishes a service metadata standard library, performs full lifecycle management of service metamodels including creation, modification, version iteration, and archiving, provides metamodel verification tools to verify the syntactic consistency of input and output specifications, the rationality of resource constraints, and the feasibility of SLA indicators, automatically detects the interface compatibility and resource conflict risks between new services and existing services, and supports metamodel version backtracking and difference comparison.

[0014] Furthermore, it also includes a fault tolerance compensation module, which has a preset fault classification and handling mechanism. Based on the fault type and severity, it automatically triggers the corresponding fault tolerance strategy: minor faults are retried, moderate faults are switched to a backup service provider, and severe faults initiate a service degradation process. At the same time, a transaction compensation mechanism is established to record the resource occupation status during the execution of combined services. When a task is interrupted or fails, it automatically performs space release, computing resource reclamation and data rollback operations, and generates an analysis report containing the cause of the fault, the scope of impact and the handling results.

[0015] Furthermore, it also includes a dynamic rate adjustment and billing optimization module, which adjusts dynamic factors of various resources in real time based on market supply and demand, airspace resource scarcity, and business scenario characteristics, constructing a multi-dimensional comprehensive billing formula. The calculation expression is as follows:

[0016]

[0017] in, For the total cost, For the first The actual consumption of such resources For the first Basic fee rate for similar resources For the first Duration of resource usage As a time-dynamic factor, For regional dynamic factors, As the SLA rating factor, As an urgency factor, This is a fixed service call fee.

[0018] Furthermore, it includes a testing sandbox and a rapid deployment module, providing a high-fidelity testing sandbox that simulates a low-altitude environment. It supports the injection of simulated airspace data, meteorological data, task orders, equipment status, and fault scenarios. Developers can conduct service calls, orchestration, functional testing, and stress testing in the sandbox. During the testing process, test reports containing call logs, performance metrics, and error statistics are generated in real time. After the test is passed, a one-click deployment function is provided to deploy the application as an elastically scalable microservice, automatically adapting to platform resource configurations and dynamically adjusting the number of instances based on business traffic. It supports blue-green deployment and rapid rollback.

[0019] Furthermore, it also includes an ecosystem revenue sharing management module, which establishes a revenue sharing model based on service call volume, revenue contribution, and service quality rating. It supports customized revenue sharing ratios among platforms, service providers, and application developers, allows setting multiple revenue sharing modes, automatically calculates the number of service calls, total fees, revenue sharing amount, and settlement cycle for each participant, generates detailed revenue sharing bills, supports automatic settlement and fund transfer on a daily, weekly, and monthly basis, provides revenue sharing data query, reconciliation, and dispute handling functions, and connects to mainstream payment channels and financial systems.

[0020] Furthermore, it also includes a data statistics and operation analysis module, which collects various types of data during the platform's operation, uses data analysis algorithms to uncover business hotspots, resource bottlenecks, user demand trends, and service quality shortcomings, generates operation analysis reports, and supports data visualization and custom report export.

[0021] Furthermore, the method for encapsulating and dynamically combining billing systems for low-altitude economic cloud platform services includes the following steps:

[0022] The service standardization encapsulation steps are based on a unified low-altitude service meta-model, defining service identifiers, functional descriptions, input / output specifications, resource constraints, and SLA metrics; using adapters to convert heterogeneous backend system interfaces into platform standard interfaces; and using a graphical designer to configure interface logic, exception handling processes, and resource adaptation rules, automatically generating complete API documentation.

[0023] The service composition orchestration steps involve dragging and dropping atomic services through a visual interface to build a directed acyclic graph-like service composition workflow, configuring dependencies and data flow between services, and having the intelligent orchestration engine automatically parse data and resource dependencies and optimize the execution order. Runtime context is injected to enable data transfer between services, and fault tolerance strategies and compensation transaction rules are set to complete the construction and configuration of the composite services.

[0024] The multi-dimensional resource metering process involves deploying distributed metering probes to collect consumption data in real time during the execution of combined services. The collected data is then cleaned, standardized, and integrated to generate a metering dataset in a unified format.

[0025] The dynamic billing generation process, based on the metering dataset and the preset basic rate table, combines time, region, SLA level, and urgency level to dynamically adjust factors and calculate service usage fees through a multi-dimensional comprehensive billing formula. It generates detailed bills and summary bills in real time and supports online bill query, export, verification, and payment.

[0026] The service release and ecosystem operation steps involve releasing the encapsulated atomic services and combined services to the service marketplace, setting service subscription rules, trial permissions and charging standards, allowing developers to subscribe to and call services through the open gateway, monitoring the service operation status and cost consumption in real time, providing fault handling and operation and maintenance support, and completing ecosystem revenue sharing settlement according to the agreed revenue sharing ratio and settlement cycle.

[0027] Furthermore, it includes visual orchestration and automatic dependency resolution methods, providing a drag-and-drop visual orchestration interface that allows developers to select atomic services, configure parameter mapping relationships, and set execution conditions and branch logic; during the orchestration process, it automatically detects data dependencies and resource conflicts between services, automatically adjusts the execution order and establishes data transfer channels when data dependencies occur, and provides warnings and solutions when resource conflicts occur; it supports saving, exporting, importing, and version management of combined service workflows, and generates standardized workflow configuration files.

[0028] Furthermore, it also includes revenue sharing calculation and billing management methods. Based on the service provider's service call volume, service pricing, service quality rating, and preset revenue sharing ratio, it calculates the revenue sharing amount for each service provider, generates a revenue sharing bill that includes the amount, basis, period, and method, supports online reconciliation, objection submission and processing, automatically transfers revenue sharing funds and sends notifications on a periodic basis, and generates a revenue sharing settlement report that includes details, transaction history, and reconciliation results.

[0029] Compared with existing technologies, the beneficial effects of this invention are:

[0030] In terms of lowering the development threshold and integration complexity, the system transforms complex low-altitude professional capabilities into standardized APIs through service encapsulation modules. Developers do not need to deeply understand professional processes such as airspace management and meteorological assessment; they can implement complex functions simply by making calls. The graphical service designer and visual orchestration interface support drag-and-drop combination of atomic services and workflow configuration. The intelligent orchestration engine automatically resolves dependencies and optimizes the execution order, greatly simplifying the construction process of complex business scenarios, significantly shortening the application development and integration cycle, and allowing developers to focus on core business innovation.

[0031] In terms of resource utilization and billing accuracy, the multi-dimensional billing module enables real-time collection and accurate measurement of resource consumption across multiple dimensions, including airspace, flight, computing, and data. The dynamic rate model flexibly adjusts based on factors such as time, region, SLA level, and urgency, generating detailed bills that accurately reflect actual resource consumption. This fine-grained billing approach makes developers' cost expenditures more transparent and reasonable, while also providing platform operators with data support for resource optimization, incentivizing developers to optimize task logic and improve overall resource utilization efficiency.

[0032] In terms of ecosystem building and innovation incentives, the open gateway and service marketplace modules establish standardized service integration and transaction channels. Developers can easily discover, subscribe to, and try various low-altitude services, while capability providers can package their core technologies into services and release them to the market for commercial monetization. The ecosystem revenue-sharing management module supports multiple revenue-sharing models and automatic settlement, protecting the interests of the platform, service providers, developers, and other parties, attracting more entities to join, and forming a positive cycle of the industrial ecosystem. The testing sandbox and rapid deployment modules lower the barriers to application testing and deployment, accelerate the iteration and implementation of innovative applications, and enrich the application scenarios of the low-altitude economy.

[0033] In terms of operational stability and sustainability, the fault tolerance and compensation module ensures the integrity of combined service execution and the rational utilization of resources through fault classification and transaction compensation mechanisms, avoiding resource waste and process interruptions caused by task failures. The data statistics and operational analysis module provides platform operators with multi-dimensional operational data support, helping to accurately grasp business hotspots and resource bottlenecks, and optimize service strategies and operational decisions. The system operation and maintenance module supports elastic scaling and load balancing, ensuring the stable operation of the platform in high-concurrency scenarios and adapting to the needs of the large-scale development of the low-altitude economy.

[0034] Overall, this invention realizes the transformation of low-altitude economic services from "closed and decentralized" to "open and shared," the development model from "complex customization" to "modular construction," and the billing method from "extensive and fixed" to "refined and dynamic." It not only significantly improves application development efficiency and resource utilization efficiency, but also builds a sustainable low-altitude economic industrial ecosystem, providing solid support for application innovation in multiple scenarios such as logistics distribution, power line inspection, and air travel, and promoting the high-quality development of the low-altitude economy towards large-scale, market-oriented, and ecological directions. Attached Figure Description

[0035] Figure 1 is a schematic block diagram of the low-altitude economic cloud platform service encapsulation and dynamic combination billing system proposed in this invention.

[0036] Figure 2 is a schematic block diagram of the low-altitude economic cloud platform service encapsulation and dynamic combination billing method proposed in this invention;

[0037] Figure 3 is a bar chart comparing the application development cycle of the traditional model and the present invention.

[0038] Figure 4 is a line graph comparing resource utilization efficiency under different workloads;

[0039] Figure 5 is a bar chart comparing the success rates of service combinations with different complexities. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0042] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0043] Referring to Figures 1 to 5: A low-altitude economic cloud platform service encapsulation and dynamic combination billing system includes the following modules:

[0044] The service encapsulation module defines a unified low-altitude service meta-model, clearly defining service identifiers, function descriptions, input / output specifications, resource constraints, and SLA indicators. It adapts to heterogeneous backend systems such as air traffic control systems, meteorological systems, and UAV manufacturer SDKs through the adapter pattern. It encapsulates core low-altitude capabilities such as airspace application, path planning, UAV scheduling, and data transmission into standardized APIs, provides a graphical service designer, supports drag-and-drop configuration of interface logic, exception handling processes, and resource adaptation rules, and automatically generates complete API documentation including parameter descriptions, call examples, and return code explanations.

[0045] The service orchestration module uses a directed acyclic graph to build a service composition workflow model. Nodes cover types such as atomic services, branch logic, and loop control. Edges define data flow and dependencies, providing a visual orchestration interface that allows developers to drag and drop services. The built-in intelligent orchestration engine automatically parses data and resource dependencies between services, optimizes the execution order, and injects runtime context such as UAV real-time location, task ID, and airspace status to achieve data transfer. It has fault tolerance mechanisms such as retry and service replacement, as well as compensation transaction processing capabilities such as airspace release and resource reclamation after task failure.

[0046] The multi-dimensional billing module deploys distributed metering probes to collect multi-dimensional consumption data in real time during service execution, including airspace resource consumption, flight mileage, flight time, aircraft type coefficient, CPU core time, GPU card time, memory usage, data transmission volume, and API call count. It establishes a billing model that includes a basic rate table and dynamic adjustment factors, supports real-time calculation of service usage fees, and generates multi-dimensional detailed bills and summary bills based on projects, tasks, and resource types.

[0047] The open gateway and service marketplace module provides unified API access, identity authentication, permission authorization, traffic control, and protocol conversion functions. It constructs a categorized service marketplace directory, supports service browsing, retrieval, subscription, trial, and evaluation, and integrates service level agreement management, cost monitoring, and budget early warning functions, providing third-party developers with a one-stop service integration and management portal. The resource adaptation layer integrates airspace services, flight services, data services, and computing services, realizing the abstraction and standardized output of basic capabilities such as airspace query, dynamic reservation, path planning, real-time scheduling, remote sensing data processing, storage and distribution, simulation, and model training, adapting to the interface specifications and operating characteristics of different types of UAVs, eVTOL aircraft, and low-altitude equipment.

[0048] The developer ecosystem support module provides functions such as developer registration, real-name authentication, and hierarchical permission management. It supports the entire process of application development, testing, deployment, launch, and commercialization, including project management, team collaboration, version control, application release channels, and canary release functions. It establishes a service call revenue sharing mechanism and a developer community communication platform, and provides resource support such as technical documents, development tutorials, and case libraries.

[0049] The system operation and maintenance module monitors the operating status, resource usage, and service call quality of each module on the platform in real time. It provides log collection, centralized storage, fault alarms, and rapid location functions. It supports system elastic scaling and load balancing, automatically detects and repairs potential operational faults, and regularly generates operation and maintenance reports and performance optimization suggestions to ensure the stable and reliable operation of the platform.

[0050] This invention also includes a service metamodel management module, which establishes a service metadata standard library, performs full lifecycle management of service metamodels including creation, modification, version iteration, and archiving, provides metamodel verification tools to verify the syntactic consistency of input and output specifications, the rationality of resource constraints, and the feasibility of SLA indicators, automatically detects the interface compatibility and resource conflict risks between new and existing services, supports metamodel version backtracking and difference comparison, provides standardized data support for service encapsulation, orchestration, and upgrades, ensures that all services within the platform follow unified specifications, and reduces the complexity of cross-service integration.

[0051] This invention also includes a fault tolerance compensation module with a preset fault classification handling mechanism. Based on the fault type and severity, such as service call timeout, execution failure, and return exception, the module automatically triggers corresponding fault tolerance strategies. Minor faults trigger a retry mechanism, moderate faults switch to a backup service provider, and severe faults initiate a service degradation process. Simultaneously, a transaction compensation mechanism is established to record the resource occupancy status during the execution of combined services. When a task is interrupted or fails, the module automatically performs compensation operations such as releasing space, reclaiming computing resources, and rolling back data, generating a fault analysis report that includes the cause of the fault, the scope of impact, and the handling results. This provides a basis for platform optimization and problem investigation, ensuring the integrity of business processes and the rational use of resources.

[0052] This invention also includes a dynamic rate adjustment and billing optimization module, which adjusts dynamic factors of various resources in real time based on market supply and demand, airspace resource scarcity, and business scenario characteristics, constructing a multi-dimensional comprehensive billing formula. The calculation expression is as follows:

[0053]

[0054] in, For the total cost, For the first The actual consumption of such resources For the first Basic fee rate for similar resources For the first Duration of resource usage This is a time-based dynamic factor; its value is greater than 1 during peak hours and less than 1 during off-peak hours. This is a regional dynamic factor; values ​​are greater than 1 for core areas and less than 1 for suburban areas. As an SLA tier factor, Platinum service has a higher value than Gold service, which in turn has a higher value than Standard service. As an urgency factor, urgent tasks have a higher value than normal tasks. To fix service call fees, dynamic adjustment of multiple factors enables accurate and flexible billing, balancing platform revenue and developer costs.

[0055] This invention also includes a test sandbox and a rapid deployment module, providing a high-fidelity test sandbox that simulates a low-altitude environment. It supports the injection of simulated airspace data, meteorological data, task orders, equipment status, and fault scenarios. Developers can perform service calls, orchestration, functional testing, and stress testing within the sandbox without occupying real low-altitude resources and equipment. During the testing process, test reports are generated in real time, including call logs, performance indicators, and error statistics. After the test is passed, a one-click deployment function is provided, supporting the deployment of applications as elastically scalable microservices, automatically adapting to platform resource configurations, dynamically adjusting the number of instances based on business traffic, supporting blue-green deployment and rapid rollback, and ensuring the stability and efficiency of application operation.

[0056] This invention also includes an ecosystem revenue-sharing management module, which establishes a revenue-sharing model based on service call volume, revenue contribution, and service quality rating. It supports customized revenue-sharing ratios among the platform, service providers, and application developers, allowing for various revenue-sharing modes such as fixed-ratio revenue sharing, tiered revenue sharing, and a minimum guarantee plus commission. The module automatically calculates the number of service calls, total expenses, revenue-sharing amount, and settlement cycle for each participant, generating detailed revenue-sharing statements including service name, number of calls, revenue amount, revenue-sharing ratio, and actual amount received. It supports automatic daily, weekly, and monthly settlements and fund transfers, provides revenue-sharing data query, reconciliation, and dispute handling functions, and connects to mainstream payment channels and financial systems to ensure transparency, fairness, and efficiency in the revenue-sharing process. This incentivizes service providers and developers to join the platform, enriching ecosystem resources.

[0057] This invention also includes a data statistics and operational analysis module, which collects various data during platform operation, including service call volume, combined service utilization rate, resource consumption distribution, developer registration volume, application release volume, service subscription volume, and billing amount. Through data analysis algorithms, it identifies business hotspots, resource bottlenecks, user demand trends, and service quality shortcomings, generating multi-dimensional operational analysis reports. These reports include service popularity rankings, resource optimization suggestions, ecosystem development trends, revenue analysis, and profit-sharing statistics. The module supports data visualization and custom report export, providing data support for platform operators to adjust resource allocation, optimize service strategies, formulate operational decisions, and expand business scenarios, thereby improving platform operational efficiency and ecosystem competitiveness.

[0058] This invention includes the following steps:

[0059] The service standardization encapsulation steps are based on a unified low-altitude service meta-model. Service identifiers, function descriptions, input and output specifications, resource constraints, and SLA indicators are defined. Through adapters, the interfaces of heterogeneous backend systems such as air traffic control systems, meteorological systems, and UAV manufacturer SDKs are converted into platform standard interfaces. The interface logic, exception handling process, and resource adaptation rules are configured using a graphical designer. Complete API documentation is automatically generated to complete the service encapsulation of core low-altitude capabilities.

[0060] The service composition orchestration steps involve dragging and dropping atomic services through a visual interface to build a directed acyclic graph-like service composition workflow, configuring dependencies and data flow between services, and having the intelligent orchestration engine automatically parse data and resource dependencies and optimize the execution order. Runtime context is injected to enable data transfer between services, and fault tolerance strategies and compensation transaction rules are set to complete the construction and configuration of the composite services.

[0061] The multi-dimensional resource metering process involves deploying distributed metering probes to collect multi-dimensional consumption data in real time during the execution of combined services, including airspace resource consumption, flight mileage, flight time, aircraft type coefficient, computing resource usage, data transmission volume, and API call count. The collected data is then cleaned, standardized, and integrated to generate a metering dataset in a unified format.

[0062] The dynamic billing generation process, based on the metering dataset and the preset basic rate table, combines dynamic adjustment factors such as time, region, SLA level, and urgency level to calculate service usage fees through a multi-dimensional comprehensive billing formula, generating detailed bills and summary bills in real time, and supporting online bill query, export, verification and payment;

[0063] The service release and ecosystem operation steps involve releasing the encapsulated atomic services and combined services to the service marketplace, setting service subscription rules, trial permissions and charging standards, allowing developers to subscribe to and call services through the open gateway, monitoring the service operation status and cost consumption in real time, providing fault handling and operation and maintenance support, and completing ecosystem revenue sharing settlement according to the agreed revenue sharing ratio and settlement cycle.

[0064] This invention also includes a visual orchestration and automatic dependency resolution method, providing a drag-and-drop visual orchestration interface that allows developers to select atomic services, configure input / output parameter mapping relationships, and set execution conditions and branch logic through graphical operations. During the orchestration process, it automatically detects data dependencies and resource conflicts between services. When data dependencies exist, it automatically adjusts the service execution order and establishes data transfer channels. When resource conflicts are detected, it provides warnings and conflict solutions. It supports saving, exporting, importing, and version management of composite service workflows, generating standardized workflow configuration files for easy reuse, sharing, and secondary editing, reducing the difficulty and time cost of building composite services.

[0065] This invention also includes a revenue-sharing calculation and billing management method. Based on the service provider's service call volume, service pricing, service quality rating, and preset revenue-sharing ratio, the method calculates the revenue-sharing amount for each service provider. Simultaneously, based on the application developer's service usage fees and revenue-sharing agreement terms, it calculates the developer's share of the revenue. A detailed revenue-sharing bill is generated, clearly specifying the revenue-sharing amount, calculation basis, settlement cycle, and payment method. It supports online reconciliation, objection submission, and processing of revenue-sharing bills. The method automatically completes the transfer of revenue-sharing funds according to the settlement cycle and simultaneously sends settlement notifications. A revenue-sharing settlement report is generated, including revenue-sharing details, fund flow, and reconciliation results within the cycle. This achieves transparency, fairness, and efficiency in the revenue-sharing process, protects the legitimate rights and interests of all participants in the ecosystem, and promotes the sustainable development of the platform ecosystem.

[0066] The following two examples further illustrate specific embodiments of the present invention:

[0067] Example 1: Application of Low-Altitude Service Platform for Urban Unmanned Aerial Vehicle Logistics Delivery

[0068] This embodiment is applied to a drone logistics delivery platform in a certain city. The platform connects with multiple drone manufacturers, the city's air traffic control system, a meteorological service platform, and community delivery stations, covering more than 100 communities and more than 20 business districts in the urban area, providing instant delivery services for fresh produce, medicines, emergency supplies, etc. The scenario is characterized by complex delivery routes, scarce airspace resources, and large fluctuations in order volume. It is necessary to quickly integrate multiple resources such as airspace, flight, data, and computing, adapt to the operating specifications of different drone models, accurately measure resource consumption, and realize commercial billing to support revenue sharing settlement between the platform, developers, and drone operators.

[0069] The service encapsulation module defines a unified low-altitude service meta-model, clearly defining service identifiers, functional descriptions, input / output specifications, resource constraints, and SLA metrics. Dedicated adapters are developed for heterogeneous systems such as airspace application interfaces for air traffic control systems, real-time meteorological data interfaces for meteorological platforms, and scheduling SDKs for various UAV manufacturers, converting them into platform standard APIs. Through a graphical service designer, "dynamic airspace reservation" is encapsulated as an API with inputs including area range, usage time period, and delivery type, internally automating processes such as form filling, rule validation, and air traffic control department workflow. "Community delivery route planning" is encapsulated as an API with inputs including start-point coordinates, end-point coordinates, avoidance area, and UAV type, outputting standardized results including a list of waypoints, estimated flight time, and energy consumption estimates, automatically generating API documentation including parameter descriptions, call examples, and return code explanations.

[0070] The service orchestration module uses a directed acyclic graph (DAG) to construct the workflow model. Nodes include atomic services and branch control logic such as "order receipt," "airspace query," "weather assessment," "path planning," "drone scheduling," "material delivery," and "status synchronization." Developers can drag and drop services through a visual interface to configure data flow between services. For example, the output of the "order receipt" service serves as the input for the "airspace query" service, and the result of the "weather assessment" service determines whether to execute the "path adjustment" branch. The intelligent orchestration engine automatically resolves data and resource dependencies, optimizes the execution order, and injects runtime context such as drone real-time location, order ID, and airspace occupancy status. When a service call times out, a retry mechanism is automatically triggered. After three failed retries, the system switches to a backup service provider. If task execution is interrupted, reserved airspace resources are automatically released, computing resources are reclaimed, and a fault analysis report is generated.

[0071] The multi-dimensional billing module deploys distributed metering probes to collect multi-dimensional consumption data in real time during service execution: airspace resources are statistically analyzed by occupied volume and duration; flight resources record flight mileage, flight time, and drone type coefficients; computing resources are statistically analyzed by CPU core time and memory usage; and data resources collect downlink telemetry data, uplink order information, and video surveillance bandwidth, while also recording API call counts. A dynamic rate model is established, with the base rate set according to a unified city standard. The time dynamic factor is set at 1.5 during morning peak hours (7-9 AM) and evening peak hours (6-8 PM), and 0.8 during off-peak hours (0-6 AM); the regional dynamic factor is set at 1.3 for core business districts and 0.9 for suburban communities; the SLA level factor is set at 1.2 for expedited delivery services and 1.0 for regular delivery; and the urgency factor is set at 1.4 for medical supplies delivery and 1.0 for regular supplies. Detailed bills based on orders and resource types are generated in real time, supporting online queries by developers and operators.

[0072] The open gateway and service marketplace module provide a unified API access point. After registration and authentication, developers can browse categorized services such as "Airspace Query," "Route Planning," "Drone Scheduling," and "Status Tracking" in the service marketplace directory, view service details, call examples, and pricing standards, and obtain calling permissions through the subscription function. The gateway implements identity authentication, permission authorization, and traffic control, setting traffic thresholds for developers making high-frequency calls to avoid system overload. It also supports multiple protocol conversions such as HTTP and HTTPS to ensure compatibility with different terminals and systems. It integrates service level agreement management functions, clearly defining service response latency, success rate, and other commitments, and automatically triggering a compensation mechanism when service standards are not met.

[0073] The resource adaptation layer integrates airspace services, flight services, data services, and computing services. Airspace services enable urban airspace queries, dynamic reservations, and conflict detection. Flight services provide precise path planning, real-time drone scheduling, and flight status monitoring. Data services process, store, and distribute delivery order data, flight trajectory data, and meteorological data. Computing services support delivery route simulation and order optimization allocation model training. It adapts to multiple drone models from different manufacturers, using unified interface specifications and operational logic to ensure developers don't need to worry about underlying device differences when calling services.

[0074] The developer ecosystem support module provides developer registration, real-name authentication, and hierarchical permission management, categorized into roles such as individual developers, enterprise developers, and device operators, assigning different service access permissions and revenue sharing ratios. It supports the entire application development, testing, deployment, and commercialization process, including project management functions to create collaborative projects for multiple teams, version control to record application iteration history, and a canary release channel to allow select users to experience new versions of the application first. A developer community exchange platform is established, providing technical documentation, development tutorials, FAQs, and a library of typical cases, and regularly hosting online training and technical salons.

[0075] The system operations and maintenance module monitors the operational status of each module on the platform in real time, collecting metrics such as service call response time, success rate, and resource utilization. It centrally stores operation logs, fault logs, and operational logs through a log collection system. When service response latency exceeds a threshold or resource utilization is too high, a fault alarm is automatically triggered and pushed to operations and maintenance personnel. The system supports elastic scaling, dynamically adjusting the number of compute resource instances based on order traffic to achieve load balancing. It automatically detects potential operational faults and attempts to repair them, generating a weekly operations and maintenance report that includes service operation quality, resource usage, fault handling statistics, and performance optimization suggestions.

[0076] The testing sandbox and rapid deployment module provide a high-fidelity simulation of a low-altitude environment, supporting the injection of simulated airspace restriction data, real-time weather data, order traffic data, and drone failure scenarios. Developers can call various services and combine workflows within the sandbox to test the application's functional completeness and compatibility. Examples include simulating path adjustment logic under heavy rain and replanning processes during airspace conflicts, without consuming real airspace and equipment resources. Test reports are generated in real time during testing, including call logs, performance metrics, and error statistics. After passing the test, the application can be deployed as a scalable microservice with a single click, automatically adapting to platform resource configurations.

[0077] The ecosystem revenue-sharing management module establishes a revenue-sharing model based on service call volume, revenue contribution, and service quality rating. The platform, developers, and drone operators agree on a fixed revenue-sharing ratio, with tiered revenue-sharing rewards for developers with high-frequency calls. It automatically calculates the number of service calls, total costs, and revenue-sharing amounts for each participant, generating detailed revenue-sharing statements including service name, number of calls, revenue amount, revenue-sharing ratio, and actual amount received. It supports daily statistics and monthly settlements, and integrates with mainstream payment channels and financial systems. Developers can reconcile accounts online, raise objections, and submit supporting materials. The platform completes the review and processing within 3 business days and automatically transfers funds according to the settlement cycle.

[0078] Table 1: Comparison of Application Effects of Urban Unmanned Aerial Vehicle Logistics Delivery Platforms

[0079]

[0080] Table 1 clearly demonstrates the advantages of this invention in urban logistics and delivery scenarios. Traditional delivery models require developers to separately connect to multiple systems such as air traffic control, meteorology, and drone manufacturers, resulting in long development cycles and high complexity in resource integration; billing uses fixed per-order charges, which cannot accurately reflect resource consumption; there are few ecosystem participants and limited service types; and the lack of a unified adaptation and fault tolerance mechanism leads to a low service call success rate. This invention significantly shortens the development cycle and reduces the difficulty of resource integration through standardized service encapsulation and visual orchestration; multi-dimensional accurate billing achieves cost transparency; an open service market attracts more developers and operators to join, enriching ecosystem resources; and a comprehensive adaptation and fault tolerance mechanism improves the service call success rate, perfectly adapting to the high-frequency, high-efficiency, and high-reliability requirements of urban drone logistics and delivery.

[0081] Example 2: Application of Low-Altitude Service Platform for Power Grid Inspection

[0082] This embodiment is applied to a provincial-level low-altitude service platform for power line inspection. The platform connects with the power company's equipment management system, the provincial air traffic control system, meteorological observation stations, drone inspection teams, and AI algorithm service providers. The service covers over 5,000 kilometers of transmission lines, over 300 substations, and over 100 wind farms within the province, providing services such as line inspection, equipment defect identification, fault location, and data archiving. The scenario is characterized by a vast inspection area, complex terrain, and diverse equipment types, requiring the coordination of multiple resources including airspace, flight, data processing, and AI recognition. It adapts to different inspection task requirements, accurately measuring and calculating resource consumption across multiple dimensions such as data transmission and AI recognition, supporting the commercial revenue sharing between the platform, algorithm service providers, and inspection teams.

[0083] The service encapsulation module defines a unified service metamodel. It develops heterogeneous system adapters for the equipment parameter interfaces of the power equipment management system, the transmission line airspace interface of the air traffic control system, the defect identification interface of the AI ​​service provider, and the control SDK of the inspection drone, converting them into platform standard APIs. Through a graphical service designer, "Transmission Line Airspace Application" is encapsulated as an API that inputs the line number, inspection time period, and inspection altitude, automatically completing multiple airspace applications and permission verification internally. "Equipment Defect Identification" is encapsulated as an API that inputs the inspection video stream, equipment type, and identification accuracy requirements, outputting standardized results including defect location, defect type, and confidence level. "Fault Location and Reporting" is encapsulated as an API that inputs defect information, line coordinates, and equipment number, automatically completing fault classification, report generation, maintenance system notification, and other processes, simultaneously generating complete API documentation.

[0084] The service orchestration module constructs a combined service workflow encompassing "inspection task creation," "airspace application," "meteorological assessment," "inspection route planning," "UAV dispatch," "video acquisition," "defect identification," "fault reporting," and "data archiving." Power inspection personnel configure workflow parameters through a visual interface. For example, they can set rules for the "inspection route planning" service, such as flying along the power line, maintaining a 5-meter altitude, and stopping to observe key equipment. They can also configure branch logic so that when the "defect identification" service detects a high-risk defect, it automatically triggers the "emergency dispatch and repair" service; otherwise, it executes the "routine data archiving" process. The intelligent orchestration engine automatically resolves dependencies, optimizes the execution order, and injects contextual information such as real-time power line status, UAV location, and meteorological data. When the "video acquisition" service is interrupted, it automatically triggers a retry mechanism and switches to a backup transmission channel. If the task fails, it automatically releases airspace resources and generates a compensation report.

[0085] The multi-dimensional billing module deploys distributed metering probes to collect multi-dimensional consumption data in real time during inspections: airspace resources are statistically analyzed based on the airspace volume and occupancy time covered by the inspection route; flight resources record flight mileage, flight time, and inspection drone type coefficients; computing resources statistically analyze CPU core time, GPU card time, and memory usage for AI defect identification; data resources collect the size of the inspection video stream, the amount of equipment parameter data, and the report storage capacity, while also recording the number of API calls. In the dynamic rate model, the base rate is set according to the power inspection industry standard; the regional dynamic factor is 1.4 for mountain inspections and 1.0 for plain inspections; the SLA level factor is 1.3 for high-risk defect identification services and 1.0 for routine inspections; the urgency factor is 1.5 for fault repair inspections and 1.0 for periodic maintenance inspections. Detailed bills based on inspection tasks and resource types are generated in real time, supporting statistical analysis by route, device, and time period.

[0086] The open gateway and service marketplace modules provide unified API access and access control. After registration and authentication, power companies, inspection teams, and algorithm service providers can subscribe to the services they need in the service marketplace. The gateway implements traffic control and sets up a bandwidth guarantee mechanism for high-definition video transmission services to ensure stable data transmission; it supports protocol conversion to adapt to internal power system protocols and platform standard protocols. The service marketplace is categorized into "Airspace Services," "Flight Services," "Data Services," and "AI Recognition Services," and offers a service trial function. Developers can verify the service effect in a test environment before officially subscribing. It integrates cost monitoring and budget warning functions, automatically alerting users when resource consumption approaches the budget threshold.

[0087] The resource adaptation layer integrates airspace services, flight services, data services, and computing services. Airspace services enable airspace queries for transmission lines, multi-segment airspace linkage applications, and conflict coordination. Flight services provide precise path planning along the line, real-time drone scheduling, and flight attitude control. Data services handle inspection video processing, equipment data storage, and historical data queries. Computing services support defect identification model training, inspection path simulation, and fault simulation. It is compatible with various models of inspection drones and testing equipment, uses a unified interface standard, and supports the acquisition and processing of various inspection data, including infrared, visible light, and lidar data.

[0088] The developer ecosystem support module provides tiered access control for developers, algorithm service providers, and drone operators involved in power line inspection. Algorithm service providers can publish defect identification services, drone operators can provide equipment rental services, and power companies can subscribe to bundled services as demanders. It supports the entire application development process, including project management functions to assign inspection task development permissions, version control to record service iteration history, a canary release channel, and support for piloting new inspection workflows on selected lines. An ecosystem community is established to share inspection case studies, algorithm optimization experience, and equipment adaptation solutions, and regularly organizes technical exchange activities.

[0089] The system operations and maintenance module monitors the operational status of each module on the platform in real time, focusing on the response speed of the AI ​​defect identification service, the stability of the video transmission service, and the success rate of the drone scheduling service. It collects operational logs and fault information for various services, stores them centrally, and performs analysis. The system supports elastic scaling, automatically adding computing resource instances during peak inspection periods to ensure the efficiency of defect identification and data processing; it also achieves load balancing, evenly distributing inspection tasks across different server nodes. It automatically detects potential faults and triggers alarms, such as drone connection interruptions or excessively high data transmission latency, promptly notifying operations and maintenance personnel for handling. Monthly operations and maintenance reports are generated, including service operation quality, resource utilization efficiency, fault handling status, and optimization suggestions.

[0090] The data statistics and operations analysis module collects platform operational data, including service call volume, number of inspection tasks completed, defect identification accuracy, resource consumption distribution, developer registration volume, and service subscription volume. It uses data analysis algorithms to identify business hotspots, such as recognizing that summer's high temperatures are a peak period for line defects, and that resource consumption for mountain line inspections is higher than for plains lines; it analyzes resource bottlenecks, finding that high-definition video processing has a high CPU utilization rate; and it generates operations analysis reports, including service popularity rankings, resource optimization suggestions, revenue analysis, and profit-sharing statistics. It supports data visualization and custom report export, providing data support for the platform to adjust resource allocation, optimize fee strategies, and expand inspection scenarios.

[0091] Table 2 Comparison of Application Effects of Low-Altitude Service Platform for Power Inspection

[0092]

[0093] Table 2 data highlights the application value of this invention in power grid inspection scenarios. Traditional inspection methods require manual coordination of airspace, equipment scheduling, and data processing, resulting in low task completion efficiency; defect identification relies on manual analysis, leading to slow response times; resource allocation lacks overall planning, resulting in low utilization efficiency; billing uses a project-based package method, resulting in low transparency; and independent operation and maintenance of each system leads to high costs. This invention improves the efficiency of inspection task completion by integrating multiple types of resources through service encapsulation and orchestration; seamless integration of AI services with the inspection process accelerates defect identification response speed; accurate measurement of resource consumption optimizes resource allocation and improves utilization efficiency; multi-dimensional detailed billing achieves cost transparency; and a unified operation and maintenance platform reduces operation and maintenance costs, perfectly adapting to the large-scale, efficient, and precise needs of power grid inspection.

[0094] Referring to Figure 3, this figure visually illustrates the core advantages of this invention in lowering the development threshold and shortening the development cycle, directly addressing the core pain points of the traditional model. In the traditional development model, developers need to individually interface with multiple heterogeneous systems such as air traffic control, meteorology, and drone manufacturers, deeply learning low-altitude professional knowledge and interface specifications. Resource integration and system integration are extremely difficult, resulting in development cycles typically lasting 3-6 months. This invention transforms core low-altitude capabilities into standardized APIs through service encapsulation modules. Combined with a visual orchestration interface and intelligent dependency resolution, developers do not need to concern themselves with complex underlying logic; they can quickly build applications simply by dragging and dropping atomic services. The development cycle for various scenarios is shortened to less than 1.5 months. This significantly shortened development cycle not only reduces developers' time and trial-and-error costs but also accelerates the innovation and iteration speed of low-altitude applications, providing strong support for the rapid deployment in logistics, inspection, cultural tourism, and other scenarios.

[0095] Referring to Figure 4, this figure clearly reflects the significant advantages of this invention in resource optimization and allocation, solving the problem of severe resource waste in traditional models. In traditional models, airspace, computing, and data resources are managed in a decentralized manner, lacking unified scheduling and precise matching. When the workload increases, it can only be coped with extensive expansion, and resource utilization remains consistently between 42% and 60%, with a large amount of resources idle. This invention, through the unified abstraction of the resource adaptation layer and the dynamic scheduling of the intelligent orchestration engine, achieves precise matching and efficient collaboration of multi-dimensional resources. As the workload increases, resource utilization steadily increases to 90%. Efficient resource utilization not only reduces the hardware costs and energy consumption of platform operation but also supports larger-scale concurrent task processing, improving the platform's carrying capacity and service response speed, adapting to the needs of the large-scale development of the low-altitude economy.

[0096] Referring to Figure 5, this figure illustrates the stability and reliability of this invention in handling complex tasks, solving the problems of high difficulty and low success rate in service composition using traditional methods. In traditional methods, multi-service composition requires manual handling of data dependencies, resource conflicts, and exception handling. As task complexity increases, the success rate of composition drops sharply, with ultra-complex tasks achieving a success rate of only 20%, making it difficult to support the implementation of complex application scenarios. This invention, through a directed acyclic graph workflow model and an intelligent orchestration engine, automatically parses data and resource dependencies between services, optimizes the execution order, and effectively addresses various problems in complex compositions by incorporating fault tolerance mechanisms such as retry and service replacement, as well as transaction compensation mechanisms. Even for ultra-complex tasks with more than 15 service compositions, the success rate remains above 85%. This highly stable composition success rate provides core assurance for the implementation of complex scenarios such as drone logistics delivery, multi-route collaborative inspection, and aerial emergency response, expanding the application boundaries of the low-altitude economy.

[0097] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A low-altitude economic cloud platform service encapsulation and dynamic combination billing system, characterized in that, It includes the following modules: Service encapsulation module, which defines a unified low-altitude service meta-model, adapts to heterogeneous backend systems through the adapter pattern, encapsulates the core low-altitude capabilities into standardized APIs, provides a graphical service designer, and automatically generates complete API documentation; Service orchestration module, which uses a directed acyclic graph to build a service composition workflow model, provides a visual orchestration interface, has a built-in intelligent orchestration engine to parse service dependencies and optimize the execution order, and has fault tolerance mechanisms and compensation transaction processing capabilities; The multi-dimensional billing module deploys distributed metering probes to collect consumption data in real time, establishes a billing model that includes a basic rate table and dynamic adjustment factors, supports real-time calculation of service usage fees, and generates multi-dimensional detailed bills and summary bills. The open gateway and service marketplace module provides unified API access, identity authentication, permission authorization, traffic control, and protocol conversion. It constructs a categorized service marketplace directory, supporting service browsing, retrieval, subscription, trial, and evaluation, and integrates protocol management, cost monitoring, and budget warning functions. The resource adaptation layer integrates four types of services: airspace, flight, data, and computing, achieving the abstraction and standardized output of basic capabilities, and adapting to the interface specifications and operating characteristics of different types of UAVs, eVTOL aircraft, and low-altitude equipment. The developer ecosystem support module provides developer registration, real-name authentication, and hierarchical management functions, supports the entire process of application development, testing, deployment, and commercialization, establishes a service call revenue-sharing mechanism and community exchange platform, and provides technical documentation and case study resources. The system operation and maintenance module monitors the operating status, resource usage and service call quality of each module on the platform in real time. It provides log collection, centralized storage, fault alarm and rapid location functions, supports system elastic scaling and load balancing, automatically detects and repairs potential faults, and regularly generates operation and maintenance reports and optimization suggestions. It also includes a fault tolerance compensation module, which has a preset fault classification and handling mechanism. Based on the fault type and severity, it automatically triggers corresponding fault tolerance strategies: minor faults are retried, moderate faults are switched to a backup service provider, and severe faults initiate a service degradation process. Simultaneously, a transaction compensation mechanism is established to record the resource occupancy status during the execution of combined services. When a task is interrupted or fails, it automatically performs airspace release, computing resource reclamation, and data rollback operations, generating an analysis report including the cause of the fault, the scope of impact, and the handling results. A dynamic rate adjustment and billing optimization module adjusts the dynamic factors of various resources in real time based on market supply and demand, airspace resource scarcity, and business scenario characteristics, constructing a multi-dimensional comprehensive billing formula. The calculation expression is as follows: in, For the total cost, For the first The actual consumption of such resources For the first Basic fee rate for similar resources For the first Duration of resource usage As a time-dynamic factor, For regional dynamic factors, As the SLA rating factor, As an urgency factor, This is a fixed service call fee.

2. The low-altitude economic cloud platform service encapsulation and dynamic combination billing system according to claim 1, characterized in that, It also includes a service metamodel management module, which establishes a service metadata standard library, performs full lifecycle management of service metamodels including creation, modification, version iteration, and archiving, provides metamodel verification tools to verify the syntactic consistency of input and output specifications, the rationality of resource constraints, and the feasibility of SLA indicators, automatically detects the interface compatibility and resource conflict risks between new and existing services, and supports metamodel version backtracking and difference comparison.

3. The low-altitude economic cloud platform service encapsulation and dynamic combination billing system according to claim 1, characterized in that, It also includes a test sandbox and a rapid deployment module, providing a high-fidelity test sandbox that simulates a low-altitude environment. It supports the injection of simulated airspace data, meteorological data, task orders, equipment status and fault scenarios. Developers can conduct service calls, combination orchestration, functional testing and stress testing in the sandbox. During the testing process, test reports containing call logs, performance indicators and error statistics are generated in real time. Once the test is passed, a one-click deployment function is provided to deploy the application as an elastically scalable microservice, automatically adapt to the platform resource configuration and dynamically adjust the number of instances according to business traffic, and support blue-green deployment and fast rollback.

4. The low-altitude economic cloud platform service encapsulation and dynamic combination billing system according to claim 1, characterized in that, It also includes an ecosystem revenue sharing management module, which establishes a revenue sharing model based on service call volume, revenue contribution, and service quality rating. It supports customized revenue sharing ratios among platforms, service providers, and application developers, allows setting multiple revenue sharing modes, automatically calculates the number of service calls, total fees, revenue sharing amount, and settlement cycle for each participant, generates detailed revenue sharing bills, supports automatic settlement and fund transfer on a daily, weekly, and monthly basis, provides revenue sharing data query, reconciliation, and dispute handling functions, and connects to mainstream payment channels and financial systems.

5. The low-altitude economic cloud platform service encapsulation and dynamic combination billing system according to claim 1, characterized in that, It also includes a data statistics and operation analysis module, which collects various types of data during the platform's operation, uses data analysis algorithms to uncover business hotspots, resource bottlenecks, user demand trends, and service quality shortcomings, generates operation analysis reports, and supports data visualization and custom report export.

6. A method for a low-altitude economic cloud platform service encapsulation and dynamic combination billing system according to any one of claims 1-5, characterized in that, Includes the following steps: The service standardization and encapsulation steps, based on a unified low-altitude service meta-model, define service identifiers, functional descriptions, input / output specifications, resource constraints, and SLA metrics; adapters convert heterogeneous backend system interfaces into platform standard interfaces; a graphical designer configures interface logic, exception handling processes, and resource adaptation rules, automatically generating complete API documentation; the service composition and orchestration steps involve dragging and dropping atomic services through a visual interface to build a directed acyclic graph-like composition service workflow, configuring dependencies and data flows between services, with an intelligent orchestration engine automatically resolving data and resource dependencies and optimizing execution order, injecting runtime context to achieve data transfer between services, setting fault tolerance strategies and compensation transaction rules, and completing the construction and configuration of the composition service; the multi-dimensional resource metering step deploys distributed metering probes during the execution of the composition service. The process involves real-time data collection of consumption data, followed by data cleaning, standardization, and integration to generate a unified formatted metering dataset. The dynamic billing generation step, based on the metering dataset and a pre-set basic rate table, dynamically adjusts factors according to time, region, SLA level, and urgency, calculating service usage fees through a multi-dimensional comprehensive billing formula. Detailed and summary bills are generated in real-time, supporting online querying, exporting, verification, and payment. The service release and ecosystem operation step involves publishing encapsulated atomic and combined services to the service marketplace, setting service subscription rules, trial permissions, and pricing standards. Developers subscribe to and invoke services through an open gateway. The platform monitors service operation status and cost consumption in real-time, providing fault handling and maintenance support, and completing ecosystem revenue sharing settlement according to the agreed revenue sharing ratio and settlement cycle.

7. The method for encapsulating and dynamically combining billing systems for low-altitude economic cloud platform services according to claim 6, characterized in that, It also includes visual orchestration and automatic dependency resolution methods, providing a drag-and-drop visual orchestration interface that allows developers to select atomic services, configure parameter mapping relationships, and set execution conditions and branch logic; During the orchestration process, it automatically detects data dependencies and resource conflicts between services. When data dependencies occur, it automatically adjusts the execution order and establishes a data transfer channel. When resource conflicts occur, it provides early warnings and solutions. It supports saving, exporting, importing, and version management of combined service workflows and generates standardized workflow configuration files.

8. The method for encapsulating and dynamically combining billing systems for low-altitude economic cloud platform services according to claim 6, characterized in that, It also includes revenue sharing calculation and billing management methods. Based on the service provider's service call volume, service pricing, service quality rating, and preset revenue sharing ratio, it calculates the revenue sharing amount for each service provider and generates a revenue sharing bill that includes the amount, basis, period, and method. It supports online reconciliation, objection submission and processing; it automatically transfers revenue sharing funds and sends notifications on a periodic basis, and generates a revenue sharing settlement report that includes details, transaction history, and reconciliation results.

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