Microorganism culture big data processing and analyzing system

Abstract

The invention discloses a microbiological culture big data processing analysis system, and relates to the field of data processing analysis, and the system comprises a culture processing analysis platform which comprises a culture monitoring module, a data storage module, a monitoring processing module, a resource monitoring module, a processing distribution module and a processing analysis module; the culture monitoring module is used for inputting culture item information and collecting culture monitoring data; the data storage module is used for acquiring federated microorganism culture data and constructing a microorganism storage data lake; the monitoring processing module is used for acquiring a classification evaluation result corresponding to the cultivation monitoring data; the resource monitoring module is used for acquiring historical processing data and resource data of each data processing resource node; the processing distribution module is used for setting processing analysis path information corresponding to the cultivation monitoring data; the processing and analyzing module is used for analyzing and processing the culture monitoring data to obtain culture whole-cycle analysis data; according to the invention, the accuracy and efficiency of the data processing process are improved.

Description

Technical Field

[0001] This invention relates to the field of data processing and analysis technology, and in particular to a microbial culture big data processing and analysis system. Background Technology

[0002] With the continuous progress of biology, the valuable information mined from biological data is increasing. Microbial culture is one of the basic methods of biological data mining, and it has crucial applications in many fields, including medicine, industrial production, and agriculture. As microbial culture continues to develop in various fields, higher requirements are being placed on the efficiency, quality, and yield of microbial culture. Traditional microbial culture mainly relies on manual operation and experience judgment. With the continuous development of sensor technology, image acquisition technology, and automated equipment, the amount of data that can be collected during microbial culture is growing explosively, providing strong support for the processing and analysis of microbial culture processes through big data computing.

[0003] A search revealed Chinese patent CN118051859A, which discloses an automated system for analyzing microbial culture results. Specifically, this system includes modules for environmental data integration and analysis, real-time resource optimization and adjustment, microbial growth simulation, predictive process optimization and resource scheduling, data flow management and strategy optimization, emergency event handling and response, system fault recovery and continuation, and comprehensive analysis of experimental results. This invention, by integrating multi-source data and employing data fusion algorithms, enables real-time monitoring of key factors in the microbial culture environment. Linear programming and optimization algorithms are used for dynamic resource allocation and step adjustment. This improves the efficiency and flexibility of the processing flow, especially enabling timely response and adaptation under complex or changing environmental conditions. By combining artificial neural networks and dynamic modeling using differential equations, the system can more accurately simulate the growth and metabolic behavior of microorganisms under different environments.

[0004] Compared with existing technologies, the Chinese patent with patent number CN118051859A can improve the efficiency and flexibility of the processing flow by dynamically allocating corresponding resources and adjusting steps through real-time monitoring of key aspects of the microbial culture environment.

[0005] However, in actual use, the above system only improves the efficiency and flexibility of the processing flow by dynamically allocating resources and adjusting steps. However, the data analysis process corresponding to the dynamically allocated and adjusted processing resources is not adjusted synchronously, which reduces the accuracy of the data processing process to some extent. Summary of the Invention

[0006] The purpose of this invention is to address the problem of insufficient accuracy in existing technologies, and to propose a microbial culture big data processing and analysis system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A microbial culture big data processing and analysis system includes a culture processing and analysis platform, which includes a culture monitoring module, a data storage module, a monitoring and processing module, a resource monitoring module, a processing allocation module, and a processing analysis module. The culture monitoring module is used to input the corresponding culture project information and obtain the corresponding culture monitoring data during the culture process of the corresponding microorganisms based on the culture project information. The data storage module is used to collect federated microbial culture data, obtain corresponding microbial morphology data and microbial characteristic data based on the federated microbial culture data for storage and management, construct a microbial storage data lake, and set up project sharing space according to the culture project information. The monitoring and processing module is used to perform real-time data stream pre-evaluation processing on the obtained culture monitoring data based on the culture project information and the microbial storage data lake, and obtain the corresponding classification and evaluation results; The resource monitoring module is equipped with corresponding data processing resource nodes, and obtains the historical processing data and resource data corresponding to the corresponding data processing resource nodes. The processing and allocation module is used to allocate and process the cultivation monitoring data corresponding to the corresponding classification and evaluation results based on the historical processing data and resource data of the corresponding data processing resource nodes, and to obtain the corresponding processing and analysis path information. The processing and analysis module is used to analyze and process the obtained culture monitoring data according to the corresponding processing and analysis path information, and obtain the full-cycle analysis data of the corresponding culture project information.

[0008] The above technical solution further includes: the process of inputting culture project information and obtaining corresponding culture monitoring data based on the culture project information includes: Set up a project entry unit and a cultivation monitoring unit; The project entry unit is used to enter culture project information, which includes basic project information, microbial information, and culture process information. The culture monitoring unit is equipped with corresponding sensor devices, image acquisition devices, and experimental recording devices based on Internet of Things technology according to the corresponding culture equipment. It collects the corresponding culture monitoring data during the culture process of the corresponding microorganisms according to the corresponding culture project information. The culture monitoring data includes physicochemical parameter monitoring information, image monitoring data, and operation monitoring information.

[0009] Furthermore, the process of constructing a microbial storage data lake includes: Set up information collection units, information storage units, and project storage units; The information collection unit is equipped with a federated sharing database. The federated sharing database is equipped with corresponding federated sharing nodes according to the corresponding sharing institutions. The federated sharing nodes collect the federated microbial culture data that is allowed to be shared within the corresponding sharing institutions. The federated microbial culture information includes microbial morphology data and microbial characteristic data. The information storage unit sets up microbial type datasets for the obtained federated microbial culture data based on the types corresponding to microbial morphological data and microbial characteristic data; For each microbial type dataset, the corresponding microbial culture data are matched one-to-one with the corresponding culture project information to obtain the corresponding elements. The obtained corresponding elements are analyzed and processed based on the correlation coefficient analysis algorithm to obtain the corresponding correlation data. The correlation data between each corresponding element in the microbial type dataset is integrated and analyzed to obtain the importance data. The importance data corresponding to each microbial type dataset are comprehensively sorted, and data layers are set up in sequence according to the sorting results. Data classification nodes are set up in the data layers according to the corresponding types. The obtained federated microbial culture data is mapped to the corresponding data classification nodes in each data layer, and the corresponding storage link information is obtained to store the federated microbial culture data. The storage link information of each data layer is integrated to construct a microbial storage data lake.

[0010] Furthermore, the process of setting up a shared space for the training program based on the program information includes: The project storage unit is used to set up a shared space for projects based on project development information; Obtain the basic project information and training process information corresponding to the project training information, set the corresponding distributed storage nodes and node permission information based on the basic project information and training process information, and set the corresponding project shared space according to the distributed storage nodes and node permissions.

[0011] Furthermore, the process of obtaining the corresponding classification and evaluation results from the culture monitoring data includes: Set up data matching and data evaluation units; The data matching unit acquires the corresponding culture project information, culture monitoring data and microbial storage data lake, performs feature analysis on the currently acquired culture monitoring data based on the culture project information, acquires the corresponding monitoring type based on the feature analysis results, acquires the corresponding storage link information in the biological storage data lake based on the corresponding monitoring type, and generates monitoring matching link information. The data evaluation unit is used to perform real-time data stream pre-evaluation processing on the corresponding culture monitoring data based on the monitoring matching link information, and to classify and evaluate the federated microbial culture data in the monitoring matching link information based on big data algorithms to obtain the federated culture dataset. For the federated culture dataset, based on the data type corresponding to the culture monitoring data, a corresponding dynamic mean baseline and abnormal fluctuation baseline are set using a linear interpolation algorithm; Based on the corresponding dynamic mean baseline and abnormal fluctuation baseline, set the dynamic threshold intervals corresponding to the culture monitoring data. Compare and analyze the culture monitoring data with the dynamic threshold intervals of the corresponding data types. Perform integrated pre-evaluation processing according to the dynamic threshold intervals to obtain the classification evaluation results corresponding to the culture monitoring data.

[0012] Furthermore, the process of setting up data processing resource nodes and obtaining the historical processing data and resource data corresponding to the respective data processing resource nodes includes: The resource monitoring module includes a resource management unit and a resource monitoring unit. The resource management unit is used to set up corresponding data processing resource nodes in the corresponding data layer according to the microbial storage data lake. The data processing resource nodes are used to analyze and process the culture monitoring information obtained in the corresponding data layer. The resource monitoring unit is used to acquire the historical processing data and resource data corresponding to the corresponding cultivation monitoring data processed by each data processing resource node.

[0013] Furthermore, the process of obtaining the corresponding processing and analysis path information for the culture monitoring data includes: The processing and allocation module includes a resource processing unit and a resource allocation unit. The resource processing unit is used to acquire the historical processing data corresponding to each data processing resource node, analyze and process the historical processing data corresponding to each data processing resource node, acquire the classification evaluation results of the corresponding historical processing data in the corresponding data layer of the corresponding data processing resource node, perform statistical analysis on the classification evaluation results, and acquire the processing frequency data of the data processing resource node corresponding to the corresponding classification evaluation results. Based on the processing frequency data corresponding to the corresponding classification and evaluation results, the data processing resource nodes are sorted individually, and the individual sorting results of each data processing resource node in the corresponding data layer are integrated to construct a comprehensive node sorting table. The resource allocation unit is used to allocate and process the corresponding data processing resource nodes according to the classification evaluation results, resource data and comprehensive node sorting table corresponding to the corresponding cultivation monitoring data, obtain the corresponding data processing resource nodes in the corresponding data layer to which the corresponding cultivation monitoring data belongs, and integrate the data processing resource nodes to generate the corresponding processing and analysis path information.

[0014] Furthermore, the process of obtaining the full-cycle analysis data corresponding to the information of the corresponding training program includes: Set up node analysis units and data analysis units; The node analysis unit is used to analyze and process the set data processing resource nodes, obtain the corresponding type of federated microbial culture data in the corresponding data layer of the corresponding data processing resource node according to the corresponding comprehensive node sorting table, generate a biological culture dataset, analyze and train the corresponding biological culture dataset based on deep learning algorithm, and construct a culture monitoring and processing model. The data analysis unit is used to input the corresponding culture monitoring data into the corresponding data processing resource node according to the corresponding processing and analysis link information, and the corresponding data processing resource node analyzes and processes the corresponding culture monitoring data to obtain the corresponding data analysis and processing results. The data analysis and processing results of each culture monitoring data corresponding to the culture project information are marked and processed to obtain the full-cycle analysis data of the corresponding culture project information.

[0015] The present invention has the following beneficial effects: 0. In this invention, by setting up a federated shared database to obtain corresponding federated microbial culture data from other shared institutions, the obtained federated microbial culture information is analyzed and processed to construct a corresponding microbial storage data lake. Based on the microbial storage data lake, the real-time data corresponding to the culture monitoring data is preprocessed to obtain the corresponding classification and evaluation results. Based on the corresponding classification and evaluation results, corresponding data processing resource nodes are set up for targeted analysis and processing, thereby improving the processing efficiency in the data processing process and avoiding the impact of a single, general data analysis and processing node on different types of culture monitoring data.

[0016] 1. In this invention, by analyzing the processing frequency data of the corresponding data information processed within different data processing resource nodes, a comprehensive node ranking table is set for the corresponding data processing resource nodes corresponding to different classification evaluation results. Based on the processing frequency data in the corresponding comprehensive node ranking table, corresponding data processing resource nodes are allocated to the corresponding culture monitoring data. By extracting a corresponding proportion of data information from the corresponding microbial storage data lake from the historical processing data corresponding to the corresponding data processing resource nodes within different data layers, a corresponding biological culture dataset is set for analysis and processing. This allows for the analysis and training of the culture monitoring processing model corresponding to the corresponding data processing resource nodes, thereby improving the accuracy of the corresponding culture monitoring data analysis and processing process. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of a microbial culture big data processing and analysis system proposed in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 like Figure 1 As shown, the present invention proposes a microbial culture big data processing and analysis system, which includes a culture processing and analysis platform. The culture processing and analysis platform includes a culture monitoring module, a data storage module, a monitoring and processing module, a resource monitoring module, a processing allocation module, and a processing and analysis module. The culture processing and analysis platform is used to acquire monitoring data of the corresponding microbial culture process in the laboratory, and to analyze and process the acquired monitoring data, thereby improving the efficiency and accuracy of the analysis of the corresponding monitoring data during the microbial culture process, and thus improving the efficiency and accuracy of data processing and analysis of the microbial culture results. Its specific implementation process includes: The culture monitoring module is used to input relevant culture project information, obtain corresponding culture monitoring data during the microbial culture process based on the culture project information, and mark the culture monitoring data according to the acquisition time. The specific implementation process includes: Set up a project entry unit and a cultivation monitoring unit; The project entry unit is equipped with entry permission information, which includes the account information of the staff in the corresponding microbial culture laboratory who are responsible for data entry. Based on the entry permissions, the corresponding staff member enters the corresponding culture project information. The culture project information includes basic project information, microbial information, and culture process information, among others. Basic project information includes project name, project number, project manager, and project start and end dates; Microbiological information includes information on the types, sources, and characteristics of microorganisms proposed in advance by the relevant project leader; The cultivation process information includes information on cultivation conditions, cultivation equipment, and cultivation testing methods. The culture monitoring unit is used to acquire culture project information entered in the project entry unit, and to monitor and manage the microbial culture process corresponding to the relevant culture project information. The process includes: Obtain the corresponding culture process information within the culture project information, and set up the corresponding sensor devices, image acquisition devices, and experimental recording devices according to the corresponding culture process information; The physicochemical parameters of the corresponding microbial culture process within the relevant culture project information are acquired through sensor devices. Image monitoring data such as the morphology, quantity, and distribution of microorganisms during the corresponding microbial culture process are obtained through image acquisition equipment within the relevant culture project information. The experimental recording equipment is used to obtain operational monitoring information on the corresponding microbial culture process within the relevant culture project information, including inoculation time, culture medium formula, type and dosage of added reagents, etc. The obtained physicochemical monitoring data, image monitoring data, and operational monitoring data are uniformly labeled as culture monitoring data in the microbial culture process corresponding to the corresponding culture project information, and are processed according to the corresponding project number and monitoring time.

[0020] The data storage module is used to collect and store different types of microbial culture data, including microbial morphology data and microbial characteristic data, to construct a microbial data lake. The specific implementation process includes: Set up information collection units, information storage units, and project storage units; The information collection unit is equipped with a federated shared database, which includes channel resources such as institutions with explicit authorization, clear data usage scope, and permitted by the agreement. Federated shared nodes are set up according to the channel resources corresponding to the corresponding sharing structure. Federated microbial culture data that is permitted to be shared within the corresponding shared structure is collected through federated sharing nodes. Based on the privacy and security requirements of the respective sharing institutions, keyword feature extraction is performed on the federated microbial culture data using natural language processing algorithms, and biological morphological feature extraction is performed using machine vision algorithms. Based on the feature extraction results, corresponding microbial morphological data and microbial characteristic data are obtained, including: Microbial characteristic data includes various types of characteristic data such as physiological characteristics, metabolic characteristics, and genetic characteristics of corresponding microorganisms at different time periods or during the culture process; Microbial morphological data includes individual morphological data and population morphological data of the corresponding types of microorganisms at different time periods or during the culture process; The information storage unit is used to classify and process the microbial characteristic data and microbial morphology data obtained corresponding to the microbial culture data, and to set up corresponding microbial type datasets according to the corresponding microbial characteristic data type and microbial morphology data type. Obtain the corresponding research target information from the corresponding microbial culture data in each microbial type dataset, and match the corresponding microbial characteristic data and the corresponding research target information in each microbial type dataset one by one to obtain the corresponding elements; The Spearman correlation coefficient analysis algorithm was used to analyze the corresponding elements in each microbial type dataset to obtain the correlation data of each corresponding element. Statistical analysis was performed on the correlation data of each corresponding element in the microbial type dataset to obtain the importance data corresponding to the microbial type dataset. Based on the importance data corresponding to each microbial type dataset, the corresponding microbial characteristic data and microbial morphology data are sorted in sequence, and the corresponding data layer is set according to the sorting results; Within the corresponding data layers, classification evaluation criteria intervals are set for the corresponding microbial type datasets, and corresponding data classification nodes are set according to the classification evaluation criteria intervals. The number of data classification nodes is determined based on the number of classification evaluation criteria intervals. The corresponding data classification nodes within each data layer are sorted, and the obtained microbial culture data is mapped to the corresponding data classification nodes within the corresponding data layer. The storage link information corresponding to the microbial culture data is obtained, and the storage link information is integrated to construct a microbial storage data lake. The microbial storage data lake centrally stores the obtained federated microbial culture information according to the corresponding storage link information, thereby improving the accuracy of big data analysis. The project storage unit is used to set up a shared space for projects based on project development information; Obtain the corresponding basic project information and training process information from the project training information; Based on the cultivation process information, each distributed storage node in the project shared space is set up. The distributed storage node is used to distribute and store cultivation monitoring data corresponding to different types and process steps. Based on the basic information of the project, set the node permission information corresponding to each distributed storage node in the project shared space. The node permission information is the permission corresponding to the relevant microbial culture related equipment and related personnel accounts. The microbial culture process corresponding to the relevant culture project information is shared, stored, and managed according to the corresponding project sharing space.

[0021] The monitoring and processing module is used to perform real-time data stream pre-evaluation processing on the obtained culture monitoring data based on culture project information and microbial storage data lake, and obtain corresponding classification and evaluation results. Its specific implementation process includes: Set up data matching and data evaluation units; The data matching unit acquires the corresponding culture project information, culture monitoring data, and microbial storage data lake. Based on the culture project information, it performs feature analysis on the currently acquired culture monitoring data, acquires the corresponding data classification node within the corresponding data layer of the corresponding monitoring type of the culture monitoring data, and sequentially acquires the corresponding storage link information within the corresponding biological storage data lake based on the data classification node corresponding to each culture monitoring data, thereby generating the monitoring matching link information corresponding to the culture project information at the current moment. The data evaluation unit is used to perform real-time data stream pre-evaluation processing on the corresponding culture monitoring data based on the monitoring matching link information corresponding to the culture project information at the current moment, and to classify and evaluate the federated microbial culture data in the monitoring matching link information based on big data algorithms to obtain the federated culture dataset. For the federated culture dataset, based on the data type corresponding to the culture monitoring data, a corresponding dynamic mean baseline and abnormal fluctuation baseline are set using a linear interpolation algorithm; Based on the corresponding dynamic mean baseline and abnormal fluctuation baseline, set the dynamic threshold intervals corresponding to the culture monitoring data. Compare and analyze the culture monitoring data with the dynamic threshold intervals of the corresponding data types. Perform integrated pre-evaluation processing according to the dynamic threshold intervals to obtain the classification evaluation results corresponding to the culture monitoring data.

[0022] The resource monitoring module is equipped with corresponding data processing resource nodes, and acquires the historical processing data and resource data corresponding to the respective data processing resource nodes. The specific implementation process includes: The resource monitoring module includes a resource management unit and a resource monitoring unit. The resource management unit is used to set up corresponding data processing resource nodes in the corresponding data layer according to the microbial storage data lake. The data processing resource nodes are used to analyze and process the culture monitoring information obtained in the corresponding data layer. The resource monitoring unit is used to acquire the historical processing data and resource data corresponding to the corresponding cultivation monitoring data processed by each data processing resource node.

[0023] The processing and allocation module is used to allocate and process the cultivation monitoring data corresponding to the corresponding classification and evaluation results based on the historical processing data and resource data of the corresponding data processing resource nodes, and to obtain the corresponding processing and analysis path information. Its specific implementation process includes: The processing and allocation module includes a resource processing unit and a resource allocation unit. The resource processing unit is used to acquire the historical processing data corresponding to each data processing resource node, perform statistical analysis on the historical processing data corresponding to each data processing resource node, and acquire the classification evaluation results of the corresponding historical processing data in the corresponding data classification node within the corresponding data layer to which the corresponding data processing resource node belongs. Statistical analysis is performed on the classification and evaluation results of each type to obtain the processing frequency data of the corresponding data processing resource nodes to which the classification and evaluation results belong; Based on the processing frequency data corresponding to the corresponding classification and evaluation results, the data processing resource nodes are sorted individually, and the processing frequency data of the data processing resource nodes corresponding to the corresponding classification and evaluation results are determined from high to low. The corresponding classification and evaluation results and the ranking results corresponding to the corresponding data processing resource nodes are integrated, and the corresponding horizontal and vertical labels are set in sequence. The corresponding processing frequency data and ranking results are mapped to the corresponding cells to construct a comprehensive node ranking table for visualization. The resource allocation unit is used to allocate and process the corresponding data processing resource nodes according to the classification evaluation results, resource data, and comprehensive node sorting table corresponding to the corresponding cultivation monitoring data. Obtain the corresponding data processing resource nodes and classification evaluation results within the corresponding data layer of the corresponding cultivation monitoring data; and obtain the real-time sorting results of the data processing resource nodes corresponding to the sorting results in the corresponding comprehensive node sorting table based on the corresponding classification evaluation results. Based on the corresponding real-time sorting results, the resource data corresponding to the corresponding data processing resource nodes are obtained sequentially, and the data processing resource nodes corresponding to the appropriate resource data are selected based on the real-time sorting results. The selected data processing resource nodes corresponding to each cultivation and monitoring data are integrated to generate corresponding processing and analysis path information.

[0024] The processing and analysis module is used to analyze and process the obtained culture monitoring data according to the corresponding processing and analysis path information, and to obtain the full-cycle analysis data of the corresponding culture project information. Its specific implementation process includes: Set up node analysis units and data analysis units; The node analysis unit is used to update the set data processing resource nodes in real time. According to the corresponding comprehensive node sorting table, it obtains the processing ratio of the processing frequency data corresponding to the classification evaluation results in the corresponding data layer to which the corresponding data processing resource node belongs. According to the processing ratio of the corresponding classification results, it selects the corresponding federated microbial culture data and generates a biological culture dataset. Based on deep learning algorithms, the corresponding biological culture datasets are analyzed and trained to construct a culture monitoring and processing model; The data analysis unit is used to input the corresponding culture monitoring data into the corresponding data processing resource node according to the corresponding processing and analysis link information, and the corresponding data processing resource node analyzes and processes the corresponding culture monitoring data to obtain the corresponding data analysis and processing results. The data analysis and processing results of each culture monitoring data corresponding to the culture project information are marked and processed to obtain the full-cycle analysis data of the corresponding culture project information. The full-cycle analysis data of the culture project is then stored in the corresponding distributed storage nodes in the corresponding project shared space according to the microbial culture process. The relevant staff members process the obtained data analysis and processing results according to the node permissions until the corresponding microbial culture process is completed.

[0025] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A microbial culture big data processing and analysis system, comprising a culture processing and analysis platform, characterized in that, The culture processing and analysis platform includes a culture monitoring module, a data storage module, a monitoring and processing module, a resource monitoring module, a processing allocation module, and a processing analysis module. The culture monitoring module is used to input the corresponding culture project information and obtain the corresponding culture monitoring data during the culture process of the corresponding microorganisms based on the culture project information. The data storage module is used to collect federated microbial culture data, obtain corresponding microbial morphology data and microbial characteristic data based on the federated microbial culture data for storage and management, construct a microbial storage data lake, and set up project sharing space according to the culture project information. The monitoring and processing module is used to perform real-time data stream pre-evaluation processing on the obtained culture monitoring data based on the culture project information and the microbial storage data lake, and obtain the corresponding classification and evaluation results; The resource monitoring module is equipped with corresponding data processing resource nodes, and obtains the historical processing data and resource data corresponding to the corresponding data processing resource nodes. The processing and allocation module is used to allocate and process the cultivation monitoring data corresponding to the corresponding classification and evaluation results based on the historical processing data and resource data of the corresponding data processing resource nodes, and to obtain the corresponding processing and analysis path information. The processing and analysis module is used to analyze and process the obtained culture monitoring data according to the corresponding processing and analysis path information, and obtain the full-cycle analysis data of the corresponding culture project information.

2. The microbial culture big data processing and analysis system according to claim 1, characterized in that, The process of entering cultivation project information and obtaining corresponding cultivation monitoring data based on that information includes: Set up a project entry unit and a cultivation monitoring unit; The project entry unit is used to enter culture project information, which includes basic project information, microbial information, and culture process information. The culture monitoring unit is equipped with corresponding sensor devices, image acquisition devices, and experimental recording devices based on Internet of Things technology according to the corresponding culture equipment. It collects the corresponding culture monitoring data during the culture process of the corresponding microorganisms according to the corresponding culture project information. The culture monitoring data includes physicochemical parameter monitoring information, image monitoring data, and operation monitoring information.

3. The microbial culture big data processing and analysis system according to claim 2, characterized in that, The process of constructing a microbial storage data lake includes: Set up information collection units, information storage units, and project storage units; The information collection unit is equipped with a federated sharing database. The federated sharing database is equipped with corresponding federated sharing nodes according to the corresponding sharing institutions. The federated sharing nodes collect the federated microbial culture data that is allowed to be shared within the corresponding sharing institutions. The federated microbial culture information includes microbial morphology data and microbial characteristic data. The information storage unit sets up microbial type datasets for the obtained federated microbial culture data based on the types corresponding to microbial morphological data and microbial characteristic data; For each microbial type dataset, the corresponding microbial culture data are matched one-to-one with the corresponding culture project information to obtain the corresponding elements. The obtained corresponding elements are analyzed and processed based on the correlation coefficient analysis algorithm to obtain the corresponding correlation data. The correlation data between each corresponding element in the microbial type dataset is integrated and analyzed to obtain the importance data. The importance data corresponding to each microbial type dataset are comprehensively sorted, and data layers are set up in sequence according to the sorting results. Data classification nodes are set up in the data layers according to the corresponding types. The obtained federated microbial culture data is mapped to the corresponding data classification nodes in each data layer, and the corresponding storage link information is obtained to store the federated microbial culture data. The storage link information of each data layer is integrated to construct a microbial storage data lake.

4. The microbial culture big data processing and analysis system according to claim 3, characterized in that, The process of setting up a shared space for a program based on the program information includes: The project storage unit is used to obtain the corresponding basic project information and training process information within the project training information, set up corresponding distributed storage nodes and node permission information based on the basic project information and training process information, and set up corresponding project shared space according to the distributed storage nodes and node permissions.

5. The microbial culture big data processing and analysis system according to claim 4, characterized in that, The process of obtaining the corresponding classification and assessment results from the culture monitoring data includes: Set up data matching and data evaluation units; The data matching unit acquires the corresponding culture project information, culture monitoring data and microbial storage data lake, performs feature analysis on the currently acquired culture monitoring data based on the culture project information, acquires the corresponding monitoring type based on the feature analysis results, acquires the corresponding storage link information in the biological storage data lake based on the corresponding monitoring type, and generates monitoring matching link information. The data evaluation unit is used to perform real-time data stream pre-evaluation processing on the corresponding culture monitoring data based on the monitoring matching link information, and to classify and evaluate the federated microbial culture data in the monitoring matching link information based on big data algorithms to obtain the federated culture dataset. For the federated culture dataset, based on the data type corresponding to the culture monitoring data, a corresponding dynamic mean baseline and abnormal fluctuation baseline are set using a linear interpolation algorithm; Based on the corresponding dynamic mean baseline and abnormal fluctuation baseline, set the dynamic threshold intervals corresponding to the culture monitoring data. Compare and analyze the culture monitoring data with the dynamic threshold intervals of the corresponding data types. Perform integrated pre-evaluation processing according to the dynamic threshold intervals to obtain the classification evaluation results corresponding to the culture monitoring data.

6. The microbial culture big data processing and analysis system according to claim 5, characterized in that, The process of setting up data processing resource nodes and obtaining the historical processing data and resource data corresponding to the respective data processing resource nodes includes: The resource monitoring module includes a resource management unit and a resource monitoring unit. The resource management unit is used to set up corresponding data processing resource nodes in the corresponding data layer according to the microbial storage data lake. The data processing resource nodes are used to analyze and process the culture monitoring information obtained in the corresponding data layer. The resource monitoring unit is used to acquire the historical processing data and resource data corresponding to the corresponding cultivation monitoring data processed by each data processing resource node.

7. The microbial culture big data processing and analysis system according to claim 6, characterized in that, The process of obtaining the processing and analysis path information corresponding to the relevant culture monitoring data includes: The processing and allocation module includes a resource processing unit and a resource allocation unit. The resource processing unit is used to acquire the historical processing data corresponding to each data processing resource node, analyze and process the historical processing data corresponding to each data processing resource node, acquire the classification evaluation results of the corresponding historical processing data in the corresponding data layer of the corresponding data processing resource node, perform statistical analysis on the classification evaluation results, and acquire the processing frequency data of the data processing resource node corresponding to the corresponding classification evaluation results. Based on the processing frequency data corresponding to the corresponding classification and evaluation results, the data processing resource nodes are sorted individually, and the individual sorting results of each data processing resource node in the corresponding data layer are integrated to construct a comprehensive node sorting table. The resource allocation unit is used to allocate and process the corresponding data processing resource nodes according to the classification evaluation results, resource data and comprehensive node sorting table corresponding to the corresponding cultivation monitoring data, obtain the corresponding data processing resource nodes in the corresponding data layer to which the corresponding cultivation monitoring data belongs, and integrate the data processing resource nodes to generate the corresponding processing and analysis path information.

8. The microbial culture big data processing and analysis system according to claim 7, characterized in that, The process of obtaining the full-cycle analysis data corresponding to the information of the corresponding training program includes: Set up node analysis units and data analysis units; The node analysis unit is used to analyze and process the set data processing resource nodes, obtain the corresponding type and proportion of federated microbial culture data in the corresponding data layer of the corresponding data processing resource node according to the corresponding comprehensive node sorting table, generate a biological culture dataset, analyze and train the corresponding biological culture dataset based on deep learning algorithm, and construct a culture monitoring and processing model. The data analysis unit is used to input the corresponding culture monitoring data into the corresponding data processing resource node according to the corresponding processing and analysis link information, and the corresponding data processing resource node analyzes and processes the corresponding culture monitoring data to obtain the corresponding data analysis and processing results. The data analysis and processing results of each culture monitoring data corresponding to the culture project information are marked and processed to obtain the full-cycle analysis data of the corresponding culture project information.

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