Swab detection self-service system and sampling method

Abstract

The invention discloses a swab detection self-service system, which comprises an identity recognition module, a sample collection management module, a swab detection module and a swab detection module, and is characterized in that the identity recognition module is used for recognizing a user identity in a manner of combining a biological characteristic recognition technology and intelligent card recognition, and the module recognizes user identity information and transmits the user identity information to the sample collection management module; the sample collection and management module comprises an intelligent swab grabbing device and a swab positioning and guiding mechanism, the intelligent swab grabbing device adopts a high-precision mechanical arm, the positioning precision error of the intelligent swab grabbing device does not exceed 0.1 mm, and the detection and analysis module adopts a molecular detection technology to analyze a collected sample and transmits a detection result to the result feedback and storage module; according to the invention, by adopting an identity recognition mode of combining a biological feature recognition technology and smart card recognition, the accuracy and efficiency of identity recognition are improved, the complexity and errors of traditional identity recognition are reduced, a user can enter a detection process more quickly and accurately, and the convenience and overall efficiency of detection are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of swab detection, and in particular to a swab detection self-service system and a sampling method. Background Art

[0002] In the field of medical testing, swab testing is a common and important diagnostic method, widely used in disease screening, pathogen detection, etc. However, traditional swab testing methods have many limitations.

[0003] Traditional swab testing usually requires professional medical staff to collect samples, which not only places high demands on the number and professional skills of medical staff, but also faces large-scale testing needs, such as public health emergencies or mass disease screening. Limited medical staff resources are often unable to meet the needs of rapid and large-scale testing. Large amounts of manpower input also increase testing costs and organizational difficulties.

[0004] In traditional testing, the identification method is relatively simple, and may only rely on manual registration or a single certificate verification, which is prone to identification errors. For example, in a testing site with a large number of people and a noisy environment, there may be recording errors or confusion of identities, which will cause trouble for the subsequent accurate recording and tracking of test results. Moreover, this traditional identification method is inefficient, resulting in a long overall testing process.

[0005] Since sample collection is highly dependent on the experience and operating standards of medical staff, operational differences between different medical staff may lead to uneven sample collection quality. For example, if factors such as the depth of swab insertion and the accuracy of the collection site are not properly grasped, it will directly affect the quality of the sample and, in turn, the accuracy of the test results. In addition, due to the lack of real-time and effective sample quality assessment methods, sample quality problems are often discovered in the late stages of the testing process, resulting in the need to re-collect samples, wasting time and resources.

[0006] Traditional testing and analysis methods usually require a large number of samples to be sent to the laboratory, and then analyzed by professionals using large-scale testing equipment. This centralized testing model results in a long testing cycle, and it usually takes hours or even days to get the test results, which is difficult to meet the needs of rapid diagnosis and timely prevention and control of diseases. Especially in response to emergency epidemics, the timeliness of test results is crucial for epidemic control and patient treatment.

[0007] In traditional testing, test results are mostly recorded in paper or simple spreadsheets. Data storage is scattered and lacks unified standards, which is not convenient for data management and query. At the same time, in terms of data sharing, due to the lack of a secure and efficient data transmission mechanism, test results are difficult to share quickly and accurately with medical institutions or related health management platforms, which is not conducive to disease monitoring, statistical analysis and overall medical decision-making.

[0008] To sum up, in the face of many problems of traditional swab testing, combined with the development of existing technologies, the development of a swab testing self-service system and sampling method has important practical significance and broad application prospects. It can improve detection efficiency, accuracy and user experience, and meet the growing demand for medical testing. Summary of the invention

[0009] The present invention provides a self-service swab testing system and a sampling method to solve the problems mentioned in the above-mentioned prior art.

[0010] In order to achieve the above object, the present invention adopts the following technical solution: a swab detection self-service system, comprising:

[0011] Identity recognition module: The user's identity is recognized by combining biometric recognition technology with smart card recognition. The accuracy of biometric recognition is P b , the smart card recognition accuracy is P c , comprehensive recognition accuracy P total By formula: P total =P b ×P c +(1-P b )×(1-P c ) is calculated, when the set threshold is reached: P total When the value is ≥99%, the user identity is confirmed to be valid, and the module identifies the user identity information and transmits it to the sample collection management module;

[0012] Sample collection management module: including an intelligent swab grabbing device and a swab positioning and guiding mechanism. The intelligent swab grabbing device adopts a high-precision robotic arm with a positioning accuracy error of no more than 0.1 mm. Through a preset path planning algorithm, the motion path function of the robotic arm is set to be f(x, y, z, t), where (x, y, z) is the spatial coordinate and t is the time. The swab is accurately grabbed and passed to the user according to the user's position and sample collection requirements. The swab positioning and guiding mechanism guides the user to accurately place the swab in the detection area through a combination of laser positioning and voice prompts to ensure the accuracy of sampling, and the sample collection status is fed back to the detection and analysis module in real time;

[0013] Detection and analysis module: Use molecular detection technology to analyze the collected samples, and set the detection time as T d, the detection sensitivity is S d By optimizing the detection algorithm and instrument parameters, the detection sensitivity S d ≥95%, detection time T d ≤30 minutes, the module transmits the test results to the result feedback and storage module;

[0014] Result feedback and storage module: Receive the test results transmitted by the detection and analysis module, and feed back the results to the user by displaying on the screen or by SMS notification. The test results are classified and stored according to the user identity information using encryption storage technology. The storage data format complies with the relevant medical data standards. The encryption key of the stored data is K, and the AES symmetric encryption algorithm is used to encrypt the data. The encrypted data is C=E(K,M), where M is the original data and E is the encryption function;

[0015] System cleaning and disinfection module: After each sample collection is completed, the sample collection area is automatically cleaned and disinfected by combining ultraviolet irradiation and disinfectant spraying. The ultraviolet irradiation intensity is set to I u , the concentration of disinfectant is C d , killing bacteria and viruses above the sample collection area.

[0016] Preferably, the user interaction interface module: the user interacts with the system through a touch screen or voice interaction, and the interface displays operation guides and detection progress information. The user operation error rate is set to E o By optimizing the interface design and interaction process, the user operation error rate is reduced to E o ≤1%;

[0017] Equipment status monitoring module: real-time monitoring of the operating status of each device in the system, including the working status of the robot arm and the performance parameters of the detection instrument. The equipment failure warning threshold is set as T w , when the equipment operating parameters exceed T w When a fault occurs, it will automatically issue a fault warning and notify maintenance personnel.

[0018] Preferably, the sample quality assessment module: performs real-time assessment on the quality of collected samples, and assumes that the sample quality assessment index is Q, which is related to factors such as the integrity of the sample and the accuracy of the collection position. The sample quality is quantitatively assessed through image analysis and sensor data fusion technology. When the sample quality assessment index Q is lower than the set standard, the user is prompted to recollect the sample;

[0019] Data transmission and sharing module: A secure data transmission protocol is used to transmit the test results to medical institutions or related health management platforms with user authorization. The data transmission success rate is S t By optimizing the network configuration and data transmission algorithm, the data transmission success rate St ≥98%, realizing the sharing and effective use of detection data.

[0020] Preferably, intelligent scheduling module: This module uses a scheduling algorithm based on artificial intelligence to intelligently schedule system resources. r , by analyzing the user's arrival time, sample collection and testing demand factors, dynamically adjust the working status of equipment such as the intelligent swab grabbing device and the detection and analysis module, and set the scheduling optimization objective function as:

[0021] Where a, b, c are constants, and the resource scheduling solution is realized by solving the maximum value of the function;

[0022] Environmental monitoring and adjustment module: real-time monitoring of environmental parameters in the sample collection area, including temperature, humidity, and air quality. Assume that the environmental comfort index is E c , which is related to temperature T, humidity H, and air quality index A, through formula E c =αT+βH+γA, where α, β, and γ are weight coefficients. The air conditioner and air purification equipment are automatically adjusted according to the environmental comfort index to ensure the accuracy of sample collection and detection.

[0023] Preferably, the user interaction interface module supports multi-language display and voice switching functions, and the language switching accuracy is set to S l By optimizing the language recognition and switching algorithms, the language switching accuracy rate is S l ≥95%, meeting the language requirements of different users and improving the versatility and usability of the system;

[0024] The user interaction interface module has a personalized setting function. Users can set the interface color and font size parameters. Set the user satisfaction index as S u , collect user satisfaction with personalized settings through user surveys and feedback mechanisms, and use the user satisfaction index S u When it is lower than the set standard, the personalized setting function will be optimized and improved.

[0025] Preferably, the present invention also discloses a self-service sampling method for swab detection, comprising the following steps:

[0026] Step 1: Identity recognition: The identity recognition module uses a combination of biometric recognition technology and smart card recognition to accurately identify the user's identity. After confirming that the user's identity is valid, proceed to the next step;

[0027] Step 2: Sample collection preparation: the intelligent swab grabbing device in the sample collection management module grabs the swab and passes it to the user, and the swab positioning and guiding mechanism guides the user to prepare for sample collection through laser positioning and voice prompts;

[0028] Step 3: Sample collection: Under the guidance of the swab positioning guide mechanism, the user accurately places the swab in the detection area for sample collection. The sample collection management module monitors the collection process in real time to ensure that the collected samples meet the quality requirements and transfers the collected samples to the detection and analysis module.

[0029] Step 4: Detection and analysis: The detection and analysis module uses advanced molecular detection technology to quickly analyze the collected samples and obtain the test results under the premise of meeting the detection sensitivity and detection time requirements;

[0030] Step 5: Result feedback and storage. The result feedback and storage module receives the detection results of the detection and analysis module, feeds back the results to the user and encrypts and stores the data.

[0031] Preferably, in the identity identification process of step one, in addition to biometric identification and smart card identification, a mobile phone verification code verification link is added to improve the security of identity identification. When the user identity identification information is inconsistent with the pre-stored information, a mobile phone verification code is sent for secondary verification to ensure the authenticity of the user's identity.

[0032] Preferably, in the detection and analysis process of step four, parallel detection technology is used to divide the sample into multiple sub-samples for simultaneous detection. Suppose the detection efficiency is improved by a multiple of N. Through reasonable sample allocation and detection task scheduling, the detection efficiency is improved by a multiple of N≥2, thereby shortening the detection time and improving the detection efficiency.

[0033] Preferably, in the sample collection preparation process of step 2, virtual reality VR technology is introduced to train users on sampling operations, and the sampling scene and operation process are simulated by VR. The user training effect evaluation index is set as E t , based on factors such as user operation accuracy and proficiency in VR simulation, when the user training effect evaluation index E t When the set standards are met, users can proceed with actual sample collection operations;

[0034] In the result feedback and storage process of step five, data analysis and report generation functions are added to perform data analysis on the user's test results and generate a detailed test report. The report content includes test items, test results, and result interpretation information, and is provided to the user in the form of an electronic document.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention improves the accuracy and efficiency of identity recognition by adopting an identity recognition method that combines biometric recognition technology with smart card recognition, reduces the complexity and errors of traditional identity recognition, allows users to enter the detection process more quickly and accurately, and improves the convenience and overall efficiency of detection.

[0037] The present invention ensures the accuracy of sample collection through the intelligent swab grasping device of the high-precision mechanical arm in the sample collection management module and the swab positioning and guiding mechanism combining laser positioning with voice prompts. At the same time, the sample quality assessment module assesses the sample quality in real time to ensure the quality of the samples entering the detection and analysis link, thereby improving the accuracy of the detection results.

[0038] The present invention adopts advanced molecular detection technology and optimizes algorithms and instrument parameters through the detection and analysis module, thereby shortening the detection time. At the same time, virtual reality technology is introduced to train users on sampling operations, thereby improving the accuracy and standardization of sample collection, reducing sample quality problems and re-collection caused by improper operation, and improving the overall detection efficiency.

[0039] The present invention ensures the security, authenticity and integrity of test data through the encryption storage technology of the result feedback and storage module, the secure transmission protocol of the data transmission and sharing module and the blockchain technology. The data analysis and report generation functions facilitate users and medical staff to accurately interpret the test results, thereby improving the application value and accuracy of the test results.

[0040] The present invention improves system resource utilization and reduces user waiting time through the intelligent scheduling module of system resources. The environmental monitoring and adjustment module provides users with a comfortable sampling environment. At the same time, the system cleaning and disinfection module ensures the hygiene and safety of the sample collection area, thereby improving user experience and system security. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a schematic block diagram of the swab testing self-service system proposed by the present invention;

[0042] Figure 2 This is a schematic diagram of the self-service sampling method for swab testing proposed in the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0045] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0046] Reference Figure 1-2 :A swab testing self-service system, comprising:

[0047] Identity recognition module: The user's identity is recognized by combining biometric recognition technology with smart card recognition. The accuracy of biometric recognition is P b , the smart card recognition accuracy is P c , comprehensive recognition accuracy P total By formula: P total =P b ×P c +(1-P b )×(1-P c ) is calculated, when the set threshold is reached: P total When the value is ≥99%, the user identity is confirmed to be valid, and the module identifies the user identity information and transmits it to the sample collection management module;

[0048] Sample collection management module: including an intelligent swab grabbing device and a swab positioning and guiding mechanism. The intelligent swab grabbing device adopts a high-precision robotic arm with a positioning accuracy error of no more than 0.1 mm. Through a preset path planning algorithm, the motion path function of the robotic arm is set to be f(x, y, z, t), where (x, y, z) is the spatial coordinate and t is the time. The swab is accurately grabbed and passed to the user according to the user's position and sample collection requirements. The swab positioning and guiding mechanism guides the user to accurately place the swab in the detection area through a combination of laser positioning and voice prompts to ensure the accuracy of sampling, and the sample collection status is fed back to the detection and analysis module in real time;

[0049] Detection and analysis module: Use molecular detection technology to analyze the collected samples, and set the detection time as T d , the detection sensitivity is S d By optimizing the detection algorithm and instrument parameters, the detection sensitivity S d ≥95%, detection time T d ≤30 minutes, the module transmits the test results to the result feedback and storage module;

[0050] Result feedback and storage module: Receive the test results transmitted by the detection and analysis module, and feed back the results to the user by displaying on the screen or by SMS notification. The test results are classified and stored according to the user identity information using encryption storage technology. The storage data format complies with the relevant medical data standards. The encryption key of the stored data is K, and the AES symmetric encryption algorithm is used to encrypt the data. The encrypted data is C=E(K,M), where M is the original data and E is the encryption function;

[0051] System cleaning and disinfection module: After each sample collection is completed, the sample collection area is automatically cleaned and disinfected by combining ultraviolet irradiation and disinfectant spraying. The ultraviolet irradiation intensity is set to I u , the concentration of disinfectant is C d , killing bacteria and viruses above the sample collection area.

[0052] In the present invention, the user interaction interface module: the user interacts with the system through a touch screen or voice interaction, and the interface displays operation guides and detection progress information. The user operation error rate is set to E o By optimizing the interface design and interaction process, the user operation error rate is reduced to E o ≤1%;

[0053] Equipment status monitoring module: real-time monitoring of the operating status of each device in the system, including the working status of the robot arm and the performance parameters of the detection instrument. The equipment failure warning threshold is set as T w , when the equipment operating parameters exceed T wWhen a fault occurs, it will automatically issue a fault warning and notify maintenance personnel.

[0054] In the present invention, the sample quality assessment module: performs real-time assessment on the quality of collected samples, and assumes that the sample quality assessment index is Q, which is related to factors such as the integrity of the sample and the accuracy of the collection position. The sample quality is quantitatively assessed through image analysis and sensor data fusion technology. When the sample quality assessment index Q is lower than the set standard, the user is prompted to recollect the sample;

[0055] Data transmission and sharing module: A secure data transmission protocol is used to transmit the test results to medical institutions or related health management platforms with user authorization. The data transmission success rate is S t By optimizing the network configuration and data transmission algorithm, the data transmission success rate S t ≥98%, realizing the sharing and effective use of detection data.

[0056] In the present invention, the intelligent scheduling module: This module uses a scheduling algorithm based on artificial intelligence to intelligently schedule the system resources. r , by analyzing the user's arrival time, sample collection and testing demand factors, dynamically adjust the working status of equipment such as the intelligent swab grabbing device and the detection and analysis module, and set the scheduling optimization objective function as:

[0057] Where a, b, c are constants, and the resource scheduling solution is realized by solving the maximum value of the function;

[0058] Environmental monitoring and adjustment module: real-time monitoring of environmental parameters in the sample collection area, including temperature, humidity, and air quality. Assume that the environmental comfort index is E c , which is related to temperature T, humidity H, and air quality index A, through formula E c =αT+βH+γA, where α, β, and γ are weight coefficients. The air conditioner and air purification equipment are automatically adjusted according to the environmental comfort index to ensure the accuracy of sample collection and detection.

[0059] In the present invention, the user interaction interface module supports multi-language display and voice switching functions. The language switching accuracy is S l By optimizing the language recognition and switching algorithms, the language switching accuracy rate is S l ≥95%, meeting the language requirements of different users and improving the versatility and usability of the system;

[0060] The user interaction interface module has a personalized setting function. Users can set the interface color and font size parameters. Set the user satisfaction index as S u, collect user satisfaction with personalized settings through user surveys and feedback mechanisms, and use the user satisfaction index S u When it is lower than the set standard, the personalized setting function will be optimized and improved.

[0061] The present invention also discloses a self-service sampling method for swab detection, comprising the following steps:

[0062] Step 1: Identity recognition: The identity recognition module uses a combination of biometric recognition technology and smart card recognition to accurately identify the user's identity. After confirming that the user's identity is valid, proceed to the next step;

[0063] Step 2: Sample collection preparation: the intelligent swab grabbing device in the sample collection management module grabs the swab and passes it to the user, and the swab positioning and guiding mechanism guides the user to prepare for sample collection through laser positioning and voice prompts;

[0064] Step 3: Sample collection: Under the guidance of the swab positioning guide mechanism, the user accurately places the swab in the detection area for sample collection. The sample collection management module monitors the collection process in real time to ensure that the collected samples meet the quality requirements and transfers the collected samples to the detection and analysis module.

[0065] Step 4: Detection and analysis: The detection and analysis module uses advanced molecular detection technology to quickly analyze the collected samples and obtain the test results under the premise of meeting the detection sensitivity and detection time requirements;

[0066] Step 5: Result feedback and storage. The result feedback and storage module receives the detection results of the detection and analysis module, feeds back the results to the user and encrypts and stores the data.

[0067] In the present invention, in the identity identification process of step one, in addition to biometric identification and smart card identification, a mobile phone verification code verification link is added to improve the security of identity identification. When the user identity identification information is inconsistent with the pre-stored information, a mobile phone verification code is sent for secondary verification to ensure the authenticity of the user's identity.

[0068] In the present invention, in the detection and analysis process of step four, parallel detection technology is adopted to divide the sample into multiple sub-samples for simultaneous detection. Assuming that the detection efficiency is improved by a multiple of N, through reasonable sample allocation and detection task scheduling, the detection efficiency is improved by a multiple of N≥2, thereby shortening the detection time and improving the detection efficiency.

[0069] In the present invention, in the sample collection preparation process of step 2, virtual reality VR technology is introduced to train users on sampling operation. The sampling scene and operation process are simulated by VR. The user training effect evaluation index is set as E t, based on factors such as user operation accuracy and proficiency in VR simulation, when the user training effect evaluation index E t When the set standards are met, users can proceed with actual sample collection operations;

[0070] In the result feedback and storage process of step five, data analysis and report generation functions are added to perform data analysis on the user's test results and generate a detailed test report. The report content includes test items, test results, and result interpretation information, and is provided to the user in the form of an electronic document.

[0071] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A swab testing self-service system, characterized in that: include: Identity recognition module: The user's identity is recognized by combining biometric recognition technology with smart card recognition. The accuracy of biometric recognition is P b , the smart card recognition accuracy is P c , comprehensive recognition accuracy P total By formula: P total =P b ×P c +(1-P b )×(1-P c ) is calculated, when the set threshold is reached: P total When the value is ≥99%, the user identity is confirmed to be valid, and the module identifies the user identity information and transmits it to the sample collection management module; Sample collection management module: including an intelligent swab grabbing device and a swab positioning and guiding mechanism. The intelligent swab grabbing device adopts a high-precision robotic arm with a positioning accuracy error of no more than 0.1 mm. Through a preset path planning algorithm, the motion path function of the robotic arm is set to be f(x, y, z, t), where (x, y, z) is the spatial coordinate and t is the time. The swab is accurately grabbed and passed to the user according to the user's position and sample collection requirements. The swab positioning and guiding mechanism guides the user to accurately place the swab in the detection area through a combination of laser positioning and voice prompts to ensure the accuracy of sampling, and the sample collection status is fed back to the detection and analysis module in real time; Detection and analysis module: Use molecular detection technology to analyze the collected samples, and set the detection time as T d , the detection sensitivity is S d By optimizing the detection algorithm and instrument parameters, the detection sensitivity S d ≥95%, detection time T d ≤30 minutes, the module transmits the test results to the result feedback and storage module; Result feedback and storage module: Receive the test results transmitted by the detection and analysis module, and feed back the results to the user by displaying on the screen or by SMS notification. The test results are classified and stored according to the user identity information using encryption storage technology. The storage data format complies with the relevant medical data standards. The encryption key of the stored data is K, and the AES symmetric encryption algorithm is used to encrypt the data. The encrypted data is C=E(K,M), where M is the original data and E is the encryption function; System cleaning and disinfection module: After each sample collection is completed, the sample collection area is automatically cleaned and disinfected by combining ultraviolet irradiation and disinfectant spraying. The ultraviolet irradiation intensity is set to I u , the concentration of disinfectant is C d , killing bacteria and viruses above the sample collection area.

2. The swab testing self-service system according to claim 1, characterized in that: Also includes: User interaction interface module: Users interact with the system through touch screen or voice interaction. The interface displays operation guides and detection progress information. The user operation error rate is set to E. o By optimizing the interface design and interaction process, the user operation error rate is reduced to E o ≤1%; Equipment status monitoring module: real-time monitoring of the operating status of each device in the system, including the working status of the robot arm and the performance parameters of the detection instrument. The equipment failure warning threshold is set as T w , when the equipment operating parameters exceed T w When a fault occurs, it will automatically issue a fault warning and notify maintenance personnel.

3. The swab testing self-service system according to claim 1, characterized in that: Also includes: Sample quality assessment module: conducts real-time assessment of the quality of collected samples. The sample quality assessment index is set as Q, which is related to factors such as sample integrity and collection position accuracy. The sample quality is quantitatively assessed through image analysis and sensor data fusion technology. When the sample quality assessment index Q is lower than the set standard, the user is prompted to recollect the sample. Data transmission and sharing module: A secure data transmission protocol is used to transmit the test results to medical institutions or related health management platforms with user authorization. The data transmission success rate is S t By optimizing the network configuration and data transmission algorithm, the data transmission success rate S t ≥98%, realizing the sharing and effective use of detection data.

4. The swab testing self-service system according to claim 1, characterized in that: Also includes: Intelligent scheduling module: This module uses an artificial intelligence-based scheduling algorithm to intelligently schedule system resources. r , by analyzing the user's arrival time, sample collection and testing demand factors, dynamically adjust the working status of equipment such as the intelligent swab grabbing device and the detection and analysis module, and set the scheduling optimization objective function as: Where a, b, c are constants, and the resource scheduling solution is realized by solving the maximum value of the function; Environmental monitoring and adjustment module: real-time monitoring of environmental parameters in the sample collection area, including temperature, humidity, and air quality. Assume that the environmental comfort index is E c , which is related to temperature T, humidity H, and air quality index A, through formula E c =αT+βH+γA, where α, β, and γ are weight coefficients. The air conditioner and air purification equipment are automatically adjusted according to the environmental comfort index to ensure the accuracy of sample collection and detection.

5. The user interaction interface module according to claim 2, characterized in that: The user interface module supports multi-language display and voice switching functions. The language switching accuracy is S l By optimizing the language recognition and switching algorithms, the language switching accuracy rate is S l ≥95%, meeting the language requirements of different users and improving the versatility and usability of the system; The user interaction interface module has a personalized setting function. Users can set the interface color and font size parameters. Set the user satisfaction index as S u , collect user satisfaction with personalized settings through user surveys and feedback mechanisms, and use the user satisfaction index S u When it is lower than the set standard, the personalized setting function will be optimized and improved.

6. A self-service sampling method for swab detection, characterized in that: The following steps are involved: Step 1: Identity recognition: The identity recognition module uses a combination of biometric recognition technology and smart card recognition to accurately identify the user's identity. After confirming that the user's identity is valid, proceed to the next step; Step 2: Sample collection preparation: the intelligent swab grabbing device in the sample collection management module grabs the swab and passes it to the user, and the swab positioning and guiding mechanism guides the user to prepare for sample collection through laser positioning and voice prompts; Step 3: Sample collection: Under the guidance of the swab positioning guide mechanism, the user accurately places the swab in the detection area for sample collection. The sample collection management module monitors the collection process in real time to ensure that the collected samples meet the quality requirements and transfers the collected samples to the detection and analysis module. Step 4: Detection and analysis: The detection and analysis module uses advanced molecular detection technology to quickly analyze the collected samples and obtain the test results under the premise of meeting the detection sensitivity and detection time requirements; Step 5: Result feedback and storage. The result feedback and storage module receives the detection results of the detection and analysis module, feeds back the results to the user and encrypts and stores the data.

7. The self-service sampling method for swab detection according to claim 6, characterized in that: In the identity identification process of step one, in addition to biometric identification and smart card identification, a mobile phone verification code verification link is added to improve the security of identity identification. When the user's identity identification information is inconsistent with the pre-stored information, a mobile phone verification code is sent for secondary verification to ensure the authenticity of the user's identity.

8. The self-service sampling method for swab detection according to claim 6, characterized in that: In the detection and analysis process of step four, parallel detection technology is used to divide the sample into multiple sub-samples for simultaneous detection. Suppose the detection efficiency is improved by a multiple of N. Through reasonable sample allocation and detection task scheduling, the detection efficiency is improved by a multiple of N ≥ 2, shortening the detection time and improving the detection efficiency.

9. The self-service sampling method for swab detection according to claim 6, characterized in that: In the sample collection preparation process of step 2, virtual reality VR technology is introduced to train users on sampling operations. VR simulates sampling scenes and operation processes. The user training effect evaluation index is set as E t , based on factors such as user operation accuracy and proficiency in VR simulation, when the user training effect evaluation index E t When the set standards are met, users can proceed with actual sample collection operations; In the result feedback and storage process of step five, data analysis and report generation functions are added to perform data analysis on the user's test results and generate a detailed test report. The report content includes test items, test results, and result interpretation information, and is provided to the user in the form of an electronic document.

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