An out-of-the-box integration method for RPAaaS platform + RPA cloud computer

Abstract

The out-of-the-box integration method of RPAaaS platform + RPA cloud PC improves integration and flexibility: By deeply integrating the RPAaaS platform and cloud PC system, efficient management of automated processes and flexible resource scheduling are achieved; resource utilization is optimized: intelligent resource scheduling algorithms effectively avoid resource idleness and over-allocation, reducing costs; security is enhanced: encryption technology and access control policies improve data security and user privacy protection; user experience is improved: a simple and intuitive visual interface and multiple user authentication methods reduce the complexity of user configuration and debugging, improving system usability; the "RPAaaS platform + RPA cloud PC system" technical solution proposed in this invention is superior to existing technologies in terms of integration, resource utilization, security, and user experience, providing strong support for enterprise digital transformation.

Description

Technical Field

[0001] This application pertains to AI technology, and in particular relates to a robotic process automation technology. Background Technology

[0002] With the acceleration of digital transformation, enterprises are increasingly demanding automated processes. Traditional robotic process automation (RPA) technology simulates user operations to automate business processes, significantly improving work efficiency and accuracy. However, most existing RPA solutions are based on local deployment, which suffers from problems such as insufficient flexibility, low resource utilization, and high maintenance costs.

[0003] In recent years, the development of cloud computing technology has provided new deployment models for RPA. Cloud RPA services allow enterprises to access RPA functions through cloud service providers without the need for local software installation and maintenance, thereby reducing costs and improving scalability. This cloud RPA service is abbreviated as RPAaaS. However, existing RPAaaS platforms typically only provide basic automated task execution functions and lack deep integration with cloud computing systems, limiting their flexibility and efficiency in complex application scenarios.

[0004] The applicant found a patent application filed by Fujing Technology (Shenzhen) Co., Ltd., patent number 2024114143790, entitled "RPA Customer Service Interaction Optimization Method and Cloud Server Based on Artificial Intelligence." The abstract states: This application provides an RPA customer service interaction optimization method and cloud server based on artificial intelligence. The customer service interaction optimization process is assisted by a sentiment polarity analysis network. When training this neural network, the required number of samples is reduced, eliminating the need for numerous labeled customer service text samples, thus lowering training costs. Based on some labeled customer service text samples, partial guided clustering is used to obtain predictive prior information for unlabeled customer service text samples. By training the network with a massive amount of unlabeled customer service text samples, and considering the semantic consistency measurement of the entire sample and paragraphs, noise in the predictive prior information can be cleaned up, making the predictive prior information more accurate. The trained network has higher precision, helping to obtain accurate sentiment polarity labels for RPA customer service conversation text, enabling accurate customer service interaction optimization and improving the customer service experience. Summary of the Invention

[0005] Technical problems that need to be solved: 1. The problem of low integration needs to be addressed: The existing RPAaaS platform has low integration with cloud computing systems, making it difficult to achieve seamless automated process management and resource scheduling. It is necessary to improve integration, allocate resources rationally, and prevent over-allocation of resources. Source or resource idleness issues; 2. The need to address security deficiencies: In cloud environments, data security and privacy protection are significant challenges, and existing solutions fall short in terms of security. 3. The problem of poor user experience needs to be addressed: When using RPAaaS platforms, users often face complex configuration and debugging processes, which affects the user experience.

[0006] Technical solution: Step 1: Adopting the RPAaaS platform + RPA cloud PC model, a unified RPAaaS platform is designed through framework integration technology. The RPAaaS platform includes an RPA engine, an RPA cloud PC management system, a task scheduler, and a security monitoring module. The RPAaaS platform framework supports deep integration with the cloud PC system through APIs, SDKs, or middleware, enabling the RPAaaS platform to seamlessly access the resources and data of the cloud PC system. Step 2: Utilize RPA's Recorder function to record user keyboard and mouse input, and integrate these operations into the cloud computer system via API calls, solving the software integration problem of lacking data or application interfaces. Step 3: Adopting end-to-end integrated design and service throughout the product lifecycle, communication and interaction between RPA edge cloud services and central cloud services reduce overall cloud pressure, facilitate dynamic expansion of RPA cloud computers, and achieve dynamic interoperability and coexistence between RPA cloud edge computing and core computing scheduling. In the cloud, utilizing the unique identifier of each customer, a unique identification identifier is established for the client after access. By recording the access preferences, visited web pages, consumption habits, and online time of this unique identifier, corresponding resources and recommended content are matched for the user. This avoids searching for the most suitable information for each user from a massive amount of data. The unique identifier refers to a certain identity or unique identifier of the user in the cloud, including but not limited to identity numbers, social media accounts, and unique identifiers of computer devices. The unique identifiers of users are then classified and summarized. Step 4: RPAaaS Platform + RPA Cloud PC Mode. This mode uses a cloud PC system as the execution environment for RPA tasks. Virtualization or hyper-threading technology is used to dynamically allocate and schedule resources. This virtualization or hyper-threading technology refers to the ability to identify virtualization or hyper-threading technologies on the access end without considering differences in the hardware. The cloud uses these identifiers to identify the corresponding virtualization or hyper-threading technologies. Virtualization or hyper-threading technologies include PC and mobile clients. Mobile clients include virtual Android and virtual Apple clients. PC clients include DOS kernel, Windows kernel, Kylin kernel, Huawei kernel, LINUX kernel, and Windows kernel, including but not limited to WINDOWS 92 / 95 / 98 / 2000 / 2003 / XP / 7 / 8 / 10. Step 5: Employ an automated process design pattern, enabling users to design automated processes through the RPAaaS platform's visual interface. The visual interface for designing automated processes includes task definition, triggering conditions, and execution steps. The RPAaaS platform automatically allocates cloud computer resources based on task requirements and generates corresponding execution scripts. Step 6: Adopt a resource management and scheduling model, introduce an intelligent resource scheduling algorithm, dynamically adjust the allocation of cloud computer resources according to task load and resource usage, monitor resource utilization in real time, and avoid resource idleness or over-allocation; Step 7: Introduce a resource manager component to monitor and allocate resources between the RPAaaS platform and the cloud computer system. The resource manager dynamically adjusts resource allocation according to the needs of RPA tasks to avoid resource idleness or over-allocation. In specific application scenarios, either step 6 or step 7 can be performed. Step 8: Parallel Processing and Load Balancing. Multi-threading and multi-processing techniques are used to achieve parallel processing of RPA tasks. Simultaneously, a load balancing algorithm is employed to evenly distribute tasks among different RPA robots, thereby improving overall execution efficiency. Step 9: The RPAaaS platform + RPA cloud desktop mode enhances security by providing multiple security measures on the RPA cloud desktop side, including data encryption, authentication, and access control, to ensure the security and privacy of user data. Step 10: Identity Authentication and Authorization: Assign a unique identity to each RPA robot program and process, and ensure accountability for robot program behavior and access security through identity authentication and authorization mechanisms; Step 11: Audit Logs and Monitoring: Implement comprehensive audit logging and monitoring, recording monitoring data for all bot interactions, users, and transactions. This helps to promptly detect and prevent potential abuse and fraud. Step 12: Compliance Management: Ensure the RPAaaS platform meets the most stringent enterprise security compliance requirements, provide a traceable tracking mechanism, and assist platform administrators in identifying and locating problems; Step 13: To address the issue of poor user experience: The RPAaaS platform + RPA cloud desktop mode provides preset process templates, allowing users to choose the appropriate template based on their needs. Step 14: Simultaneously, by implementing an automation script library, RPA Cloud Desktop provides a rich library of automation scripts, which users can directly call to achieve various automated tasks. These script libraries include automation scripts for various common scenarios; Step 15: Provide zero-code development capabilities, enabling business users to easily create and configure RPA processes without requiring in-depth programming knowledge. This greatly simplifies the configuration and debugging process, improving the user experience; Step 16: One-stop service platform: Build a one-stop service platform that integrates the functions of the RPAaaS platform and the cloud PC system. Users can easily access and manage all RPA tasks and cloud PC resources through this platform; Step 17: Intelligent Recommendations and Self-Service: Leveraging the intelligent capabilities of RPA, provide users with personalized recommendations and self-service options. This can further improve user satisfaction and efficiency.

[0007] Beneficial Effects: The out-of-the-box integration method of RPAaaS platform + RPA cloud computer improves integration and flexibility: Through deep integration of RPAaaS platform and cloud computer system, efficient management of automated processes and flexible scheduling of resources are achieved; Optimized resource utilization: Intelligent resource scheduling algorithm effectively avoids resource idleness and over-allocation, reducing costs; Enhanced security: The adoption of encryption technology and access control policies improves data security and user privacy protection; Improved user experience: A simple and intuitive visual interface and multiple user authentication methods reduce the complexity of user configuration and debugging, improving system usability; The "RPAaaS platform + RPA cloud computer system" technical solution proposed in this invention is superior to existing technologies in terms of integration, resource utilization, security, and user experience, providing strong support for enterprise digital transformation. Detailed Implementation

[0008] The following steps will be used to achieve an out-of-the-box integration method for the RPAaaS platform and RPA cloud computer: Step 1: Adopting the RPAaaS platform + RPA cloud PC model, a unified RPAaaS platform is designed through framework integration technology. The RPAaaS platform includes an RPA engine, an RPA cloud PC management system, a task scheduler, and a security monitoring module. The RPAaaS platform framework supports deep integration with the cloud PC system through APIs, SDKs, or middleware, enabling the RPAaaS platform to seamlessly access the resources and data of the cloud PC system. Step 2: Utilize RPA's Recorder function to record the user's keyboard and mouse input, and integrate these operations into the cloud computer system via API calls to solve the software integration problem of lacking data or application interfaces; Step 3: Adopting end-to-end integrated design and service throughout the product lifecycle, communication and interaction between RPA edge cloud service and central cloud service reduce the overall cloud pressure, facilitate dynamic expansion of RPA cloud computers, and achieve dynamic interoperability and coexistence between RPA cloud edge computing and core computing scheduling. In the cloud, using the unique identifier of the customer, when a customer visits, the client establishes a unique identification identifier in the cloud. By recording the access preferences, web pages visited, consumption habits, lifestyle habits and online time under this unique identifier, corresponding resources and recommended content are matched for the user. This avoids searching for the most suitable information for each user in a massive amount of information. The unique identifier refers to a certain identity or unique identifier of the user in the cloud, including but not limited to identity number, social account, computer device unique identifier, and the user's unique identifier is classified and summarized. Step 4: RPAaaS Platform + RPA Cloud PC Mode. This mode uses a cloud PC system as the execution environment for RPA tasks. It achieves dynamic resource allocation and scheduling through virtualization or hyper-threading technology. The virtualization or hyper-threading technology refers to the ability to identify virtualization or hyper-threading technologies on the access end without considering differences in the access end hardware. The cloud uses these identifiers to identify the corresponding virtualization or hyper-threading technologies. Virtualization or hyper-threading technologies include PC and mobile clients. Mobile clients include virtual Android and virtual Apple clients. PC clients include DOS kernel, Windows kernel, Kylin kernel, Huawei kernel, and LINUX kernel. Windows kernels include, but are not limited to, WINDOWS 92 / 95 / 98 / 2000 / 2003 / XP / 7 / 8 / 10. Step 5: Employ an automated process design pattern, enabling users to design automated processes through the RPAaaS platform's visual interface. The visual interface for designing automated processes includes task definition, triggering conditions, and execution steps. The RPAaaS platform automatically allocates cloud computer resources based on task requirements and generates corresponding execution scripts. Step 6: Adopt a resource management and scheduling model: Introduce an intelligent resource scheduling algorithm to dynamically adjust the allocation of cloud computer resources based on task load and resource usage, monitor resource utilization in real time, and avoid resource idleness or over-allocation; Step 7: Introduce a resource manager component to monitor and allocate resources between the RPAaaS platform and the cloud computer system. The resource manager dynamically adjusts resource allocation according to the needs of RPA tasks to avoid resource idleness or over-allocation. In specific application scenarios, either step 6 or step 7 can be performed. Step 8: Parallel Processing and Load Balancing. Multi-threading and multi-processing techniques are used to achieve parallel processing of RPA tasks. Simultaneously, a load balancing algorithm is employed to evenly distribute tasks among different RPA robots, thereby improving overall execution efficiency. Step 9: The RPAaaS platform + RPA cloud desktop mode enhances security by providing multiple security measures on the RPA cloud desktop side, including data encryption, authentication, and access control, to ensure the security and privacy of user data. Step 10: Identity Authentication and Authorization: Assign a unique identity to each RPA robot program and process, and ensure accountability for robot program behavior and access security through identity authentication and authorization mechanisms; Step 11: Audit Logs and Monitoring: Implement comprehensive audit logging and monitoring, recording monitoring data for all bot interactions, users, and transactions. This helps to promptly detect and prevent potential abuse and fraud. Step 12: Compliance Management: Ensure the RPAaaS platform meets the strictest enterprise security compliance requirements, providing a traceable tracking mechanism to assist platform administrators in identifying and locating problems; Step 13: To address poor user experience: The RPAaaS platform + RPA cloud desktop mode uses preset process templates. The RPA cloud desktop provides preset process templates, and users can choose the appropriate template according to their needs. Step 14: Simultaneously, by implementing an automation script library, RPA Cloud Desktop provides a rich library of automation scripts, which users can directly call to achieve various automated tasks. These script libraries include automation scripts for various common scenarios; Step 15: Zero-code Development: Provides zero-code development capabilities, enabling business users to easily create and configure RPA processes without requiring in-depth programming knowledge. This greatly simplifies the configuration and debugging process, improving the user experience; Step 16: One-stop service platform: Build a one-stop service platform that integrates the functions of the RPAaaS platform and the cloud PC system. Users can easily access and manage all RPA tasks and cloud PC resources through this platform; Step 17: Intelligent Recommendations and Self-Service: Utilize the intelligent capabilities of RPA to provide users with personalized recommendations and self-service options.

[0009] Example 1. Using virtualization technology to convert a wireless keyboard or mouse into a PS / 2 or PS keyboard and mouse, applicable to many industries. In robot control, the operating system of the equipment is often a relatively simple DOS operating system or Windows 92 / 95, etc. Windows 92 / 95 recognizes PS / 2 or PS keyboards and mice, but the actual keyboard or mouse used is a USB keyboard / mouse or a wireless keyboard / mouse. Technically, using a virtual system like Windows 7 / 10 for simulated control in the cloud or on a server is not a problem. The issue lies in the large capacity of these systems. While Windows 92 / 95 can meet the requirements in terms of security and capacity, industrial control has high security requirements. Unified command issuance from the cloud or server poses serious security risks. Therefore, using a virtual system with industrial robots for data processing is more appropriate. If high security can be achieved through transmission and control, then it is only necessary to collect the keyboard control key instructions or character sets, virtualize the USB keyboard as a PS keyboard, and then write virtual PS keyboard types according to the instructions or character sets. It should be noted that when calling virtual keyboard types, since the instructions and character sets used by industrial control itself are limited, regardless of the type of physical keyboard, it is only necessary to virtualize all the characters and instruction sets. Through this step, regardless of the type of operating system of the client, Windows 92 can be used as the operating system to interact with the client in industrial control. The advantage of this is that a virtual system is obtained with very little memory, while being compatible with both new and old keyboards. Similarly, early floppy disks or hard disks can be virtualized, so that communication between different hardware can be achieved between the cloud and the client.

[0010] Example 2. Optimization algorithm: Weighted Round Robin. Principle: Each RPA robot is assigned a different weight based on factors such as its processing capacity. Robots with higher weights have a greater probability of being assigned tasks during polling, thus more rationally allocating task load. Formula: Let the robot's weight be W. j , The total weight is W= If the current task number is i, then the assigned robot number is k, where k = (ixS / W)%n, and S is the sum of the weights of the robots whose cumulative weights first exceed ixW. For example, if there are 3 robots with weights of 2, 3, and 5 respectively, the total weight W = 2 + 3 + 5 = 10. The current task is the 4th task, 4 * 10 = 40. The weight sum of the first robot is 2, the weight sum of the second robot is 2 + 3 = 5, and the weight sum of the third robot is 2 + 3 + 5 = 10. The third robot is the first to exceed 4 x 10 = 40, so the task is assigned to the 3rd robot. By using the weighted round-robin algorithm, system resources can be allocated reasonably, preventing resource idleness or overuse.

[0011] Example 3: Task Scheduler Code Sample import java.util.ArrayList; importjava.util.List:importjava.util.concurrent.ConcurrentLinkedQueue: import java.util.concurrent.ExecutorService;importjava.util.concurrent.Executors; public class OptimizedWeightedRoundRobinScheduler{ / / Robot definition static class Robot { private final String id; private int baseWeight; / / Initial weight private int currentWeight; / / Dynamic weight private int taskCount; / / Number of assigned tasks private boolean available; / / Whether it is available public Robot(String id, int baseWeight) { thisid = id; this.baseWeight = baseWeight; this.currentWeight = 0; this.taskCount = 0; this.available = true; / / Default available public synchronized void assignTask() { taskCount++; } public synchronized boolean isAvailable() { return available; public synchronized void setAvailable(boolean available) { this.available = available; } public synchronized void adjustWeight(boolean increase) if (increase) baseWeight += 1; / / Increase weight 0 else if (baseWeight > 1) { baseWeight -= 1; / / Decrease weight, but minimum is 1 public int getBaseWeight() { return baseWeight; public int getCurrentWeight() { return currentWeight;} public synchronized void increaseCurrentWeight(int delta) { this.currentWeight += delta;} public synchronized void decreaseCurrentWeight(int totalWeight) { this.currentWeight -= totalWeight; It should be noted that there is a misspelling in the original text. In line , it should be "return" instead of "retum". The above translation has corrected this error.@Override public String toString(){ retun "Robot{id=" + id + ", baseWeight=" + baseWeight + ", taskCount=" + taskCount + }'; } } / / Scheduler public static class Scheduler { private final List <robot>robots; private final ConcurrentLinkedQueue <string>taskQueue; / / Task queue private final ExecutorService executor; public Scheduler(List <robot>robots) { this.robots = robots; this.taskQueue = new ConcurrentLinkedQueue<>()); this.executor = Executors.newFixedThreadPool(robots.size()); } / / Submit task public void submitTask(String task) { taskQueue.add(task); scheduleTask();} / / Task scheduling private void scheduleTask() { executor.submit(() -> { while (taskQueue.isEmpty()) { Robot selectedRobot = selectRobot(); if (selectedRobot != null && selectedRobot.isAvailable()) { String task = taskQueue.poll(); if (task != null) { executeTask(selectedRobot, task); }); } / / Select robot private Robot selectRobot() { Robot selected = null; / / Increase the currentWeight of all robots int totalWeight = robots.stream().mapToInt(Robot::getBaseWeight).sum(); for (Robot robot : robots) { if (robot.isAvailable()) { robot.increaseCurrentWeight(robot.getBaseWeight()); / / Select the robot with the largest currentWeight for (Robot robot: robots){ if (robot.isAvailable()&&(selected -null | robot.getCurrentWeight()>selected.getCurrentWeight))){ selected = robot; } / / Subtract the total weight balance state if (selected != null) { selected.decreaseCurrentWeight(totalWeight); )} Return selected: / / Execute task private void executeTask(Robot robot, String task){System.out.println("Executing task:"+ task + " on" + robot.id); try{ / / Simulate task execution time Thread.sleep(1000); robot.assignTask(); / / Dynamically adjust weights (increase weights when the simulation success rate is high) robot.adjustWeight(true);} catch (Exception e){ System.err.println("Task execution failed on " + robotid + ": "+e.getMessage(0); / / Dynamically call Integer weight (reduce weight upon failure) robot.adjustWeight(false); )} } / / Test code public static void main(String] args){ List <robot>robots = new ArrayList<>0; robots.add(new Robot("Robot1", 5)); / / High priority robots.add(new Robot("Robot2", 3)); / / Medium weight robots.add(new Robot("Robot3",2)); / / Low priority Scheduler scheduler = new Scheduler(robots); / / Submit multiple tasks for (int i = 1; i <= 20; i++){ scheduler.submitTask("Task" + i); / / Wait for all tasks to complete scheduler.executor.shutdown(); 1j}.

[0012] Example 4: Key Code for Task Retry Mechanism The code is as follows public class RetryPolicy{ private static final int MAX_RETRIES =3: public boolean retry(Task task, Robot robot){ for (int attempt =1; attempt<= MAX_RETRIES; attempt++){ try{ robot.executeTask(task); / / Execute the task return true;} catch (Exception e){ System.out.println('"Retry attempt " +attempt +"failed for task:" +task.getId)); } ) return false; / / Retry count reached}

[0013] Example 5: Key Code for Health Monitoring The code is as follows: public class RobotHealthMonitor { private final ScheduledExecutorService executor = Executors.newScheduledThreadPool(1); public void startHealthCheck(Map<String, Robot> robotPool){ executor.scheduleAtFixedRate(() ->{ robotPool.forEach((id, robot) ->{ if(Irobot.isAlive()){ System.out.println("Robot " +id + " is down!"); robot.setAvailable(false); / / Mark as unavailable }); },0,5,TimeUnit.SECONDS); )} }< / robot> < / robot> < / string> < / robot> It should be noted that there is a spelling mistake in line where "retun" should be "return".

Claims

1. A RPAaaS platform + RPA cloud computer out-of-box integration method, characterized by: The out-of-the-box integration method of RPAaaS platform + RPA cloud computer is completed by the following steps. In the execution of these steps, the numbering is only for record-keeping convenience. In specific application scenarios, it is necessary to treat them flexibly according to the specific situation: Step 1: Adopting the RPAaaS platform + RPA cloud PC model, a unified RPAaaS platform is designed through framework integration technology. The RPAaaS platform includes an RPA engine, an RPA cloud PC management system, a task scheduler, and a security monitoring module. The RPAaaS platform framework supports deep integration with the cloud PC system through APIs, SDKs, or middleware. The RPAaaS platform can seamlessly access the resources and data of the cloud PC system. Step 2: Use the Recorder function of RPA to record the user's keyboard and mouse input, and integrate these operations into the cloud computer system through API calls to solve the software integration problem of lacking data interface or application interface; Step 3: Adopting end-to-end integrated design and service throughout the product lifecycle, communication and interaction between RPA edge cloud service and central cloud service reduce the overall cloud pressure, facilitate dynamic expansion of RPA cloud computers, and achieve dynamic interoperability and coexistence between RPA cloud edge computing and core computing scheduling. In the cloud, using the unique identifier of the customer, when a customer visits, the client establishes a unique identification identifier in the cloud. By recording the access preferences, web pages visited, consumption habits, lifestyle habits and online time under this unique identifier, corresponding resources and recommended content are matched for the user. This avoids searching for the most suitable information for each user in a massive amount of information. The unique identifier refers to a certain identity or unique identifier of the user in the cloud, including but not limited to identity number, social account, computer device unique identifier, and the user's unique identifier is classified and summarized. Step 4: RPAaaS Platform + RPA Cloud PC Mode. This mode uses a cloud PC system as the execution environment for RPA tasks. It achieves dynamic resource allocation and scheduling through virtualization or hyper-threading technology. The virtualization or hyper-threading technology refers to the ability to identify virtualization or hyper-threading technologies on the access end without considering differences in the access end hardware. The cloud uses these identifiers for identification. Virtualization or hyper-threading technologies include PC and mobile clients. Mobile clients include virtual Android and virtual Apple clients. PC clients include DOS kernel, Windows kernel, Kylin kernel, Huawei kernel, and LINUX kernel. Windows kernels include, but are not limited to, WINDOWS 92 / 95 / 98 / 2000 / 2003 / XP / 7 / 8 / 10. Step 5: Adopt an automated process design pattern, enabling users to design automated processes through the visual interface of the RPAaaS platform. The visual interface for designing automated processes includes task definition, triggering conditions, and execution steps. The RPAaaS platform automatically allocates cloud computer resources according to task requirements and generates corresponding execution scripts. Step 6: Adopt a resource management and scheduling mode, introduce intelligent resource scheduling algorithms, dynamically adjust the allocation of cloud computer resources according to task load and resource usage, monitor resource utilization in real time, and avoid resource idleness or over-allocation. Step 7: Introduce a resource manager component to monitor and allocate resources between the RPAaaS platform and the cloud computer system. The resource manager dynamically adjusts resource allocation according to the needs of RPA tasks to avoid resource idleness or over-allocation. In specific application scenarios, either step 6 or step 7 can be performed. Step 8: Parallel processing and load balancing. Utilizing multi-threading and multi-processing techniques, parallel processing of RPA tasks is achieved. Simultaneously, a load balancing algorithm is used to evenly distribute tasks among different RPA robots to improve overall execution efficiency. Step 9: The RPAaaS platform + RPA cloud desktop mode enhances security by providing multiple security measures on the RPA cloud desktop side, including data encryption, authentication, and access control, to ensure the security and privacy of user data. Step 10: Identity Authentication and Authorization. Assign a unique identity to each RPA robot program and process, and ensure accountability for robot program behavior and access security through identity authentication and authorization mechanisms. Step 11: Audit Logs and Monitoring. Implement comprehensive audit logging and monitoring, recording monitoring data for all bot interactions, users, and transactions. This helps to promptly detect and prevent potential abuse and fraud. Step 12: Compliance management, ensuring that the RPAaaS platform meets the most stringent enterprise security compliance requirements, providing a traceable tracking mechanism to assist platform administrators in identifying and locating problems; Step 13: To address the issue of poor user experience, the RPAaaS platform + RPA cloud desktop mode provides preset process templates. Users can choose the appropriate template based on their needs. Step 14: At the same time, by implementing an automation script library, RPA Cloud Desktop provides a rich automation script library, which users can directly call to implement various automation tasks. These script libraries include automation scripts for various common scenarios. Step 15: Zero-code development. This provides zero-code development capabilities, enabling business users to easily create and configure RPA processes without requiring in-depth programming knowledge. This significantly simplifies the configuration and debugging process, improving the user experience. Step 16: One-stop service platform. Build a one-stop service platform that integrates the functions of the RPAaaS platform and the cloud PC system. Users can easily access and manage all RPA tasks and cloud PC resources through this platform; Step 17: Intelligent Recommendations and Self-Service. Utilize the intelligent capabilities of RPA to provide users with personalized recommendations and self-service options. This can further improve user satisfaction and efficiency.

2. The integration method of RPAaaS platform + RPA cloud computer out-of-the-box as described in claim 1, characterized in that: The intelligent resource scheduling algorithm works by assigning different weights to each RPA robot based on factors such as its processing capacity. Robots with higher weights have a greater probability of being assigned tasks during polling, thus more rationally allocating task load. Formula: Let the robot's weight be W. j The total weight is W= If the current task number is i, then the assigned robot number is k, where k = (ixS / W)%n, and S is the weight sum of the robot from the first robot up to the current cumulative weight sum that first exceeds ixW.

3. The integration method of RPAaaS platform + RPA cloud computer out-of-the-box as described in claim 1, characterized in that: The RPAaaS platform + RPA cloud PC mode uses a cloud PC system as the execution environment for RPA tasks. It achieves dynamic resource allocation and scheduling through virtualization or hyper-threading technology. This virtualization or hyper-threading technology refers to the ability to identify virtualization or hyper-threading technologies on the access end without considering differences in the access end hardware. The cloud uses these identifiers for identification. Virtualization or hyper-threading technologies include PC and mobile clients. Mobile clients include virtual Android and virtual Apple clients. PC clients include DOS kernel, Windows kernel, Kylin kernel, Huawei kernel, and Linux kernel. Windows kernels include, but are not limited to, Windows 92, 95, 98, 2000, 2003, XP, 7, 8, and 10.

4. The integration method of RPAaaS platform + RPA cloud computer out-of-the-box as described in claim 1, characterized in that: The keyboard commands and character sets are categorized according to the types of keyboards available on the market, and then the keyboard type numbers are written into the cloud database. Based on different application scenarios, the virtual operating system with the smallest capacity is selected while meeting the needs. After the data from the physical keyboard is sent to the virtual system, the keyboard commands or character sets are executed using the keyboard of the virtual system. In this way, the virtual operating system in the cloud and the operating system and hardware of the physical terminal are separated.