Practical training working method and system for Internet of Things

Abstract

The invention discloses an Internet of Things practical training working method and system, and the method comprises the steps: firstly obtaining an Internet of Things scheme demand sent by a target enterprise, and then determining the matching degree between the Internet of Things scheme demand and a practical training target; if it is judged that the matching degree is larger than a preset matching degree threshold value, at least one practical training task is generated according to the Internet of Things scheme requirement, the practical training task is issued to a target Internet of Things practical training terminal, and the target Internet of Things practical training terminal can execute the practical training task to meet the requirement of a target enterprise; and then, obtaining first scheme information generated by the target Internet of Things practical training terminal according to the practical training task, and sending the first scheme information to the target enterprise so as to cooperate with the research and development process of the target enterprise. According to the invention, the practical demands of the target enterprise and the education resources of the target Internet of Things practical training terminal can be organically fused through the Internet of Things practical training working system, the research and development process of the target enterprise is improved, and the target Internet of Things practical training terminal is facilitated to carry out education and teaching.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things training, and in particular to an Internet of Things training working method and system. Background Art

[0002] With the continuous development of artificial intelligence technology, the content and methods of IoT teaching in colleges and universities are also constantly changing. IoT training equipment is an IoT training teaching platform that integrates teaching, competition, industrial control, and environmental monitoring development. It can comprehensively assess students' mastery of knowledge and formulate teaching plans accordingly.

[0003] At present, there are many problems in the use of IoT training equipment. For example, the setting of IoT training courses is not scientific and reasonable enough to adapt to the actual R&D process of IoT companies; the IoT training process lacks the input of high-quality resources from IoT companies, making it impossible to organically integrate industrial resources and educational resources. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an Internet of Things training method.

[0005] To achieve the above purpose, the technical solution provided by the present invention is:

[0006] A practical training method for the Internet of Things, comprising:

[0007] Obtaining IoT solution requirements sent by the target enterprise, wherein the IoT solution requirements include business functions in a specific scenario;

[0008] Determine the matching degree between the IoT solution requirements and the training objectives, wherein the training objectives include a plurality of IoT key technologies that need to be mastered through training;

[0009] If the matching degree is greater than the preset matching degree threshold, at least one training task is generated according to the IoT solution requirements, and the training task includes functional requirements, security requirements and reliability requirements; otherwise, it means that the design of the specific IoT solution is inconsistent with the training objectives of the IoT training control center. At this time, it is necessary to feedback the matching degree and the preset matching degree threshold between the IoT solution requirements and the training objectives to the target enterprise, so as to inform the target enterprise that the design of the specific IoT solution is inconsistent with the training objectives of the IoT training control center, for reference by the target enterprise.

[0010] Sending the training task to the target IoT training terminal;

[0011] The first solution information generated by the target Internet of Things training terminal according to the training task is obtained, and the first solution information is sent to the target enterprise, wherein the first solution information includes first perception layer information, first network transmission layer information and first application layer information.

[0012] Furthermore, it also includes:

[0013] Obtaining feedback information from the target enterprise on the first solution information, and sending the feedback information to the target Internet of Things training terminal, wherein the feedback information includes security vulnerability information, functional vulnerability information, and reliability information;

[0014] The second solution information generated by the target Internet of Things training terminal according to the feedback information is obtained, and the second solution information is sent to the target enterprise, where the second solution information includes second perception layer information, second network transmission layer information and second application layer information.

[0015] Furthermore, the target Internet of Things training terminal is determined by:

[0016] Determine task label information of the practical training task;

[0017] Determine the training course label information of the candidate IoT training terminal;

[0018] Analyze the correlation between the task label information and the training course label information through a semantic model to determine the IoT training terminal with the highest correlation with the training task, where different IoT training terminals are configured with different training sensors;

[0019] The Internet of Things training terminal that is most relevant to the training task is determined as the target Internet of Things training terminal.

[0020] Furthermore, before sending the training task to the target IoT training terminal, the method further includes:

[0021] Determine a deadline for the solution according to the IoT solution requirements, and determine a deadline for the training task according to the deadline for the solution;

[0022] Sending the training task to the target IoT training terminal also includes:

[0023] The task deadline and the training task are sent together to the target Internet of Things training terminal.

[0024] Furthermore, the method further includes: determining an abnormal training task that exceeds the task deadline and an abnormal Internet of Things training terminal corresponding to the abnormal training task;

[0025] Obtaining description information of the abnormal Internet of Things training terminal on the abnormal training task;

[0026] If the description information is the first type of description information, extending the task deadline according to the solution deadline;

[0027] If the description information is the second type of description information, the abnormal training task is resent to other Internet of Things training terminals.

[0028] Furthermore, it also includes:

[0029] If the description information is the second type of description information, the course generation information is sent to the target enterprise, the target training course prepared by the target enterprise according to the course generation information is obtained, and the target training course is sent to the abnormal Internet of Things training terminal.

[0030] Furthermore, it also includes:

[0031] Obtaining evaluation information of the abnormal Internet of Things training terminal on the target training course;

[0032] The evaluation information is sent to the target enterprise.

[0033] Furthermore, it also includes:

[0034] Obtaining update information of the target enterprise on the target training course according to the evaluation information;

[0035] The update information is sent to the abnormal Internet of Things training terminal.

[0036] Furthermore, determining the matching degree between the IoT solution requirements and the training objectives includes:

[0037] Determine the requirement tag information of the IoT solution requirement;

[0038] Determine the target label information of the training target;

[0039] Analyzing the matching degree between the demand label information and the target label information through a semantic model, and determining the matching degree between the demand label information and the target label information as the matching degree between the IoT solution requirement and the training objective;

[0040] When training the semantic model, the following loss function F is used to measure the difference between the predicted result of the semantic model and the true label, where a represents the main sentence, p represents the positive sentence, n represents the negative sentence, S represents the sentence embedding vector of a, p, and n, ||·|| represents the distance, and d represents S p With S n The distance between

[0041] F=max(||S a -S p ||-||S a -S n ||+d,0).

[0042] To achieve the above object, the present invention further provides an Internet of Things training system for implementing the above Internet of Things training method, comprising:

[0043] An acquisition module, used to acquire the IoT solution requirements sent by the target enterprise, wherein the IoT solution requirements include business functions under specific scenarios;

[0044] A determination module, used to determine the matching degree between the IoT solution requirements and the training objectives, wherein the training objectives include a plurality of IoT key technologies that need to be mastered through training;

[0045] A generation module, configured to generate at least one training task according to the IoT solution requirements if the matching degree is greater than a preset matching degree threshold, wherein the training task includes at least functional requirements, safety requirements, and reliability requirements;

[0046] A sending module, used for sending the training task to a target IoT training terminal;

[0047] The sending module is used to obtain the first solution information generated by the target Internet of Things training terminal according to the training task, and send the first solution information to the target enterprise, wherein the first solution information includes first perception layer information, first network transmission layer information and first application layer information.

[0048] Compared with the prior art, the principles and advantages of this technical solution are as follows:

[0049] First, the IoT solution requirements sent by the target enterprise are obtained, and then the matching degree between the IoT solution requirements and the training objectives is determined; if the matching degree is judged to be greater than the preset matching degree threshold, at least one training task is generated according to the IoT solution requirements, and the training task is sent to the target IoT training terminal, and the target IoT training terminal can perform the training task to meet the needs of the target enterprise; then, the first solution information generated by the target IoT training terminal according to the training task is obtained, and the first solution information is sent to the target enterprise, so as to cooperate with the research and development process of the target enterprise. Through the IoT training work system, the actual needs of the target enterprise can be organically integrated with the educational resources of the target IoT training terminal, which can improve the research and development process of the target enterprise and facilitate the education and teaching of the target IoT training terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 This is a connection block diagram of an Internet of Things training system according to Embodiment 1 of the present invention;

[0052] Figure 2 The present invention is a flowchart of the working principle of an Internet of Things training method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The present invention will be further described below in conjunction with specific embodiments:

[0054] like Figure 1 As shown, the Internet of Things training system described in this embodiment includes an acquisition module, a determination module, a generation module, a distribution module, and a sending module.

[0055] like Figure 2 As shown, the working principle of the Internet of Things training system is as follows:

[0056] S1. Obtain IoT solution requirements sent by the target enterprise through the acquisition module;

[0057] Among them, the IoT solution requirements include business functions under specific scenarios. The IoT solution requirements come from the actual needs of IoT companies in production and operation activities. In the traditional model, IoT companies use internal designers to complete specific IoT solution designs. When the business volume of IoT companies is large, the efficiency of IoT solution design cannot be guaranteed by using internal designers to complete specific IoT solution designs. In this embodiment, when the target company has a large business volume, the IoT solution requirements can be sent to the IoT training work system.

[0058] S2. Determine the matching degree between the IoT solution requirements and the training objectives through a determination module;

[0059] Among them, the training objectives include multiple key IoT technologies that need to be mastered through training, such as key technologies of industrial IoT, key technologies of IoT perception, key technologies of embedded technology, key technologies of machine vision and sorting technology, robot-related skills and key technologies of drones.

[0060] The IoT solution requirement involves the design of a specific IoT solution, and the design of a specific IoT solution may or may not be consistent with the training objectives of the IoT training work system. This implementation method determines whether the design of a specific IoT solution is consistent with the training objectives of the IoT training work system by determining the degree of matching between the IoT solution requirement and the training objectives.

[0061] Furthermore, when determining the matching degree between the IoT solution requirements and the training objectives, the requirement label information of the IoT solution requirements is first determined, and then the target label information of the training objectives is determined. Finally, the matching degree between the requirement label information and the target label information is analyzed through the semantic model, and the matching degree between the requirement label information and the target label information is determined as the matching degree between the IoT solution requirements and the training objectives.

[0062] When training the semantic model, the following loss function F is used to measure the difference between the predicted result of the semantic model and the true label, where a represents the main sentence, p represents the positive sentence, n represents the negative sentence, S represents the sentence embedding vector of a, p, and n, ||·|| represents the distance, and d represents S p With S n The distance between

[0063] F=max(||S a -S p ||-||S a -S n ||+d,0);

[0064] The semantic model analyzes the matching degree between the required label information and the target label information with high accuracy. When training the semantic model, the training data can be divided into a training set, a test set, and a validation set, and the parameters of the semantic model can be cross-validated through the training set, the test set, and the validation set.

[0065] S3. If the matching degree is greater than the preset matching degree threshold, at least one training task is generated according to the IoT solution requirements through the generation module, and the training task includes at least functional requirements, security requirements and reliability requirements; otherwise, it means that the design of the specific IoT solution is inconsistent with the training objectives of the IoT training control center. At this time, it is necessary to feedback the matching degree of the IoT solution requirements and the training objectives and the preset matching degree threshold to the target enterprise to inform the target enterprise that the design of the specific IoT solution is inconsistent with the training objectives of the IoT training control center for reference by the target enterprise.

[0066] When the matching degree between the IoT solution requirement and the training target is greater than a preset matching degree threshold, at least one training task is generated according to the IoT solution requirement. The number of training tasks generated according to the IoT solution requirement is determined according to actual conditions.

[0067] S4, sending the training task to the target Internet of Things training terminal through a sending module;

[0068] When determining the target IoT training terminal, first determine the task label information of the training task, then determine the training course label information of the candidate IoT training terminal; analyze the correlation between the task label information and the training course label information through the semantic model to determine the IoT training terminal with the highest correlation with the training task; determine the IoT training terminal with the highest correlation with the training task as the target IoT training terminal. Different IoT training terminals generally offer different training courses, and the training courses offered by the IoT training terminal are adapted to the IoT module installed in the IoT training terminal.

[0069] Furthermore, the IoT solution requirements of the target enterprise often have a certain deadline, and exceeding the deadline will seriously affect the production and operation activities of the target enterprise. Before sending the training task to the target IoT training terminal, the solution deadline can be determined according to the IoT solution requirements, and the task deadline of the training task can be determined according to the solution deadline; when executing the step of sending the training task to the target IoT training terminal, the task deadline and the corresponding training task are sent to the target IoT training terminal together.

[0070] S5. Obtain the first solution information generated by the target Internet of Things training terminal according to the training task through a sending module, and send the first solution information to the target enterprise, where the first solution information includes first perception layer information, first network transmission layer information and first application layer information.

[0071] Among them, after obtaining the training tasks issued by the IoT training work system, the target IoT training terminal relies on teacher and student resources and corresponding hardware resources to carry out the tasks, and finally generates the first solution information, and sends the first solution information to the IoT training work system. The IoT training work system further sends the first solution information to the target enterprise for the target enterprise to accelerate the design process.

[0072] It should be noted that the first solution information provided by the target IoT training terminal to the target enterprise may not be the final solution version, but may contain some flaws. At this time, the IoT training work system can obtain the target enterprise's feedback on the first solution information, send the feedback information to the target IoT training terminal, and the target IoT training terminal will further optimize the first solution information based on the feedback information, generate the second solution information, and send the second solution information to the IoT training work system. The feedback information includes but is not limited to security vulnerability information, functional vulnerability information and reliability information.

[0073] The second solution information includes the second perception layer information, the second network transmission layer information and the second application layer information. The Internet of Things training work system further obtains the second solution information generated by the target Internet of Things training terminal according to the feedback information, and sends the second solution information to the target enterprise.

[0074] Furthermore, the IoT training work system can also monitor the completion of training tasks, identify and promptly handle abnormal training tasks. When identifying and handling abnormal training tasks, first determine the abnormal training tasks that exceed the task deadline and the abnormal IoT training terminal corresponding to the abnormal training task. The abnormal IoT training terminal will send explanation information to the IoT training work system for the abnormal training task, which is used to explain the reason why the abnormal training task exceeds the task deadline; the explanation information includes the first type of explanation information and the second type of explanation information. The first type of explanation information is used to indicate that the reason why the abnormal training task exceeds the task deadline is a technical problem that can be overcome, and the second type of explanation information is used to indicate that the reason why the abnormal training task exceeds the task deadline is an insurmountable technical problem.

[0075] The Internet of Things training work system further obtains the description information of the abnormal Internet of Things training terminal on the abnormal training task; if the description information is judged to be the first type of description information, the Internet of Things training work system extends the task deadline according to the plan deadline; if the description information is judged to be the second type of description information, the Internet of Things training work system will re-issue the abnormal training task to other Internet of Things training terminals, and other Internet of Things training terminals will resume the processing process of the abnormal training task.

[0076] Furthermore, if the description information is the second type of description information, the target enterprise needs to provide the abnormal IoT training terminal with a target training course, and assist the abnormal IoT training terminal in carrying out targeted training courses through the target training course. Furthermore, if the description information is the second type of description information, the IoT training work system further sends course generation information to the target enterprise, obtains the target training course produced by the target enterprise according to the course generation information, and finally sends the target training course to the abnormal IoT training terminal.

[0077] Furthermore, the abnormal IoT training terminal can also evaluate the target training course. Specifically, the IoT training work system obtains the evaluation information of the abnormal IoT training terminal on the target training course and sends the evaluation information to the target enterprise.

[0078] Furthermore, the IoT training work system can obtain the target enterprise's update information on the target training course based on the evaluation information, and send the update information to the abnormal IoT training terminal, so that the abnormal IoT training terminal can obtain high-quality teaching resources in the process of executing the enterprise's actual production tasks.

[0079] In this embodiment, the IoT solution requirements sent by the target enterprise are first obtained, and then the matching degree between the IoT solution requirements and the training objectives is determined; if the matching degree is determined to be greater than the preset matching degree threshold, at least one training task is generated according to the IoT solution requirements, and the training task is sent to the target IoT training terminal, and the target IoT training terminal can perform the training task to meet the needs of the target enterprise; then, the first solution information generated by the target IoT training terminal according to the training task is obtained, and the first solution information is sent to the target enterprise, so as to cooperate with the research and development process of the target enterprise. Through the IoT training work system, the actual needs of the target enterprise can be organically integrated with the educational resources of the target IoT training terminal, the research and development process of the target enterprise can be improved, and at the same time, it is beneficial for the target IoT training terminal to carry out education and teaching.

[0080] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A practical training method for the Internet of Things, characterized in that: include: Obtaining IoT solution requirements sent by the target enterprise, wherein the IoT solution requirements include business functions in a specific scenario; Determine the matching degree between the IoT solution requirements and the training objectives, wherein the training objectives include a plurality of IoT key technologies that need to be mastered through training; If the matching degree is greater than the preset matching degree threshold, at least one training task is generated according to the IoT solution requirements, and the training task includes functional requirements, safety requirements and reliability requirements; otherwise, the matching degree between the IoT solution requirements and the training objectives and the preset matching degree threshold are fed back to the target enterprise to inform the target enterprise that the design of the specific IoT solution is inconsistent with the training objectives of the IoT training control center, for reference by the target enterprise; Sending the training task to the target IoT training terminal; The first solution information generated by the target Internet of Things training terminal according to the training task is obtained, and the first solution information is sent to the target enterprise, wherein the first solution information includes first perception layer information, first network transmission layer information and first application layer information.

2. The Internet of Things training method according to claim 1, characterized in that: Also includes: Obtaining feedback information from the target enterprise on the first solution information, and sending the feedback information to the target Internet of Things training terminal, wherein the feedback information includes security vulnerability information, functional vulnerability information, and reliability information; The second solution information generated by the target Internet of Things training terminal according to the feedback information is obtained, and the second solution information is sent to the target enterprise, where the second solution information includes second perception layer information, second network transmission layer information and second application layer information.

3. The Internet of Things training method according to claim 1, characterized in that: The target Internet of Things training terminal is determined by the following method: Determine task label information of the practical training task; Determine the training course label information of the candidate IoT training terminal; Analyze the correlation between the task label information and the training course label information through a semantic model to determine the IoT training terminal with the highest correlation with the training task, where different IoT training terminals are configured with different training sensors; The Internet of Things training terminal that is most relevant to the training task is determined as the target Internet of Things training terminal.

4. The Internet of Things training method according to claim 1, characterized in that: Before sending the training task to the target IoT training terminal, the method further includes: Determine a deadline for the solution according to the IoT solution requirements, and determine a deadline for the training task according to the deadline for the solution; Sending the training task to the target IoT training terminal also includes: The task deadline and the training task are sent together to the target Internet of Things training terminal.

5. The Internet of Things training method according to claim 4 is characterized in that: Also includes: Determine the abnormal training tasks that exceed the task deadline and the abnormal Internet of Things training terminals corresponding to the abnormal training tasks; Obtaining description information of the abnormal Internet of Things training terminal on the abnormal training task; If the description information is the first type of description information, extending the task deadline according to the solution deadline; If the description information is the second type of description information, the abnormal training task is resent to other Internet of Things training terminals.

6. The Internet of Things training method according to claim 5, characterized in that: Also includes: If the description information is the second type of description information, the course generation information is sent to the target enterprise, the target training course prepared by the target enterprise according to the course generation information is obtained, and the target training course is sent to the abnormal Internet of Things training terminal.

7. The Internet of Things training method according to claim 6, characterized in that: Also includes: Obtaining evaluation information of the abnormal Internet of Things training terminal on the target training course; The evaluation information is sent to the target enterprise.

8. The Internet of Things training method according to claim 7, characterized in that: Also includes: Obtaining update information of the target enterprise on the target training course according to the evaluation information; The update information is sent to the abnormal Internet of Things training terminal.

9. The Internet of Things training method according to claim 1, characterized in that: Determining the matching degree between the IoT solution requirements and the training objectives includes: Determine the requirement tag information of the IoT solution requirement; Determine the target label information of the training target; Analyzing the matching degree between the demand label information and the target label information through a semantic model, and determining the matching degree between the demand label information and the target label information as the matching degree between the IoT solution requirement and the training objective; When training the semantic model, the following loss function F is used to measure the difference between the predicted result of the semantic model and the true label, where a represents the main sentence, p represents the positive sentence, n represents the negative sentence, S represents the sentence embedding vector of a, p, and n, ||·|| represents the distance, and d represents S p With S n The distance between F=max(||S a -S p ||-||S a -S n ||+d,0)。 10. An Internet of Things training system, used to implement the Internet of Things training method according to any one of claims 1 to 9, characterized in that: include: An acquisition module, used to acquire the IoT solution requirements sent by the target enterprise, wherein the IoT solution requirements include business functions under specific scenarios; A determination module, used to determine the matching degree between the IoT solution requirements and the training objectives, wherein the training objectives include a plurality of IoT key technologies that need to be mastered through training; A generation module, configured to generate at least one training task according to the IoT solution requirements if the matching degree is greater than a preset matching degree threshold, wherein the training task includes at least functional requirements, safety requirements, and reliability requirements; A sending module, used for sending the training task to a target IoT training terminal; The sending module is used to obtain the first solution information generated by the target Internet of Things training terminal according to the training task, and send the first solution information to the target enterprise, wherein the first solution information includes first perception layer information, first network transmission layer information and first application layer information.

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