Intelligent management system and method for tablet personal computer

Abstract

The invention relates to the field of computer management, and discloses a tablet personal computer intelligent management system and method.The tablet personal computer intelligent management system comprises a multi-dimensional equipment attribute collection module, the multi-dimensional equipment attribute collection module collects equipment hardware features, software states and network environment data in real time and transmits the collected information to a management authority distribution module; the multi-dimensional equipment attribute acquisition module is connected with a management authority distribution module, and the management authority distribution module performs calculation according to a multi-dimensional data using algorithm so as to distribute corresponding authority management to the current tablet personal computer. According to the invention, through the multi-dimensional equipment attribute acquisition module and the sub-modules including equipment feature recognition, user and equipment association, dynamic environment perception and the like, equipment hardware features can be comprehensively and accurately acquired, dynamic grouping is intelligently carried out from multiple aspects, different management authorities are provided for different groups, and the management efficiency is improved. And the tablet computer management system is more convenient and accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of computer management, and particularly to an intelligent management system and method for a tablet computer. Background Art

[0002] Due to its portability and versatility, tablet computers are widely used in various fields. In enterprises, employees in different departments use tablet computers to perform different tasks. The sales team uses them to display products, field staff use them for mobile office, and R & D personnel use them for data testing, etc. Different usage scenarios have huge differences in the permission requirements for tablet computers.

[0003] Currently, most tablet computer management systems mainly focus on basic device information management and simple user permission settings. In terms of device information management, basic information such as the brand, model, and factory serial number of the device is mainly recorded, and these information are entered into the system through device registration. In terms of permission settings, it is usually divided according to user roles, such as ordinary users, administrators, etc., and fixed operation permissions are assigned to different roles. For example, ordinary users may only be able to use specific applications, while administrators have all permissions. At the same time, the system will conduct certain control over the applications on the device, and batch installation and uninstallation operations of applications can be performed, but the overall management method is relatively inflexible.

[0004] However, there are many obvious deficiencies in the existing tablet computer management systems. At the level of device attribute collection, it is impossible to comprehensively and accurately obtain the hardware characteristics of the device. Information such as the real-time performance parameters and the degree of hardware aging of the hardware is often ignored. In terms of the software status, only the basic list of installed applications can be mastered, and it is difficult to deeply understand the running status and resource occupancy of the applications. For network environment data, there is even a lack of real-time and dynamic monitoring capabilities. In the permission management link, due to its static permission allocation mode, it is unable to adapt to diverse usage scenarios. For example, when enterprise employees use tablet computers in different geographical locations and different network environments, the system cannot flexibly adjust permissions according to environmental changes, resulting in the risk of sensitive data leakage in an insecure network environment, or in special work scenarios, employees cannot complete tasks in a timely manner due to insufficient permissions, seriously affecting work efficiency and data security. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides an intelligent management system and method for a tablet computer, which solves the problems that the existing tablet computer management systems cannot comprehensively and accurately obtain information such as real-time performance parameters and aging degree of the hardware in device attribute collection, have insufficient understanding of the running status and resource occupancy of the software, lack real-time and dynamic monitoring capabilities for network environment data, and at the same time, the permission management link adopts a static allocation mode, which is difficult to adapt to diverse usage scenarios and is prone to data security risks and low work efficiency problems.

[0006] To achieve the above object, the present invention is implemented through the following technical solutions: An intelligent management system for a tablet computer, including a multi-dimensional device attribute collection module, which collects device hardware characteristics, software status, and network environment data in real time, and transmits the collected information to the management permission allocation module. The multi-dimensional device attribute collection module is connected to the management permission allocation module. The management permission allocation module calculates using an algorithm based on multi-dimensional data, so as to allocate corresponding permission management for the current tablet computer, and transmits the permission content to the user management module and the device management module. The management permission allocation module is connected to the user management module. The user management module is responsible for managing the user's permission level, role attributes, and corresponding authentication capabilities according to the result given by the management permission allocation module. The user management module is connected to the device management module. The device management module integrates the device attributes and the user identity according to the result given by the management permission allocation module, and executes device status control. The device management module is connected to an interaction module. At the same time, the staff directly changes the permissions of the current device management module by inputting a secret key from the outside through the interaction module. The management permission allocation module is connected to a notification module, and the notification module transmits the permission allocation message to the staff according to the result of the management permission allocation module.

[0007] Preferably, the multi-dimensional device attribute collection module includes a device feature recognition module, which recognizes and collects the features of the device. The device feature recognition module is connected to a user-device association module. The user-device association module ensures accurate permission binding through multi-factor authentication. The user-device association module is connected to a dynamic environment perception module, which collects the network status, geographical location, and movement trajectory of the environment where the device is located in real time, evaluates the security risk, and triggers permission adjustment.

[0008] Preferably, the device features in the device feature recognition module include: configuration parameters, operating system version, and application list.

[0009] Preferably, the multi-factor authentication in the user-device association module includes face / device code binding, and establishes a dynamic mapping relationship between the user account and the specific device.

[0010] Preferably, the evaluation of security risk and triggering of permission adjustment are specifically:

[0011]

[0012] Where: L represents latency; T represents access type; D represents distance deviation; v represents speed; F represents the frequency of direction change; α, β, γ represent adjustable weight coefficients; R total(L, T, D, v, F) represents the current security risk trust score.

[0013] Preferably, the specific permission adjustment scheme is:

[0014]

[0015] Preferably, the management authority allocation module is connected to a dynamic grouping module, and the dynamic grouping module is provided with a dynamic grouping algorithm, and the dynamic grouping algorithm includes:

[0016] 1. Multi-dimensional attribute fusion algorithm

[0017] Goal: Quantify device usage, user roles, and geographic locations into comparable features;

[0018] Comprehensive score S i =w u ·U i +w r ·R i +w g ·G i

[0019] Among them: U i R stands for purpose focus; i Represents the current role weight; G i represents the geographical location matching degree; w u 、w r 、w g Represents the dynamic weight coefficient; by calculating the S of each device in real time i value, and when S i ≥θ triggers group update (θ=0.75).

[0020] Preferably, the dynamic grouping algorithm further includes: 2. Dynamic clustering grouping algorithm

[0021] Goal: Automatically divide equipment into logical groups such as sales, R&D, and field operations.

[0022] Grouping conditions: Sim(S i ,S j )≥α·density threshold

[0023] Where: Sim(S i ,S j ) represents the normalized similarity; α represents the dynamic adjustment coefficient; and in conjunction with the grouping rules, the grouping rules are specifically as follows: main grouping: preset tags with the highest matching degree; temporary grouping: when a device meets multiple group conditions at the same time, it is grouped according to the priority P=R i +2U i choose.

[0024] Preferably, the dynamic grouping algorithm further includes: 3. Conflict resolution formula

[0025] Final grouping = argmax(λ · Role weight + (1 - λ) · Urgency)

[0026] When the device meets the conditions of both the sales group and the field work group, arbitrate to determine the final grouping of the current device.

[0027] A usage method of a tablet computer intelligent management system includes the following steps:

[0028] S1. Device feature recognition and data initialization: Start the device feature recognition module, collect the hardware configuration, operating system version, and installed application list, generate a unique device code and bind it to the server;

[0029] S2. User-device dynamic association authentication: Complete multi-factor authentication through the user-device association module, and establish a real-time permission mapping relationship between the user account and the device;

[0030] S3. Dynamic environment perception and data collection: Real-time monitor the network latency (L), access type (T), geographical location movement trajectory (D / v / F), calculate the security risk score and trigger permission grading;

[0031] S4. Multidimensional attribute fusion grouping calculation: Generate feature values by integrating device usage focus, user role weight, and geographical matching degree;

[0032] S5. Dynamic clustering and priority arbitration: Match the preset label group through normalized similarity, and preferentially select the highest matching group; if there is a conflict, arbitrate the final grouping according to the preset priority;

[0033] S6. Permission allocation and conflict resolution: Combine the security score and the dynamic grouping permission, with the main grouping permission taking precedence, and a high security risk triggering permission downgrade or freezing;

[0034] S7. Permission execution and device control: The user management module assigns role permissions, the device management module executes the control, and the interaction module supports manual key override;

[0035] S8. Notification and log management: The notification module pushes permission adjustment information to the administrator in real time.

[0036] The present invention provides a tablet computer intelligent management system and method. It has the following beneficial effects:

[0037] 1. Through the multi-dimensional device attribute collection module, which covers sub-modules such as device feature recognition, user-device association, and dynamic environment perception, the present invention can comprehensively and accurately obtain the hardware features of the device, intelligently perform dynamic grouping from multiple aspects, and provide different management permissions for different groups, making the tablet computer management system more convenient and accurate.

[0038] 2. The present invention also utilizes the multi-dimensional attribute fusion algorithm, dynamic clustering grouping algorithm, and conflict resolution formula to group devices according to factors such as usage, user role, and geographical location through algorithms, and effectively arbitrate in case of grouping conflicts, avoiding the situation where the system fails to group the current tablet computer in time when conflicts occur, thus delaying the subsequent work efficiency.

[0039] 3. The present invention can flexibly adjust permissions according to changes in the environment where the device is located, such as network status, geographical location, etc., effectively avoiding the risk of leakage of sensitive data in an insecure network environment, and at the same time ensuring that employees have sufficient permissions to complete tasks in a timely manner in special working scenarios, significantly improving work efficiency and data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is the system flow chart of the present invention;

[0041] Figure 2 is the flow chart of the system usage method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] Embodiment:

[0044] Please refer to the appendix Figure 1 - appendix Figure 2, an embodiment of the present invention provides a tablet computer intelligent management system, including a multi-dimensional device attribute collection module. The multi-dimensional device attribute collection module collects device hardware characteristics, software status, and network environment data in real time, and transmits the collected information to the management permission allocation module. The multi-dimensional device attribute collection module is connected to the management permission allocation module. The management permission allocation module calculates using an algorithm based on the multi-dimensional data, so as to allocate corresponding permission management for the current tablet computer, and transmits the permission content to the user management module and the device management module. The management permission allocation module is connected to the user management module. The user management module is responsible for managing the user's permission level, role attributes, and corresponding authentication capabilities according to the result given by the management permission allocation module. The user management module is connected to the device management module. The device management module integrates the device attributes and the user identity according to the result given by the management permission allocation module, and executes device status control. The device management module is connected to an interaction module. At the same time, the staff can also directly change the permissions of the current device management module by inputting a key from the outside through the interaction module, preventing a poor user experience when the management system has algorithm errors. The management permission allocation module is connected to a notification module. The notification module transmits the permission allocation message to the staff according to the result of the management permission allocation module.

[0045] The multi-dimensional device attribute collection module includes a device feature recognition module. The device feature recognition module identifies and collects the features of the device. The features of the device include: configuration parameters, operating system version, and application list. The device feature recognition module is connected to a user-device association module. The user-device association module establishes a dynamic mapping relationship between the user account and the specific device through multi-factor authentication, including face / device code binding, to ensure accurate permission binding. The user-device association module is connected to a dynamic environment perception module. The dynamic environment perception module collects the network status, geographical location, and movement trajectory of the environment where the device is located in real time, evaluates the security risk, and triggers permission adjustment.

[0046] The specific evaluation of security risk and triggering of permission adjustment is as follows:

[0047]

[0048] Where: L represents latency; T represents access type; D represents distance deviation; v represents speed; F represents the frequency of direction change; α, β, γ represent adjustable weight coefficients; R total (L, T, D, v, F) represents the current security risk trust score;

[0049] The specific permission scheme is as follows:

[0050]

[0051] A dynamic grouping module is connected to the management permission allocation module, and a dynamic grouping algorithm is set in the dynamic grouping module. The specific dynamic grouping algorithm is as follows:

[0052] 1. Multi-dimensional attribute fusion algorithm

[0053] Objective: Quantify device usage, user roles, and geographical locations into comparable features;

[0054] Comprehensive score S i = w u ·U i + w r ·R i + w g ·G i

[0055] Where: U i represents the usage focus; R i represents the current role weight; G i represents the geographical location matching degree; w u 、w r 、w g represent dynamic weight coefficients; by calculating the S i value of each device in real time, and triggering group update when S i ≥ θ (θ = 0.75);

[0056] 2. Dynamic clustering grouping algorithm

[0057] Objective: Automatically divide devices into logical groups such as sales group, R & D group, and field work group;

[0058] Grouping conditions: Sim(S i , S j ) ≥ α · density threshold

[0059] Where: Sim(S i , S j ) represents the normalized similarity; α represents the dynamic adjustment coefficient; and in combination with the grouping rules, the specific grouping rules are as follows: Main grouping: The preset label with the highest matching degree; Temporary grouping: When a device meets multiple group conditions, select according to the priority P = R i + 2U i ;

[0060] 3. Conflict resolution formula

[0061] Final grouping = argmax(λ · role weight + (1 - λ) · urgency)

[0062] Arbitrate when the device meets the conditions of both the sales group and the field work group to determine the final grouping of the current device.

[0063] A usage method of a tablet computer intelligent management system, comprising the following steps:

[0064] S1. Device feature recognition and data initialization: Start the device feature recognition module, collect the hardware configuration, operating system version, and installed application list, generate a unique device code, and bind it to the server;

[0065] S2. User-device dynamic association authentication: Complete multi-factor authentication through the user-device association module, and establish a real-time permission mapping relationship between the user account and the device;

[0066] S3. Dynamic environment perception and data collection: Real-time monitor the network latency (L), access type (T), geographical location movement trajectory (D / v / F), calculate the security risk score, and trigger permission grading;

[0067] S4. Multi-dimensional attribute fusion grouping calculation: Generate feature values by comprehensively considering the device usage focus, user role weight, and geographical matching degree;

[0068] S5. Dynamic clustering and priority arbitration: Match the preset label group through normalized similarity, and preferentially select the highest matching group; if there is a conflict, arbitrate the final group according to the preset priority;

[0069] S6. Permission allocation and conflict resolution: Combine the security score with the dynamic grouping permission, with the main grouping permission taking precedence, and a high security risk triggering permission downgrade or freezing;

[0070] S7. Permission execution and device control: The user management module assigns role permissions, the device management module executes control, and the interaction module supports manual key override;

[0071] S8. Notification and log management: The notification module pushes permission adjustment information to the administrator in real time.

[0072] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tablet computer intelligent management system, characterized in that, It includes a multi-dimensional device attribute collection module which collects device hardware features, software status, and network environment data in real time and transmits the collected information to the management permission allocation module. The multi-dimensional device attribute collection module is connected to the management permission allocation module. The management permission allocation module calculates using an algorithm based on multi-dimensional data to allocate corresponding permission management for the current tablet computer and transmits the permission content to the user management module and the device management module. The management permission allocation module is connected to the user management module. The user management module is responsible for managing the user's permission level, role attributes, and corresponding authentication capabilities according to the result given by the management permission allocation module. The user management module is connected to the device management module. The device management module integrates device attributes and user identities according to the result given by the management permission allocation module and executes device status control. The device management module is connected to an interaction module. At the same time, the staff directly changes the permissions of the current device management module by inputting a key from the outside through the interaction module. The management permission allocation module is connected to a notification module. The notification module transmits the permission allocation message to the staff according to the result of the management permission allocation module.

2. The intelligent management system for a tablet computer according to claim 1, characterized in that, The multi-dimensional device attribute collection module includes a device feature recognition module which recognizes and collects the features of the device. The device feature recognition module is connected to a user-device association module. The user-device association module ensures accurate binding of permissions through multi-factor authentication. The user-device association module is connected to a dynamic environment perception module. The dynamic environment perception module collects the network status, geographical location, and movement trajectory of the environment where the device is located in real time, evaluates security risks, and triggers permission adjustment.

3. A tablet computer intelligent management system according to claim 1, characterized in that, The device features in the device feature recognition module include: configuration parameters, operating system version, and application list.

4. A tablet computer intelligent management system according to claim 1, characterized in that, The multi-factor authentication in the user-device association module includes face / device code binding to establish a dynamic mapping relationship between the user account and the specific device.

5. An intelligent management system for a tablet computer according to claim 2, characterized in that, The evaluation of security risks and the triggering of permission adjustment solutions include: Where: L represents delay; T represents access type; D represents distance deviation; v represents speed; F represents direction change frequency; α, β, γ represent adjustable weight coefficients; R total (L, T, D, v, F) represents the current security risk trust score.

6. An intelligent management system for a tablet computer according to claim 5, characterized in that, The specific permission adjustment solutions include:

7. The intelligent management system for a tablet computer according to claim 1, characterized in that, The management permission allocation module is connected to a dynamic grouping module. A dynamic grouping algorithm is set in the dynamic grouping module. The dynamic grouping algorithm includes:

1. Multi-dimensional attribute fusion algorithm Objective: Quantify device usage, user role, and geographical location into comparable features; Comprehensive score S i = w u ·U i + w r ·R i + w g ·G i Among them: U i represents the degree of focus on usage; R i represents the current role weight; G i represents the geographical location matching degree; w u , w r , w g represent dynamic weight coefficients; by calculating the S i value of each device in real time, and triggering group update when S i ≥θ (θ = 0.75).

8. An intelligent management system for a tablet computer according to claim 7, characterized in that, The dynamic grouping algorithm also includes:

2. Dynamic clustering grouping algorithm Objective: Automatically divide devices into logical groups such as the sales group, R & D group, and field work group; Grouping conditions: Among them: Sim(S i ,S j ) represents the normalized similarity; α represents the dynamic adjustment coefficient; and in combination with the grouping rule, the grouping rule is specifically as follows: main grouping: the preset label with the highest matching degree; temporary grouping: when the device satisfies multiple group conditions at the same time, select according to the priority P = R i +2U i Selection.

9. An intelligent management system for a tablet computer according to claim 7, characterized in that, The dynamic grouping algorithm also includes:

3. Conflict resolution formula Final grouping = argmax(λ · role weight + (1 - λ) · urgency) Arbitrate when the device meets the conditions of both the sales group and the field work group to determine the final grouping of the current device.

10. A method for using a tablet computer intelligent management system according to any one of claims 1-9, characterized in that, It includes the following steps: S1. Device feature recognition and data initialization: Start the device feature recognition module, collect hardware configuration, operating system version, and installed application list, generate a unique device code, and bind it to the server; S2. User-Device Dynamic Association Authentication: Multifactor authentication is completed through the user-device association module, and a real-time permission mapping relationship between the user account and the device is established; S3. Dynamic Environment Perception and Data Collection: The network latency (L), access type (T), and geographical location movement trajectory (D / v / F) are monitored in real time, and the security risk score is calculated and the permission level is triggered; S4. Multidimensional Attribute Fusion Grouping Calculation: Feature values are generated by comprehensively considering the device usage focus, user role weight, and geographical matching degree; S5. Dynamic Clustering and Priority Arbitration: The preset tag group is matched through normalized similarity, and the highest matching group is preferentially selected; If there is a conflict, the final grouping is arbitrated according to the preset priority; S6. Permission Allocation and Conflict Resolution: The security score is combined with the dynamic grouping permission, with the main grouping permission taking precedence, and a high security risk triggers permission downgrading or freezing; S7. Permission Execution and Device Control: The user management module assigns role permissions, the device management module executes the control, and the interaction module supports manual key override; S8. Notification and Log Management: The notification module pushes the permission adjustment information to the administrator in real time.

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