CN113849203A - Internet of things terminal upgrading system and method - Google Patents
Internet of things terminal upgrading system and method Download PDFInfo
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Abstract
The invention provides a method for upgrading strategies of terminals of the Internet of things, and relates to the technical field of the Internet of things, wherein a plurality of terminals of the Internet of things regularly acquire data and send the data to an Internet of things management platform in real time; the Internet of things management platform receives data sent by a plurality of Internet of things terminals, filters the data, classifies and arranges the data into formatted data by taking terminal IDs of the Internet of things as calculation targets, and stores the formatted data into a database of the model training platform; the model training platform calls formatted data in the database as a sample data set to execute a training task, and sends an upgrade model which completes training to the Internet of things management platform; and the IOT management platform issues the upgrade model to each IOT terminal for upgrading, and transmits the upgrade log to the IOT management platform. The method is based on a linear regression analysis algorithm, an upgrading model is trained, the upgrading model can be optimized and perfected through continuous self-learning, and meanwhile, the upgrading model interacts with a platform, and the independent upgrading strategy of each internet of things terminal is achieved.
Description
Technical Field
The disclosure relates to the technical field of internet of things, in particular to a system and a method for upgrading a terminal of the internet of things.
Background
With the development of the internet of things industry and the exponential increase of application software of the internet of things terminal, terminal services are continuously increased, software installation and upgrading become an urgent need, and a large batch of software upgrading needs to have high concurrency capability of the system. The existing technology is mainly based on an upgrading strategy of manually setting fixed time, occupies larger bandwidth in the upgrading process, causes certain influence on a system, and can cause service interruption of the operation of the terminal of the internet of things and fail to formulate personalized upgrading strategies aiming at different terminals.
Disclosure of Invention
The invention provides a method for upgrading a strategy of an Internet of things terminal aiming at the problems.
In order to solve at least one of the above technical problems, the present disclosure proposes the following technical solutions: the Internet of things terminal upgrading method comprises the following steps:
the method comprises the following steps that a plurality of internet of things terminals collect data regularly and send the data to an internet of things management platform in real time;
the Internet of things management platform receives data sent by a plurality of Internet of things terminals, filters the data, classifies and arranges the data into formatted data by taking terminal IDs of the Internet of things as calculation targets, and stores the formatted data into a database of the model training platform; the formatted data comprises a terminal ID, transmission time, a service data type, network delay time and a data packet size;
the model training platform calls formatted data in the database as a sample data set to execute a training task, and sends an upgrade model which completes training to the Internet of things management platform;
and the Internet of things management platform issues the upgrading model to each Internet of things terminal for processing, the Internet of things terminals use the upgrading model for upgrading, and the upgrading logs are transmitted to the Internet of things management platform.
In some embodiments, the method for filtering the data sent by the terminals of the internet of things by the internet of things management platform comprises the following steps of:
the method comprises the steps that an Internet of things management platform receives running log data of each Internet of things terminal;
the method comprises the steps that an Internet of things management platform collects self interactive log data and interactive network flow data with an Internet of things terminal;
performing matching association according to the running log data, the interactive network traffic data and the interactive log data so as to obtain a terminal ID required by a model training platform, and time, service type, network delay time and data packet size corresponding to the terminal ID;
and storing the acquired terminal ID, the transmission time corresponding to the terminal ID, the service data type, the network delay time and the data packet size into a database of a model training platform.
In some embodiments, the model training platform calls formatted data in the database as training data to perform a training task, comprising the steps of:
taking formatted data stored in a database as a sample data set, and dividing the data into independent variable data and dependent variable data, wherein the independent variable data comprises a terminal ID and a data packet size, a service data type and transmission time of each transmission corresponding to the terminal ID, and the dependent variable is network delay time;
selecting a plurality of data from the independent variable data and the dependent variable data as a training set, and using the rest data as a test set;
selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4Is independent variable, respectively terminal ID and data packet size, service data type and transmission time of each transmission corresponding to the terminal ID, and the independent variable and dependent variable are in linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error item, and generating an upgrading model;
and verifying the upgrade model by adopting the data of the test set, if the upgrade model is a valid model, archiving, and otherwise finishing training.
In some embodiments, the method for processing the upgrade model by the internet of things management platform includes the following steps:
each Internet of things terminal receives an upgrading model issued by the Internet of things management platform and updates a terminal upgrading module according to the upgrading model;
after the updating is finished, informing the Internet of things management platform to release a terminal upgrading task to the Internet of things terminal for terminal upgrading;
and after the terminal finishes upgrading, uploading the upgrading log to an internet of things management platform for processing.
In some embodiments, after the terminal finishes upgrading, the upgrade log is uploaded to an internet of things management platform for processing, and the method includes the following steps:
the method comprises the steps that an Internet of things management platform receives an upgrade log uploaded by an Internet of things terminal in real time;
filtering and analyzing the data fed back from the upgrade log;
deciding whether to start an upgrade model update task by analyzing the accuracy data and the performance data; if the training task needs to be updated, starting a new training task, and if the training task does not need to be updated, terminating the feedback;
the updating specific implementation method comprises the following steps:
collecting accuracy data and performance data of the model application;
pushing the collected data, filtering the integrity and effectiveness of the data, and then performing classification, aggregation and statistical analysis;
according to the analysis result, a part of data is used for generating a user use report, and a part of available data is used for generating sample data;
and directly feeding back a user report, verifying the sample data according to the requirements of a formal sample, expanding the sample data to a sample data set after the sample data passes the requirements of the formal sample, and finally feeding back the data.
The invention also provides an Internet of things terminal upgrading system, which comprises an Internet of things management platform, a model training platform and at least one Internet of things terminal, wherein the at least one Internet of things terminal can be any Internet of things equipment which can be accessed to a network,
the Internet of things management platform is used for receiving data sent by the Internet of things terminal, filtering the data, classifying and sorting the data into formatted data by taking the terminal ID of the Internet of things as a calculation target, and storing the formatted data into a database of the model training platform; meanwhile, an upgrading model is issued to at least one Internet of things terminal, and an upgrading log of the Internet of things terminal is received for processing;
the Internet of things terminal sends data to the Internet of things management platform at regular time, receives an upgrade model issued by the Internet of things management platform at the same time, and feeds an upgrade result back to the Internet of things management platform;
the model training platform is configured to perform specific execution training tasks, train the model according to the formatted data of the IOT management platform to form an optimized upgrade model and send the optimized upgrade model to the IOT management platform.
In some embodiments, the internet of things management platform comprises:
the data collection module is used for completing data collection of the terminal of the Internet of things;
the data processing module is used for cleaning, filtering, analyzing and summarizing the acquired data, generating formatted data, storing the formatted data serving as a sample data set into a database of the model training platform and completing data preparation work;
and the model issuing module is used for receiving the model output by the model training platform, rapidly issuing the model and distributing the model to each Internet of things terminal.
In some embodiments, the internet of things terminal includes:
the terminal processing module is used for communicating with the Internet of things management platform and carrying out upgrade control on the Internet of things terminal according to the received information sent by the Internet of things management platform; the method comprises the following steps of updating a terminal upgrading module according to a model of a model publishing module, receiving a feedback message of the terminal upgrading module and sending the feedback message to a task publishing module of an Internet of things management platform;
the task issuing module is used for issuing the terminal upgrading task to the terminal processing module after receiving the message that the terminal upgrading module completes updating, and then the terminal processing module executes the upgrading task.
In some embodiments, the model training platform comprises a platform processing module and a database in communication connection with the platform processing module, the processing module comprises a training unit, a verification unit and a database, the training unit is used for calling a part of sample data sets stored in the database to process the sample data sets to obtain a training data set, and an upgrade model is established according to the training data set;
and the verification unit is used for verifying the upgrade model by using data which is not acquired by the training module as a test data set, if the upgrade model is an effective model, archiving the upgrade model, and otherwise finishing the training.
In some embodiments, the specific method of building an upgrade model from the training data set comprises:
dividing a training data set into independent variable data and dependent variable data;
selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4As independent variables, respectively terminal ID and packet size, service data type and transmission time of each transmission corresponding to the terminal ID, and the independent variables and dependent variables are in linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error term, and generating an upgrade model.
The beneficial effects of this disclosure are: the method is based on a linear regression analysis algorithm, an upgrading model is trained, the upgrading model can be optimized and perfected through continuous self-learning, and meanwhile, the upgrading model interacts with a platform, and the independent upgrading strategy of each internet of things terminal is achieved.
In addition, in the technical solutions of the present disclosure, the technical solutions can be implemented by adopting conventional means in the art, unless otherwise specified.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic structural diagram of an internet of things terminal upgrading system according to the present application;
fig. 2 is a flowchart of the internet of things terminal upgrading method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below with reference to the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of some, but not all, embodiments of the disclosure and are not to be considered as limiting the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1:
as shown in fig. 1-2, the method for upgrading the internet of things terminal includes the following steps:
s100, a plurality of Internet of things terminals acquire data regularly and send the data to an Internet of things management platform in real time;
s200, the Internet of things management platform receives data sent by a plurality of Internet of things terminals, filters the data, classifies and arranges the data into formatted data by taking terminal IDs of the Internet of things as calculation targets, and stores the formatted data into a database of a model training platform; the formatted data comprises a terminal ID, transmission time, a service data type, network delay time and a data packet size; specifically, the method takes the terminal ID as a calculation target, and arranges the start time, the end time, the network delay time, the service type of the transmission data and the size of the single transmission data packet.
S300, the model training platform calls formatted data in a database as a sample data set to execute a training task, and sends an upgrade model which completes training to the Internet of things management platform;
s400, the Internet of things management platform issues the upgrading model to each Internet of things terminal for processing, the Internet of things terminals use the upgrading model for upgrading, and the upgrading logs are transmitted to the Internet of things management platform.
Specifically, in step s200, the internet of things management platform receives data sent by a plurality of terminals of the internet of things, filters the data, classifies and arranges the data into formatted data by using terminal IDs of the internet of things as calculation targets, and stores the formatted data in a database of the model training platform, and the method includes the following steps:
s201, receiving running log data of each Internet of things terminal by an Internet of things management platform;
s202, receiving interactive network flow data and interactive log data by the Internet of things management platform;
s203, performing matching association according to the running log data, the interactive network flow data and the interactive log data so as to obtain a terminal ID required by a model training platform, and time, service type, network delay time and data packet size corresponding to the terminal ID;
and S204, storing the acquired terminal ID, the transmission time corresponding to the terminal ID, the service data type, the network delay time and the data packet size into a database of a model training platform. Therefore, the generated formatted data are imported into a model training platform, model parameter packaging is carried out on the extracted formatted data, model training parameters are built based on a linear regression kernel building principle, and an upgrading model related to the time period and the flow of terminal ID upgrading is analyzed.
Specifically, in step S300, the model training platform calls formatted data in the database as training data to execute a training task, including the following steps:
s301, taking formatted data stored in a database as a sample data set, and dividing the data into independent variable data and dependent variable data, wherein the independent variable data comprises a terminal ID, and the size, the type and the transmission time of a data packet which is transmitted every time and corresponds to the terminal ID, and the dependent variable is network delay time;
s302, selecting a plurality of data from the independent variable data and the dependent variable data as training sets, and using the rest data as test sets;
s303, selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4Is independent variable, respectively terminal ID and data packet size, service data type and transmission time of each transmission corresponding to the terminal ID, and the independent variable and dependent variable are in linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
s304, training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error item, and generating an upgrading model;
s305, verifying the upgrade model by adopting the data of the test set, if the upgrade model is a valid model, archiving, and otherwise, finishing training.
Specifically, in step S200, the internet of things management platform issues an upgrade model to each internet of things terminal for processing, the internet of things terminal uses the upgrade model for upgrading, and transmits an upgrade log to the internet of things management platform, including the following steps:
s401, each Internet of things terminal receives an upgrading model issued by an Internet of things management platform and updates a terminal upgrading module according to the upgrading model;
s402, after the updating is completed, informing the Internet of things management platform to release a terminal upgrading task to the Internet of things terminal for terminal upgrading;
and S403, after the terminal is upgraded, uploading the upgrade log to an internet of things management platform for processing.
In this embodiment, after the terminal finishes upgrading, the upgrade log is uploaded to the internet of things management platform for processing, which includes the following steps:
the method comprises the steps that an Internet of things management platform receives an upgrade log uploaded by an Internet of things terminal in real time;
filtering and analyzing the upgrade log;
deciding whether to start an upgrade model update task by analyzing the accuracy data and the performance data; if the training task needs to be updated, starting a new training task, and if the training task does not need to be updated, terminating the feedback;
the updating specific implementation method comprises the following steps:
collecting accuracy data and performance data of the model application;
pushing the collected data, filtering the integrity and effectiveness of the data, and then performing classification, aggregation and statistical analysis;
according to the analysis result, a part of data is used for generating a user use report, and a part of available data is used for generating sample data;
and directly feeding back a user report, verifying the sample data according to the requirements of a formal sample, expanding the sample data to a sample data set after the sample data passes the requirements of the formal sample, and finally feeding back the data.
Example 2
As shown in fig. 2, the present invention further provides an internet of things terminal upgrading system, which includes an internet of things management platform, a model training platform, and at least one internet of things terminal, where the at least one internet of things terminal may be any internet of things device capable of accessing a network,
the Internet of things management platform is used for receiving data sent by the Internet of things terminal, filtering the data, classifying and sorting the data into formatted data by taking the terminal ID of the Internet of things as a calculation target, and storing the formatted data into a database of the model training platform; meanwhile, an upgrading model is issued to at least one Internet of things terminal, and an upgrading log of the Internet of things terminal is received for processing;
the Internet of things terminal sends data to the Internet of things management platform at regular time, receives an upgrade model issued by the Internet of things management platform at the same time, and feeds an upgrade result back to the Internet of things management platform;
the model training platform is configured to perform specific execution training tasks, train the model according to the formatted data of the IOT management platform to form an optimized upgrade model and send the optimized upgrade model to the IOT management platform.
The thing allies oneself with management platform includes:
the data collection module is used for completing data collection of the terminal of the Internet of things;
the data processing module is used for cleaning, filtering, analyzing and summarizing the acquired data, generating formatted data, storing the formatted data serving as a sample data set into a database of the model training platform and completing data preparation work;
and the model issuing module is used for receiving the model output by the model training platform, rapidly issuing the model and distributing the model to each Internet of things terminal.
In this embodiment, the internet of things terminal includes:
the terminal processing module is used for communicating with the Internet of things management platform and carrying out upgrade control on the Internet of things terminal according to the received information sent by the Internet of things management platform; the method comprises the following steps of updating a terminal upgrading module according to a model of a model publishing module, receiving a feedback message of the terminal upgrading module and sending the feedback message to a task publishing module of an Internet of things management platform;
the task issuing module is used for receiving a message whether the terminal upgrading module fed back by the terminal of the Internet of things completes updating or not, deciding whether the terminal upgrading task needs to be issued or not according to the received message, and informing the terminal processing module of the terminal of the Internet of things to execute the upgrading task if necessary.
Therefore, the upgrading model is issued to the Internet of things terminal through the Internet of things management platform, the task issuing module is configured in the Internet of things management platform, the upgrading task is issued to the Internet of things terminal, and the Internet of things terminal upgrades the terminal according to the upgrading task. In the process, the internet of things management platform collects network flow data and related log data information in the running process of the internet of things terminal in real time.
Preferably, the model training platform comprises a platform processing module and a database in communication connection with the platform processing module, the processing module comprises a training unit, a verification unit and a database, the training unit is used for calling part of sample data sets stored in the database to process the sample data sets to obtain training data sets, and an upgrade model is established according to the training data sets;
and the verification unit is used for verifying the upgrade model by using data which is not acquired by the training module as a test data set, if the upgrade model is an effective model, archiving the upgrade model, and otherwise finishing the training.
Specifically, the specific method for establishing the upgrade model according to the training data set includes:
dividing a training data set into independent variable data and dependent variable data;
selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4As independent variables, respectively terminal ID and packet size, service data type and transmission time of each transmission corresponding to the terminal ID, and the independent variables and dependent variables are in linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error term, and generating an upgrade model.
The method is based on a linear regression analysis algorithm, an upgrading model is trained, the upgrading model can be optimized and perfected through continuous self-learning, and meanwhile, the upgrading model interacts with a platform, and the independent upgrading strategy of each internet of things terminal is achieved.
It should be noted that: the sequence of the embodiments in this specification is merely for description, and does not represent the advantages or disadvantages of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the embodiments of the apparatus, the device and the storage medium, since they are substantially similar to the method embodiments, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiments.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent replacements, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The Internet of things terminal upgrading method is characterized by comprising the following steps:
the method comprises the following steps that a plurality of internet of things terminals collect data regularly and send the data to an internet of things management platform in real time;
the Internet of things management platform receives data sent by a plurality of Internet of things terminals, filters the data, classifies and arranges the data into formatted data by taking terminal IDs of the Internet of things as calculation targets, and stores the formatted data into a database of the model training platform;
the model training platform calls formatted data in the database as a sample data set to execute a training task, and sends an upgrade model which completes training to the Internet of things management platform;
and the Internet of things management platform issues the upgrading model to each Internet of things terminal for processing, the Internet of things terminals use the upgrading model for upgrading, and the upgrading logs are transmitted to the Internet of things management platform.
2. The method for upgrading the strategy of the terminal of the internet of things according to claim 1, wherein the internet of things management platform receives data sent by a plurality of terminals of the internet of things, filters the data, classifies the data into formatted data by taking a terminal ID of the internet of things as a calculation target, and stores the formatted data into a database of a model training platform, wherein the formatted data comprises the terminal ID, transmission time, service data type, network delay time and data packet size; and comprises the following steps:
the method comprises the steps that an Internet of things management platform receives running log data of each Internet of things terminal;
the method comprises the steps that an Internet of things management platform collects self interactive log data and interactive network flow data with an Internet of things terminal;
performing matching association according to the running log data, the interactive network traffic data and the interactive log data so as to obtain a terminal ID required by a model training platform, and time, service type, network delay time and data packet size corresponding to the terminal ID;
and storing the acquired terminal ID, the transmission time corresponding to the terminal ID, the service data type, the network delay time and the data packet size into a database of a model training platform.
3. The method for upgrading policy of a terminal of internet of things according to claim 2,
the model training platform calls formatted data in a database as training data to execute a training task, and the method comprises the following steps:
taking formatted data stored in a database as a sample data set, and dividing the data into independent variable data and dependent variable data, wherein the independent variable data comprises a terminal ID and a data packet size, a service data type and transmission time of each transmission corresponding to the terminal ID, and the dependent variable is network delay time;
selecting a plurality of data from the independent variable data and the dependent variable data as a training set, and using the rest data as a test set;
selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4Is fromVariables which are respectively the terminal ID and the size of the data packet transmitted each time corresponding to the terminal ID, the type of the service data and the transmission time, and the independent variable and the dependent variable are in a linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error item, and generating an upgrading model;
and verifying the upgrade model by adopting the data of the test set, if the upgrade model is a valid model, archiving, and otherwise finishing training.
4. The method for upgrading the strategy of the internet of things terminal according to claim 1, wherein the internet of things management platform issues the upgrading model to each internet of things terminal for processing, the internet of things terminal uses the upgrading model for upgrading, and an upgrading log is transmitted to the internet of things management platform, and the method comprises the following steps:
each Internet of things terminal receives an upgrading model issued by the Internet of things management platform and updates a terminal upgrading module according to the upgrading model;
after the updating is finished, informing the Internet of things management platform to release a terminal upgrading task to the Internet of things terminal for terminal upgrading;
and after the terminal finishes upgrading, uploading the upgrading log to an internet of things management platform for processing.
5. The method for upgrading the strategy of the internet of things terminal according to claim 1, wherein the upgrading log is uploaded to an internet of things management platform for processing after the terminal is upgraded, and the method comprises the following steps:
the method comprises the steps that an Internet of things management platform receives an upgrade log uploaded by an Internet of things terminal in real time;
filtering and analyzing the upgrade log;
deciding whether to start an upgrade model update task by analyzing the accuracy data and the performance data; if the training task needs to be updated, starting a new training task, and if the training task does not need to be updated, terminating the feedback;
the updating specific implementation method comprises the following steps:
collecting accuracy data and performance data of the model application;
pushing the collected data, filtering the integrity and effectiveness of the data, and then performing classification, aggregation and statistical analysis;
according to the analysis result, a part of data is used for generating a user use report, and a part of available data is used for generating sample data;
and directly feeding back a user report, expanding sample data to a sample data set, and finally feeding back the data.
6. An Internet of things terminal upgrading system is characterized by comprising an Internet of things management platform, a model training platform and at least one Internet of things terminal, wherein the at least one Internet of things terminal can be any Internet of things equipment which can be accessed to a network,
the Internet of things management platform is used for receiving data sent by the Internet of things terminal, filtering the data, classifying and sorting the data into formatted data by taking the terminal ID of the Internet of things as a calculation target, and storing the formatted data into a database of the model training platform; meanwhile, an upgrading model is issued to at least one Internet of things terminal, and an upgrading log of the Internet of things terminal is received for processing;
the Internet of things terminal sends data to the Internet of things management platform at regular time, receives an upgrade model issued by the Internet of things management platform at the same time, and feeds an upgrade result back to the Internet of things management platform;
the model training platform is configured to perform specific execution training tasks, train the model according to the formatted data of the IOT management platform to form an optimized upgrade model and send the optimized upgrade model to the IOT management platform.
7. The Internet of things terminal upgrading system according to claim 6,
the thing allies oneself with management platform includes:
the data collection module is used for completing data collection of the terminal of the Internet of things;
the data processing module is used for cleaning, filtering, analyzing and summarizing the acquired data, generating formatted data, storing the formatted data serving as a sample data set into a database of the model training platform and completing data preparation work;
and the model issuing module is used for receiving the model output by the model training platform, rapidly issuing the model and distributing the model to each Internet of things terminal.
8. The internet of things terminal upgrading system according to claim 7, wherein the internet of things terminal comprises:
the terminal processing module is used for communicating with the Internet of things management platform and carrying out upgrade control on the Internet of things terminal according to the received information sent by the Internet of things management platform; the method comprises the following steps of updating a terminal upgrading module according to a model of a model publishing module, receiving a feedback message of the terminal upgrading module and sending the feedback message to a task publishing module of an Internet of things management platform;
the task issuing module is used for issuing the terminal upgrading task to the terminal processing module after receiving the message that the terminal upgrading module completes updating, and then the terminal processing module executes the upgrading task.
9. The internet of things terminal upgrading system according to claim 6, wherein the model training platform comprises a platform processing module and a database in communication connection with the platform processing module, the processing module comprises a training unit, a verification unit and a database, the training unit is used for calling a part of sample data sets stored in the database to process the sample data sets to obtain training data sets, and an upgrading model is established according to the training data sets;
and the verification unit is used for verifying the upgrade model by using data which is not acquired by the training module as a test data set, if the upgrade model is an effective model, archiving the upgrade model, and otherwise finishing the training.
10. The internet of things terminal upgrading system according to claim 7, wherein the specific method for establishing an upgrading model according to the training data set comprises the following steps:
dividing a training data set into independent variable data and dependent variable data;
selecting a multiple linear regression analysis model, wherein the multiple linear regression analysis model is as follows:
Y＝b0+b1X1+b2X2+b3X3+b4X4+e
wherein, Y is set as a dependent variable network delay time, X1、X2、X3、X4As independent variables, respectively terminal ID and packet size, service data type and transmission time of each transmission corresponding to the terminal ID, and the independent variables and dependent variables are in linear relation, b0、b1、b2、b3、b4E is an error term for the parameter to be estimated;
training the multiple linear regression analysis model by using training set data to obtain a parameter b to be estimated0、b1、b2、b3、b4And the numerical value of the error term, and generating an upgrade model.
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