Data analyzer for intelligent laboratory data analysis
By introducing a data analyzer into the smart laboratory, and utilizing image recognition and AI vision robots to automatically identify experimental equipment, the timeliness problem of experimental data statistics and analysis has been solved, achieving efficient and accurate data management and analysis.
Patent Information
- Application Number
- CN202511293749.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-11
- Publication Date
- 2026-01-09
AI Technical Summary
The current laboratory experimental data statistics and analysis process relies on manual methods or paper materials, resulting in insufficient timeliness of analysis results and affecting the efficiency of experimental result processing.
Design a data analyzer for smart laboratories. Employing image recognition technology and AI vision robots, it automatically identifies the manufacturer, model, and interface information of experimental equipment. Through multi-axis robot precision positioning and data processing systems, it achieves automatic data acquisition, processing, and real-time feedback of experimental data, supporting multi-format data storage and retrieval.
It improves the efficiency of automated processing of experimental data, ensures the integrity and consistency of data, enables fast and accurate data analysis and management, and supports multi-user access control and data legality auditing.
Smart Images
Figure CN121305153A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of smart laboratory analysis technology, specifically a data analyzer for smart laboratory data analysis. Background Technology
[0002] A smart laboratory is a space based on advanced technology, with different application focuses in different scenarios. In the scientific research field, it is committed to improving the sustainability and safety of the laboratory, combining intelligent monitoring and environmental control technologies to ensure experimental safety, while supporting remote collaboration and data sharing, utilizing cloud platforms to achieve effective data flow, and providing a cross-regional innovation platform for scientific research. In the education field, it is a learning and experimental space that applies technologies such as the Internet of Things, artificial intelligence, and big data analysis to educational practice, and can provide a comprehensive experimental environment and intelligent learning management.
[0003] Currently, most laboratory experimental data statistics are achieved manually or through paper materials, which are then compared to obtain corresponding analytical results. These results are generally based on relevant experimental data standards, and the timeliness of the analysis process is clearly insufficient, greatly affecting the efficiency of experimental data processing. Therefore, it is necessary to establish a system for automatic processing and analysis of experimental data. Summary of the Invention
[0004] To address the shortcomings of existing technologies, this invention provides a data analyzer for smart laboratory data analysis, solving the problems mentioned in the background section.
[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: a data analyzer for data analysis in a smart laboratory, comprising an experimental housing, an experimental data acquisition module inside the experimental housing, an experimental platform at the front end of the experimental data acquisition module, and a data interaction platform outside the experimental housing; A data processing system is provided between the experimental data acquisition module and the data interaction platform; The data processing system includes an identification module, a data processing module, an autonomous positioning and adjustment module, and a real-time feedback and optimization module; The identification module is used to automatically identify the manufacturer, instrument name and model, and instrument interface information of the equipment. It also includes a manual input unit and compares the identified / input information with the original interface information one by one to ensure that the data is consistent. The data processing module uses the experimental data acquisition module to autonomously identify the original instrument display window, judge the data, and provide voice prompts. The autonomous positioning and adjustment module adjusts the position of the experimental data acquisition module accordingly based on the window's position data and orientation. The data processing system also includes a data management module; The data management module is used to build experimental data entry and editing functions, supports the uploading and storage of multi-format data to ensure data integrity and consistency, and provides data query functions to quickly retrieve the required data based on different conditions, including time, experimental project, and data type. The data management module also includes the ability to delete data under certain conditions to ensure the timeliness and accuracy of the data.
[0006] Optionally, the experimental chamber is composed of a bottom plate, a top plate, and a side frame, with the bottom plate located at the bottom of the side frame and the top plate located at the top of the side frame. The exterior of the side frame is equipped with a flip-up door.
[0007] Optionally, the experimental data acquisition module includes an image recognition camera for data acquisition, which is located at the top of the multi-axis robot; The multi-axis robot has a horizontal displacement platform at its bottom.
[0008] Optionally, the horizontal displacement platform includes a sliding platform and a guide rod and a drive rod that pass through the interior of the sliding platform. The guide rod and the drive rod are parallel to each other, and both ends of the guide rod are provided with mounting seats that are connected to the inner wall of the experimental chamber.
[0009] Optionally, the data interaction platform includes a display screen for dynamic display, and one side of the display screen is provided with multiple data interfaces.
[0010] Optionally, the data interface includes, but is not limited to, VGA, HDMI, USB, and DVI.
[0011] Optionally, the data processing module includes a data acquisition unit, a data preprocessing unit, a feature extraction unit, and a target recognition unit; The data acquisition unit uses an image recognition camera at the top of the multi-axis robot to acquire visual data from the original instrument display window, ensuring that the robot can capture the image of the window with sufficient resolution and clarity. The data preprocessing unit preprocesses the acquired image data, including denoising, image enhancement, and correction operations; thereby improving image quality, reducing interference factors, and providing more reliable data for subsequent target recognition. The feature extraction unit uses feature extraction algorithms from the AI Vision Robot Toolkit to extract useful features from the preprocessed image, including the image's color, texture, and shape. The target recognition unit uses the target recognition algorithm in the AI vision robot toolbox to compare the extracted features with the pre-trained model; by comparing the similarity of the features, it determines whether the current image contains a target display window and determines its position.
[0012] Optionally, the autonomous positioning adjustment module also includes a real-time feedback and optimization module. During the position adjustment process, the experimental data acquisition module obtains feedback information in real time and makes adjustments and optimizations as needed. The recognition performance is improved by adjusting the acquisition parameters and retraining the model. At the same time, the data variables in the image are captured in real time, and the variable data is continuously collected until the variable data becomes static data. This result data is then uploaded to the data interaction platform.
[0013] Optionally, the data interaction platform is used to connect to a barcode scanner, identify barcodes and QR codes, dynamically display the collected images on a screen, identify data in the collected images from multiple angles, and provide a manual data input function. At the same time, it interconnects with the laboratory management system through a modem to upload the collected data in real time.
[0014] Optionally, the data management module includes a user management unit, a data type classification unit, and a download and transmission unit; The user management unit is used to design and implement user registration, login, and permission allocation functions. Through role division and permission control, it enables different user groups to access experimental data in a differentiated manner, ensuring the authenticity of user identities and the legality of operations. The data type classification unit designs a classification system based on the nature and purpose of the experimental data, enabling automatic data classification and manual adjustment; experimental data is managed through classification labels, improving the accuracy and efficiency of data retrieval. The download and transmission unit establishes a data download application and approval process. When data in the experimental data management module is downloaded, it must follow the process of the application download module. Users need to submit a download application and explain its purpose. Only after the application is approved can the user obtain data download permission. At the same time, the system records download logs to facilitate subsequent auditing and tracking.
[0015] This invention provides a data analyzer for data analysis in smart laboratories, which has the following beneficial effects: This data analyzer for smart laboratory data analysis uses a 7-inch Android system display screen and image recognition technology to collect data from the test results of the analytical instruments. The device can automatically identify the equipment manufacturer (or manually input), instrument name and model (or manually input), and instrument interface information (intelligently identifying and matching the original interface information). It then uses a desktop 6-axis AI vision robot to autonomously identify the original instrument display window and preprocess the collected image data, including noise reduction, image enhancement, and correction. These preprocessing steps improve image quality, reduce interference factors, and provide more reliable data for subsequent target recognition. Using the feature extraction algorithm in the AI vision robot toolbox, useful features are extracted from the preprocessed images. Finally, the target recognition algorithm in the AI vision robot toolbox compares the extracted features with a pre-trained model. By comparing the similarity of features, the robot can determine whether the current image contains a target display window and determine its location; Based on the window's position and orientation, the robot can precisely move to the appropriate location for further operation or analysis. Throughout the process, the robot can acquire feedback information in real time and make adjustments and optimizations as needed. It can capture data variables in the image in real time, continuously collecting and acquiring variable data until the variable data becomes static data, and then upload this result data to the analysis system. The data information read can be interconnected with the laboratory management system via a modem to upload the collected data in real time and archive the analysis data. Attached Figure Description
[0016] Figure 1 This is a schematic diagram of the external front view of the invention; Figure 2 This is a frontal full sectional view of the invention; Figure 3 This is a side view full sectional schematic diagram of the invention; Figure 4 This is a schematic diagram of the data processing flow of the invention.
[0017] In the diagram: 1. Experimental chamber; 101. Base plate; 102. Top plate; 103. Side frame; 104. Flip-top door; 2. Experimental data acquisition module; 201. Image recognition camera; 202. Multi-axis robot; 203. Horizontal displacement platform; 204. Sliding platform; 205. Guide rod; 206. Drive rod; 207. Mounting base; 3. Experimental platform; 4. Data interaction platform; 401. Display screen; 402. Data interface. Detailed Implementation
[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.
[0019] In the description of this invention, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0020] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0021] Please see Figures 1 to 4 The present invention provides a technical solution: a data analyzer for data analysis in a smart laboratory, comprising an experimental box 1, an experimental data acquisition module 2 inside the experimental box 1, an experimental platform 3 at the front end of the experimental data acquisition module 2, and a data interaction platform 4 outside the experimental box 1. The experimental chamber 1 consists of a bottom plate 101, a top plate 102, and a side frame 103. The bottom plate 101 is located at the bottom of the side frame 103, and the top plate 102 is located at the top of the side frame 103. The exterior of the side frame 103 is provided with a flip-up door 104; The experimental data acquisition module 2 includes an image recognition camera 201 for data acquisition, which is located at the top of the multi-axis robot 202. The bottom of the multi-axis robot 202 is equipped with a horizontal displacement platform 203.
[0022] The horizontal displacement platform 203 includes a sliding platform 204 and a guide rod 205 and a drive rod 206 that pass through the interior of the sliding platform 204. The guide rod 205 and the drive rod 206 are parallel to each other, and both ends of the guide rod 205 are provided with mounting seats 207 that are connected to the inner wall of the experimental chamber 1. A data processing system is installed between the experimental data acquisition module 2 and the data interaction platform 4; The data interaction platform 4 includes a display screen 401 for dynamic display, and a plurality of data interfaces 402 are provided on one side of the display screen 401; Data interface 402 includes, but is not limited to, VGA, HDMI, USB, and DVI; The data interaction platform 4 is used to connect to the barcode scanner, identify barcodes and QR codes, dynamically display the collected images on the display screen 401, identify data in the collected images from multiple angles, and has a manual data input function. At the same time, it interconnects with the laboratory management system through the modem to upload the collected data in real time. The data processing system includes an identification module, a data processing module, an autonomous positioning and adjustment module, and a real-time feedback and optimization module; The identification module is used to automatically identify the manufacturer, instrument name and model, and instrument interface information of the equipment. It also includes a manual input unit and compares the identified / input information with the original interface information one by one to ensure that the data is consistent. The data processing module uses the experimental data acquisition module 2 to autonomously identify the original instrument display window, judge the data, and provide voice prompts. The data processing module includes a data acquisition unit, a data preprocessing unit, a feature extraction unit, and a target recognition unit; The data acquisition unit uses the image recognition camera 201 at the top of the multi-axis robot 202 to acquire the visual data of the original instrument display window; ensuring that the robot can capture the image of the window with sufficient resolution and clarity; The data preprocessing unit preprocesses the acquired image data, including denoising, image enhancement, and correction operations; thereby improving image quality, reducing interference factors, and providing more reliable data for subsequent target recognition. The feature extraction unit uses feature extraction algorithms from the AI Vision Robot Toolkit to extract useful features from the preprocessed image, including the image's color, texture, and shape. The target recognition unit uses the target recognition algorithm in the AI vision robot toolbox to compare the extracted features with the pre-trained model; by comparing the similarity of the features, it determines whether the current image contains a target display window and determines its position. The autonomous positioning and adjustment module adjusts the position of the experimental data acquisition module 2 accordingly based on the window's position data and orientation. The autonomous positioning and adjustment module also includes a real-time feedback and optimization module. During the position adjustment process, the experimental data acquisition module 2 obtains feedback information in real time and makes adjustments and optimizations as needed. The recognition performance is improved by adjusting the acquisition parameters and retraining the model. At the same time, the data variables in the image are captured in real time, and the variable data is continuously acquired until the variable data becomes static data. This result data is then uploaded to the data interaction platform 4. The data processing system also includes a data management module; The data management module is used to build experimental data entry and editing functions, supports the uploading and storage of multi-format data to ensure data integrity and consistency, and provides data query functions to quickly retrieve the required data based on different conditions, including time, experimental project, and data type. The data management module also includes the ability to delete data under certain conditions to ensure the timeliness and accuracy of the data. The data management module includes a user management unit, a data type classification unit, and a download and transmission unit; The user management unit is used to design and implement user registration, login, and permission allocation functions. Through role division and permission control, it enables different user groups to access experimental data in a differentiated manner, ensuring the authenticity of user identities and the legality of operations. The data type classification unit designs a classification system based on the nature and purpose of the experimental data, enabling automatic data classification and manual adjustment; experimental data is managed through classification labels, improving the accuracy and efficiency of data retrieval. The download and transmission unit establishes a data download application and approval process. When data in the experimental data management module is downloaded, it must follow the process of the application download module. Users need to submit a download application and explain its purpose. Only after the application is approved can the user obtain data download permission. At the same time, the system records download logs to facilitate subsequent auditing and tracking.
[0023] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
Claims
1. A data analyzer for data analysis in a smart laboratory, comprising an experimental enclosure (1), characterized in that: The experimental box (1) is equipped with an experimental data acquisition module (2) inside, an experimental platform (3) is provided at the front end of the experimental data acquisition module (2), and a data interaction platform (4) is provided outside the experimental box (1). A data processing system is provided between the experimental data acquisition module (2) and the data interaction platform (4); The data processing system includes an identification module, a data processing module, an autonomous positioning and adjustment module, and a real-time feedback and optimization module; The identification module is used to automatically identify the manufacturer, instrument name and model, and instrument interface information of the equipment. It also includes a manual input unit and compares the identified / input information with the original interface information one by one to ensure that the data is consistent. The data processing module uses the experimental data acquisition module (2) to autonomously identify the original instrument display window, judge the data, and provide voice prompts. The autonomous positioning and adjustment module adjusts the position of the experimental data acquisition module (2) accordingly based on the window's position data and orientation; The data processing system also includes a data management module; The data management module is used to build experimental data entry and editing functions, supports the uploading and storage of multi-format data to ensure data integrity and consistency, and provides data query functions to quickly retrieve the required data based on different conditions, including time, experimental project, and data type. The data management module also includes the ability to delete data under certain conditions to ensure the timeliness and accuracy of the data.
2. The data analyzer for smart laboratory data analysis according to claim 1, characterized in that: The experimental chamber (1) consists of a bottom plate (101), a top plate (102) and a side frame (103). The bottom plate (101) is located at the bottom of the side frame (103), and the top plate (102) is located at the top of the side frame (103). The exterior of the side frame (103) is provided with a flip door (104).
3. A data analyzer for smart laboratory data analysis according to claim 1, characterized in that: The experimental data acquisition module (2) includes an image recognition camera (201) for data acquisition, which is located at the top of the multi-axis robot (202); The bottom of the multi-axis robot (202) is equipped with a horizontal displacement platform (203).
4. A data analyzer for smart laboratory data analysis according to claim 3, characterized in that: The horizontal displacement platform (203) includes a sliding platform (204) and a guide rod (205) and a drive rod (206) passing through the interior of the sliding platform (204). The guide rod (205) and the drive rod (206) are parallel to each other. Both ends of the guide rod (205) are provided with mounting seats (207) that are connected to the inner wall of the experimental chamber (1).
5. A data analyzer for smart laboratory data analysis according to claim 1, characterized in that: The data interaction platform (4) includes a display screen (401) for dynamic display, and a plurality of data interfaces (402) are provided on one side of the display screen (401).
6. A data analyzer for smart laboratory data analysis according to claim 5, characterized in that: The data interface (402) includes, but is not limited to, VGA, HDMI, USB, and DVI.
7. A data analyzer for smart laboratory data analysis according to claim 4, characterized in that: The data processing module includes a data acquisition unit, a data preprocessing unit, a feature extraction unit, and a target recognition unit; The data acquisition unit uses the image recognition camera (201) at the top of the multi-axis robot (202) to acquire the visual data of the original instrument display window; Ensure the robot can capture images of the window with sufficient resolution and clarity; The data preprocessing unit preprocesses the acquired image data, including denoising, image enhancement, and correction operations; thereby improving image quality, reducing interference factors, and providing more reliable data for subsequent target recognition. The feature extraction unit uses feature extraction algorithms from the AI Vision Robot Toolkit to extract useful features from the preprocessed image, including the image's color, texture, and shape. The target recognition unit uses the target recognition algorithm in the AI vision robot toolbox to compare the extracted features with the pre-trained model; by comparing the similarity of the features, it determines whether the current image contains a target display window and determines its position.
8. A data analyzer for smart laboratory data analysis according to claim 6, characterized in that: The autonomous positioning adjustment module also includes a real-time feedback and optimization module. During the position adjustment process, the experimental data acquisition module (2) acquires feedback information in real time and makes adjustments and optimizations as needed. The recognition performance is improved by adjusting the acquisition parameters and retraining the model. At the same time, the data variables in the image are captured in real time, and the variable data is continuously acquired until the variable data becomes static data. This result data is then uploaded to the data interaction platform (4).
9. A data analyzer for smart laboratory data analysis according to claim 8, characterized in that: The data interaction platform (4) is used to connect to the barcode scanner, identify barcodes and QR codes, dynamically display the collected images through the display screen (401), identify the data in the collected images from multiple angles, and retain the function of manual data input. At the same time, it connects with the laboratory management system through the modem to upload the collected data in real time.
10. A data analyzer for smart laboratory data analysis according to claim 1, characterized in that: The data management module includes a user management unit, a data type classification unit, and a download and transmission unit; The user management unit is used to design and implement user registration, login, and permission allocation functions. Through role division and permission control, it enables different user groups to access experimental data in a differentiated manner, ensuring the authenticity of user identities and the legality of operations. The data type classification unit designs a classification system based on the nature and purpose of the experimental data, enabling automatic data classification and manual adjustment; experimental data is managed through classification labels, improving the accuracy and efficiency of data retrieval. The download and transmission unit establishes a data download application and approval process. When data in the experimental data management module is downloaded, it must follow the process of the application download module. Users need to submit a download application and explain its purpose. Only after the application is approved can the user obtain data download permission. At the same time, the system records download logs to facilitate subsequent auditing and tracking.