CN114612276A - Intelligent environmental sanitation synergy algorithm model management platform - Google Patents
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Abstract
The invention discloses a model management platform of an intelligent environmental sanitation synergy algorithm, which comprises a synergy model construction module, a model release module, a model management module, a model deployment module, a model application module, a result evaluation module, a model offline module and an API (application program interface) management module. The intelligent environmental sanitation synergy algorithm model management platform is applied by combining multiple modules, and achieves integration and visual management based on the synergy algorithm model management platform in the intelligent environmental sanitation industry, from data acquisition and processing to model training, model publishing, model management, model deployment, model execution, synergy evaluation and comparative analysis to model offline/deletion, so that full life cycle management is achieved, deployment and upgrading are facilitated, synergy result analysis is performed by scientific and effective means, the synergy result is displayed in a visual chart form, a user can visually see the synergy condition, the models are fused, a single model is converted into a system synergy model, and data safety is guaranteed by adopting a data isolation technology.
Description
Technical Field
The invention relates to the technical field of industrial big data systems (industrial data cleaning, management, analysis, visualization and the like) and industrial data modeling and analysis (mechanism modeling, machine learning and visualization) of an industrial PaaS layer, in particular to a smart environmental sanitation synergy algorithm model management platform.
Background
The sanitation industry needs to support an intelligent algorithm model, but the algorithm model and the management thereof in the sanitation industry at present have the following problems:
firstly, the fragmentation distribution of the model is difficult to manage: the models are scattered and distributed on each sub-platform (cloud) and micro-platform (cloud/edge) in the sanitation industry, and cannot be unified and effectively managed;
secondly, it is difficult to achieve full life cycle management of the model: at present, other industries including the sanitation industry have a plurality of machine learning platforms for algorithm model construction to reduce the difficulty of modeling, and some model management systems for model management, but because algorithm engineers and platform development engineers use different development languages, tools (software environments) and the like, the sanitation industry does not have platforms capable of managing the full life cycle of the algorithm model indirectly;
thirdly, model deployment and upgrading are not convenient enough: because the algorithm engineer and the platform development engineer use different development languages, tools (software environments) and the like, the deployment and the upgrade of the model are mostly operated by the algorithm engineer or operation and maintenance personnel logging in a server to perform deployment and upgrade, which is time-consuming and labor-consuming;
fourthly, no effective means is available for tracking and evaluating the synergy result of the model application: enterprise users pay attention to results of model application, particularly synergistic results, and currently, no platform can scientifically and effectively evaluate the synergistic results;
and fifthly, a model fusion tool is lacked: currently, a tool for model fusion reprocessing to convert a single model into a system synergy model is lacked.
Disclosure of Invention
The invention aims to provide an intelligent environmental sanitation synergy algorithm model management platform aiming at the defects of the prior art so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a wisdom sanitation increase algorithm model management platform, includes increase model construction module, model release module, model management module, model deployment module, model application module, result evaluation module, model offline module and API management module, its characterized in that:
the model building module is used for data management such as internet of things data acquisition, data cleaning, data expansion, data annotation and the like in the intelligent environmental sanitation, and provides a visual interface for model training to realize high-precision synergistic algorithm model building;
the model publishing module publishes the model trained by the synergy model building module or the model trained by an algorithm engineer in a fixed version, is used for receiving the model file, determines the parameter data of the model file, processes the parameter data and the model file into a mirror image package and uploads the mirror image package to a model pool (a machine learning algorithm library of cloud intelligent sanitation);
the model management module is used for managing published model information and version of the model publishing module and managing model files and mirror image packages;
the model deployment module provides two deployment and upgrading modes of a cloud end and an edge end, and is used for issuing a mirror image package (an initial version or an upgraded version) issued by the model issuing module to a cloud end server or an edge end server node, generating an algorithm model and executing the algorithm model, wherein the mirror image package is in a docker container mirror image form and is generated by the model issuing module;
the model application module is used for opening model application permission for the client, realizing configuration and application of a visual interface operation model, meeting the client model service calling requirement, enabling a service scene of intelligent sanitation, and intelligently managing and controlling equipment according to model execution result parameters so as to achieve the aims of cost reduction and efficiency improvement;
the result evaluation module is used for evaluating the synergy result after the model is used, and can also compare and analyze the synergy results after different models are used in the same service scene and display the results in a visual chart form;
the model offline module is used for performing offline or deletion processing on the archived algorithm model deployed on the cloud or edge server node;
the API management module is used for API maintenance and API call management, including API specification management, API state monitoring, call log management and metering charging.
As a preferred technical scheme of the invention, the data acquisition of the Internet of things refers to uploading data to a platform by equipment such as a vehicle-mounted terminal, a sensor, a PLC, a camera and an RFID, and the data is preprocessed and then used for model training, wherein the data preprocessing comprises preprocessing of characteristic information (field identification, name and type) of an algorithm model and preprocessing of training data/test data, and the preprocessing is used after cleaning, expansion and labeling.
As a preferred technical scheme of the invention, the model training can select an algorithm, configure preprocessed training data/test data, configure/optimize parameters and start training on a platform, the training can be selected to be finished or retrained according to a model evaluation result after the training is finished, the model training can support visual checking of a model evaluation report, the model effect can be tested by uploading data on line through a model checking function, the intelligent environmental sanitation synergy algorithm model training can provide an interface operation selection algorithm, configure training data and other related parameters to finish the training task starting, the model training can support visual checking of the model evaluation report, and the model testing effect can be uploaded on line through the model checking function.
As a preferred technical scheme of the invention, the model files can be developed by Python, Java and C + + languages, and the intelligent environmental sanitation synergy algorithm model management platform processes the files into a docker container mirror image package form for deployment and application of a following module.
As a preferred technical solution of the present invention, the model management module is further used for metadata management, service information management, and version management of the released model of the model release module, and metadata management of the management model of the model file and the mirror package.
As a preferred technical scheme of the invention, the metadata management of the model is used for maintaining the metadata of the model including model attribution, version attribute, release time and incidence relation, managing business information and managing model attribute information such as name, type, application, developer, user and release time.
As a preferred embodiment of the present invention, the version management is used for managing model version information such as version number, version description, implementation target, development language, entry parameter (model input information including data type, data amount, and quantity format), exit parameter (model output information including data type, data format, and data precision), API address, and version upgrade and rollback (release and deletion of a new version of an associated model release module).
As a preferred technical scheme of the invention, the management of the model file and the image package is used for modifying or re-uploading the model file and regenerating or downloading the image package.
The preferable technical scheme of the invention also comprises the following steps:
s1, the data collection of the Internet of things refers to uploading data to a platform by devices such as a vehicle-mounted terminal, a sensor, a PLC, a camera and an RFID, and the data is used for model training after being preprocessed, wherein the data preprocessing comprises preprocessing of characteristic information (field identification, name and type) of an algorithm model and preprocessing of training data/test data, the preprocessing comprises cleaning, expanding and labeling, the model training can select an algorithm, configure the preprocessed training data/test data, configure/optimize parameters and start training on the platform, the training can be finished or retrained according to a model evaluation result, after the model training is finished, a visual mode evaluation report is supported to be checked, data can be uploaded on line through a model checking function to test the model effect, and the model training of the environmental sanitation synergy algorithm is realized, providing an interface operation selection algorithm, configuring training data and other related parameters to complete the starting of a training task, supporting the visual viewing of a model evaluation report after the model training is finished, and uploading data to test the model effect on line through a model checking function;
s2, a result evaluation module for evaluating the synergy result after the model is used, or comparing and analyzing the synergy result after different models are used in the same service scene, and displaying the result in a visual chart, wherein the evaluation is performed after the model is used, the application of the anaerobic unit synergy algorithm model V1.0 for kitchen waste treatment is taken as an example for explanation, the average electricity consumption cost is reduced by 104.28 yuan after the model is used every day, the synergy income brought by the increase of biogas output is 704.47 yuan, the average daily comprehensive synergy is 808.75 yuan, the comparison and analysis are performed on the synergy result after different models are used in the same service scene, and the V1.0 version (assumed to be the algorithm model developed by the model developer A) of the anaerobic unit synergy algorithm model for kitchen waste treatment and the V2.0 version (possibly the model developer A or B or A) of the anaerobic unit synergy algorithm model, B, a jointly developed algorithm model) is taken as an example for illustration, and the synergistic results of the two versions can be visually seen, and the comparative analysis effect of the synergistic results of each time period can be visually seen;
s3, API management module connected with the model application module for API maintenance and API call management, including API standard management, API state monitoring, call log management and metering charge, convenient management and operation and maintenance, technical architecture design diagram of intelligent environmental sanitation synergy algorithm model management platform, in the infrastructure layer, mainly adopting the scheme of combining relational database and non-relational database to increase data file, data warehouse and database storage, the public technology layer mainly includes message middleware, search service, mail and short message service and distributed components, the platform service layer adopts Aries Spring Cud micro-service architecture design, the gateway layer adopts Spring Cloud gateway components to integrate Spring Security authentication authorization design, the display layer mainly provides operation and maintenance visualization and visualization operation function of client, the information Security system adopts different Security mechanism guarantee systems in each layer, In addition, the deployment operation of the intelligent environmental sanitation synergy algorithm model management platform adopts a jenkins + git automatic deployment mode for format release in a development and test stage, and is used for testing environment, and K8s is adopted for deploying and managing containerized platform application and service clusters in formal online and operation and maintenance.
Compared with the prior art, the invention provides an intelligent environmental sanitation synergy algorithm model management platform, which has the following beneficial effects:
1, integrated and visual management: the current intelligent environmental sanitation industry algorithm model is distributed on various environmental sanitation sub-platforms and micro-platforms at cloud and edge ends in a fragmentization mode, unified and effective management is difficult to perform, and an integrated and visual management is really achieved on the basis of the intelligent environmental sanitation industry synergistic algorithm model management platform.
2, full life cycle management: a synergistic algorithm model management platform based on the intelligent environmental sanitation industry achieves full life cycle management from data acquisition and processing to model training, model publishing, model management, model deployment, model execution, synergistic evaluation and comparative analysis to model offline/deletion.
3, convenience in deployment and upgrade: the synergistic algorithm model management platform based on the intelligent environmental sanitation industry provides two deployment and upgrading modes of a cloud end and an edge end, and is used for issuing a mirror image package (an initial version or an upgrading version) issued by a model issuing module to a cloud end server or an edge end server node, generating an algorithm model and executing the algorithm model.
4, carrying out synergistic result analysis by scientific and effective means: the efficiency enhancement algorithm model management platform based on the intelligent environmental sanitation industry provides efficiency enhancement result evaluation analysis after the model is used, can also compare and analyze the efficiency enhancement results after different models are used in the same service scene, and displays the results in a visual chart mode, so that a user can visually see the efficiency enhancement condition.
5, fusion of models: a synergistic algorithm model management platform based on the intelligent environmental sanitation industry provides a visual interface for operation, and a plurality of models are selected for fusion and reprocessing, so that a single model can be converted into a system synergistic model.
6, multi-tenant support: the synergistic algorithm model management platform based on the intelligent environmental sanitation industry supports the multi-tenant capability, can realize the construction, management, application, operation and maintenance, monitoring and the like of different model developers, model users and platform operators through the platform, and ensures the data safety by adopting a data isolation technology.
Drawings
FIG. 1 is a schematic diagram of an exemplary system architecture according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a model construction flowchart according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a model publishing flowchart according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a model deployment flowchart according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a flow chart of model application according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram illustrating exemplary synergy assessment results of the result assessment according to the embodiment of the invention;
FIG. 7 is a schematic structural diagram of an exemplary graph of comparative analysis results of result evaluation according to an embodiment of the present invention;
FIG. 8 is a schematic view of a flowchart of model downline according to an embodiment of the present invention;
FIG. 9 is a schematic structural diagram of a technical architecture design diagram according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
as shown in fig. 2, the data acquisition of the internet of things refers to that equipment such as a vehicle-mounted terminal, a sensor, a PLC, a camera, an RFID, etc. uploads data to a platform, and the data is preprocessed and then used for model training, where the data preprocessing includes preprocessing of characteristic information (field identification, name and type) of an algorithm model and preprocessing of training data/test data, and the preprocessing is used after cleaning, expansion and labeling, where model training can select an algorithm, configure preprocessed training data/test data, configure/optimize parameters, start training on the platform, and after the training is completed, the training can be selected to be completed or retrained again according to a model evaluation result, and after the model training is completed, the model training supports visual viewing of a model evaluation report, and can also upload data online through a model checking function to test model effect, and wisdom environmental sanitation synergy algorithm model training, and providing an interface operation selection algorithm, configuring training data and other related parameters to complete the starting of a training task, supporting visual checking of a model evaluation report after the model training is finished, and uploading data to test the model effect on line through a model verification function.
Example two: as shown in fig. 3, a model trained online by a synergistic model building module or a model trained offline by an algorithm engineer is published in a fixed format, and is used for receiving model files, processing the model files into a mirror image package, and uploading the mirror image package to a model pool (a cloud intelligent sanitation machine learning algorithm library), wherein the model files can be developed by Python, Java and C + +, and the intelligent sanitation synergistic algorithm model management platform processes the files into a docker container mirror image package form for deployment and application of a following module.
Example three:
as shown in fig. 4 and 5, two deployment and upgrade modes of a cloud end and an edge end are provided, and are used for issuing a mirror image package (an initial version or an upgraded version) issued by a model issuing module to a cloud end server or an edge end server node, generating an algorithm model and executing the algorithm model, wherein the mirror image package is in a docker container mirror image form and is generated by the model issuing module, and the model application module is used for opening model application permission for a client end, realizing configuration and application of a visual interface operation model, meeting the client end model service calling requirement, enabling a service scene of a smart sanitation, and intelligently controlling and controlling equipment according to a model execution result parameter, so that the goals of cost reduction and efficiency improvement are achieved.
Example four:
as shown in fig. 7 and 8, the evaluation of the synergy result after the model is used, here, taking the application of the anaerobic unit synergy algorithm model V1.0 for kitchen waste treatment as an example, the average electricity consumption cost is reduced by 104.28 yuan each day after the model is used, the synergy benefit brought by the increase of the biogas output is 704.47 yuan each day, and the average comprehensive synergy each day is 808.75 yuan, as an example, as shown in fig. 6, the synergy result after the model is used in the same business scenario is compared and analyzed, here, taking the application of the V1.0 version of the anaerobic unit synergy algorithm model for kitchen waste treatment (assumed as the algorithm model developed by the model developer a) and the V2.0 version of the anaerobic unit synergy algorithm model (possibly as the algorithm model developed by the model developer a or B or A, B in combination) as an example, here, the synergy results of the two versions can be visually seen, and the comparative analysis effect of the synergy result in each time period, and the model offline module is used for offline or deleting the archived algorithm model deployed at the cloud or edge server node.
Example four:
as shown in fig. 9, in the infrastructure layer, a scheme of combining the relational database and the non-relational database to increase data files, data bins and database storage is mainly adopted, the common technology layer mainly includes message middleware, search service, mail and short message service and distributed components, the platform service layer adopts the design of a Spring Cloud micro-service architecture of the airy system, the gateway layer adopts the design of Spring Cloud gateway components integrating Spring Security authentication authorization, the display layer mainly provides operation and maintenance visualization and a visualization operation function of a client, the information Security guarantee system adopts different Security mechanism guarantee systems, data, service and network Security in each layer, the informatization standard system performs unified standard management on technical specifications, data formats, database standards and API specifications to ensure data quality and model training effect, in addition, the deployment operation of the intelligent environmental protection algorithm model management platform, in the development and test stage, adopting a jenkins + git automatic deployment mode to carry out fixed-version release for testing environment; and when formally online and operation and maintenance are carried out, k8s is adopted to deploy and manage the containerized platform application and service cluster
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a wisdom sanitation increase algorithm model management platform, includes increase model construction module, model release module, model management module, model deployment module, model application module, result evaluation module, model offline module and API management module, its characterized in that:
the model building module is used for data management such as internet of things data acquisition, data cleaning, data expansion, data annotation and the like in the intelligent environmental sanitation, and provides a visual interface for model training to realize high-precision synergistic algorithm model building;
the model publishing module publishes the model trained by the synergy model constructing module or the model trained by an algorithm engineer in a fixed version, is used for receiving the model file, determines the parameter data of the model file, processes the parameter data and the model file into a mirror image package and uploads the mirror image package to the model pool;
the model management module is used for managing published model information and version of the model publishing module and managing model files and mirror image packages;
the model deployment module provides two deployment and upgrading modes of a cloud end and an edge end, and is used for issuing the mirror image packet issued by the model issuing module to a cloud end server or an edge end server node, generating an algorithm model and executing the algorithm model;
the model application module is used for opening model application permission for the client, realizing configuration and application of a visual interface operation model, meeting the service calling requirement of the client model and enabling a service scene of the intelligent sanitation;
the result evaluation module is used for evaluating the synergy result after the model is used, and can also compare and analyze the synergy results after different models are used in the same service scene and display the results in a visual chart form;
the model offline module is used for performing offline or deletion processing on the archived algorithm model deployed on the cloud or edge server node;
the API management module is used for API maintenance and API call management, including API specification management, API state monitoring, call log management and metering charging.
2. The intelligent environmental sanitation enhancement algorithm model management platform of claim 1, wherein: the data acquisition of the internet of things refers to that equipment such as a vehicle-mounted terminal, a sensor, a PLC, a camera and an RFID uploads data to a platform, and the data are preprocessed and then used for model training.
3. The intelligent environmental sanitation enhancement algorithm model management platform of claim 2, wherein: the model training can be performed by selecting an algorithm, configuring preprocessed training data/test data, configuring/optimizing parameters and starting training on a platform, and finishing or retraining can be selected according to a model evaluation result after the training is finished.
4. The intelligent environmental sanitation enhancement algorithm model management platform of claim 1, wherein: the model files can be developed by Python, Java and C + + languages, and the intelligent environmental sanitation synergy algorithm model management platform processes the files into a docker container mirror image package form for deployment and application of a rear module.
5. The intelligent environmental sanitation enhancement algorithm model management platform of claim 1, wherein: the model management module is also used for managing metadata, service information and version of the released model of the model release module and managing the metadata of the management model of the model file and the mirror image package.
6. The intelligent environmental sanitation enhancement algorithm model management platform of claim 5, wherein: the metadata management of the model is used for maintaining the metadata of the model including model attribution, version attribute, release time and incidence relation and managing business information, and is used for managing model attribute information such as name, type, application, developer, user and release time.
7. The intelligent environmental sanitation enhancement algorithm model management platform of claim 5, wherein: the version management is used for managing model version information such as version numbers, version description, implementation targets, development languages, entry and exit, API addresses and upgrading and returning versions.
8. The intelligent environmental sanitation enhancement algorithm model management platform of claim 1, wherein: and the management of the model file and the image package is used for modifying or re-uploading the model file and regenerating or downloading the image package.
9. The intelligent environmental sanitation enhancement algorithm model management platform of claim 1, further comprising the following processes:
s1, the data acquisition of the internet of things refers to that the vehicle-mounted terminal, the sensor, the PLC, the camera and the RFID and other devices upload data to a platform, the data is preprocessed and then used for model training, the data preprocessing comprises preprocessing of characteristic information (field identification, name and type) of an algorithm model and preprocessing of training data/test data, the preprocessing is used after cleaning, expansion and marking, the model training can select an algorithm, configure the preprocessed training data/test data, configure/optimize parameters and start training on the platform, the training can be finished or retrained according to model evaluation results, after the model training is finished, visual checking of model evaluation reports is supported, wisdom can upload data on line through a model checking function to test model effects, and environmental sanitation synergy algorithm model training is supported, providing an interface operation selection algorithm, configuring training data and other related parameters to complete the starting of a training task, supporting the visual viewing of a model evaluation report after the model training is finished, and uploading data to test the model effect on line through a model checking function;
s2, a result evaluation module for evaluating the synergy result after the model is used, or comparing and analyzing the synergy result after different models are used in the same service scene, and displaying the result in a visual chart, wherein the evaluation is performed after the model is used, the application of the anaerobic unit synergy algorithm model V1.0 for kitchen waste treatment is taken as an example for explanation, the average electricity consumption cost is reduced by 104.28 yuan after the model is used every day, the synergy income brought by the increase of biogas output is 704.47 yuan, the average daily comprehensive synergy is 808.75 yuan, the comparison and analysis are performed on the synergy result after different models are used in the same service scene, and the V1.0 version (assumed to be the algorithm model developed by the model developer A) of the anaerobic unit synergy algorithm model for kitchen waste treatment and the V2.0 version (possibly the model developer A or B or A) of the anaerobic unit synergy algorithm model, B, a jointly developed algorithm model) is taken as an example for illustration, and the synergistic results of the two versions can be visually seen, and the comparative analysis effect of the synergistic results of each time period can be visually seen;
s3, API management module connected with the model application module for API maintenance and API call management, including API standard management, API state monitoring, call log management and metering charge, convenient management and operation and maintenance, technical architecture design diagram of intelligent environmental sanitation synergy algorithm model management platform, in the infrastructure layer, mainly adopting the scheme of combining relational database and non-relational database to increase data file, data warehouse and database storage, the public technology layer mainly includes message middleware, search service, mail and short message service and distributed components, the platform service layer adopts Aries Spring Cloud micro-service architecture design, the gateway layer adopts Spring Cloud gateway components to integrate Spring Security authentication authorization design, the display layer mainly provides operation and maintenance visualization and visualization operation function of client, the information Security system adopts different Security mechanism guarantee systems in each layer, In addition, the deployment operation of the intelligent environmental sanitation synergy algorithm model management platform adopts a jenkins + git automatic deployment mode for format release in a development and test stage, and is used for testing environment, and K8s is adopted for deploying and managing containerized platform application and service clusters in formal online and operation and maintenance.
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| CN117608865A (en) * | 2024-01-23 | 2024-02-27 | 江西科技学院 | Mathematical model service method and system of take-away meal delivery platform based on cloud computing |
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| CN117608865A (en) * | 2024-01-23 | 2024-02-27 | 江西科技学院 | Mathematical model service method and system of take-away meal delivery platform based on cloud computing |
| CN117608865B (en) * | 2024-01-23 | 2024-04-05 | 江西科技学院 | Mathematical model service method and system of take-away meal delivery platform based on cloud computing |
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