Self-service body temperature measurement machine system

Abstract

The application discloses a self-service body temperature measuring machine system, which comprises a cloud platform, each body and a plurality of components arranged on each body; the plurality of components comprise an identity recognition unit, a space positioning guiding module, a body temperature measuring module, a controller, a communication module and a comprehensive information processing platform; the space positioning guiding module comprises a binocular stereo camera, an ultrasonic ranging sensor and a voice prompter, the controller generates each position correction information, and the voice prompter sends each voice instruction for reminding a user to move to an optimal temperature measuring area; the body temperature measuring module measures the body temperature of each user; and the cloud platform is used for receiving a fever crowd body temperature space-time distribution map of the comprehensive information processing platform and generating an early warning report. The self-service temperature measuring system integrates the functions of identity recognition, accurate temperature measurement, position calibration and intelligent analysis, and solves the problems of current manual temperature measurement, such as high labor cost, easy error, difficult data utilization and the incapability of existing automatic temperature measuring equipment in binding identity.

Description

Technical Field

[0001] This invention relates to the field of medical intelligent terminal technology, specifically to a self-service body temperature measurement system that integrates barcode recognition, non-contact temperature measurement, spatial positioning, and communication modules. It can be applied to automated body temperature screening, identity binding, and group health data statistical analysis in various public places such as hospitals, airports, and train stations. Background Technology

[0002] Body temperature monitoring, as the "first line of defense" for early screening of infectious diseases, has irreplaceable sentinel value in public health emergency prevention and control. Its core necessity lies in the fact that most respiratory infectious diseases (such as influenza and COVID-19) typically present with abnormal body temperature as a clinical symptom. Large-scale screening can enable the early detection and isolation of suspected cases, effectively blocking the transmission chain of pathogens in enclosed public places (such as hospitals, schools, and transportation hubs). Its deeper value lies not only in single-point screening but also in the ability, through continuous data accumulation, to outline the health status of a specific population, providing crucial data support for disease control departments to assess epidemic peaks and evaluate prevention and control policies. Therefore, body temperature monitoring is transforming from a single "screening tool" into a multi-dimensional "data entry point."

[0003] Currently, temperature monitoring in public places mainly relies on two technological approaches: one is the widely adopted manual handheld temperature measurement mode, where staff use forehead thermometers or infrared thermometers to measure the temperature of each person passing through, supplemented by manual record-keeping; the other is the deployment of fixed infrared thermal imagers in some high-traffic areas, which achieves rapid initial screening over a large area through non-contact methods and can visually display abnormal temperature points. From a technological evolution perspective, the market has begun to explore partial intelligent upgrades, such as combining temperature measurement modules with access control gates to achieve integrated "temperature measurement + passage" linkage, and some solutions are attempting to introduce facial recognition to verify identity.

[0004] Despite technological advancements, the current solution still suffers from the following problems: 1) Currently, temperature monitoring in public places mainly relies on manual operation: high labor costs, requiring dedicated personnel to use thermometers to check each person, consuming an average of 3-5 staff members per day (taking hospital outpatient clinics as an example); error risk, manual registration is prone to errors (e.g., ±0.2℃ error rate exceeds 8%, source: Clinical Medical Engineering 2023 statistics); data silos, measurement results are not electronically archived, making it impossible to form time-series statistical reports and difficult to conduct epidemic trend analysis.

[0005] 2) Existing automatic temperature measurement devices (such as fixed infrared thermal imagers) have insufficient performance: Although they can achieve non-contact temperature measurement, they generally lack patient identity binding mechanisms and cannot associate body temperature data with specific individuals; at the same time, they have not solved the problem of automatic calibration of the optimal temperature measurement distance / angle for individuals, which affects accuracy; and they also lack cloud data aggregation, processing and intelligent statistical analysis functions. Summary of the Invention

[0006] To address the aforementioned problems, the purpose of this invention is to propose a self-service body temperature measurement system. This system integrates functions such as identity recognition, accurate temperature measurement, location calibration, and intelligent analysis, solving the problems of current manual temperature measurement being labor-intensive, prone to errors, difficult to utilize data, and the inability of existing automatic temperature measurement devices to be linked to identities.

[0007] This was achieved through the following technical solutions: A self-service temperature measurement machine system includes a cloud platform, a frame for each self-service temperature measurement machine serving as a unit, and multiple components mounted on each unit. Each component on any unit includes an identity recognition unit, a spatial positioning guidance module, a temperature measurement module, a controller, a communication module, and a comprehensive information processing platform. On any unit, the identity recognition unit is used to input each user's personal information, which is then transmitted to the controller via the communication module. The spatial positioning guidance module includes a binocular stereo camera, an ultrasonic ranging sensor, and a voice prompt device. The binocular stereo camera is used to acquire first data for each user, and the ultrasonic ranging sensor is used to acquire second data for each user. Each first and second data point is transmitted via a communication module. The data is transmitted to the controller via the communication module. The controller generates position correction information for each position using the corresponding second data when any first data exceeds the preset optimal temperature measurement area. The voice prompt device receives the position correction information via the communication module and issues corresponding voice commands. Each voice command is used to remind each user to move to the optimal temperature measurement area. The body temperature measurement module is at the same height as the ultrasonic ranging sensor. The body temperature measurement module measures the body temperature of each user when they are in the optimal temperature measurement area. The integrated information processing platform receives each body temperature and generates a spatiotemporal distribution map of body temperature for people with fever. The cloud platform receives the spatiotemporal distribution map of body temperature for people with fever from the integrated information processing platform and generates a corresponding warning report.

[0008] Optionally, on any device, the identification unit includes a barcode scanner and a touchscreen. The barcode scanner is used to scan and obtain the user's personal information, while the touchscreen is used for the user to manually enter personal information. This provides both fast scanning and manual input modes, balancing efficiency and compatibility.

[0009] Optionally, it also includes an IoT box, which connects to both the cloud platform and each integrated information processing platform for transmitting the spatiotemporal distribution map of body temperature of people with fever. The IoT box enables secure remote data aggregation, supports unified monitoring of multiple devices, and effectively ensures transmission stability.

[0010] Optionally, on any device, any first data acquired by the binocular stereo camera includes the spatial position information of the user's head / forehead. After the controller identifies that the spatial position information of the user's head / forehead exceeds the optimal temperature measurement area, the ultrasonic ranging sensor acquires the corresponding second data for the user. The controller then compares the second data with the optimal temperature measurement area and generates corresponding position correction information. The controller then controls the voice prompt device to issue the voice command corresponding to the position correction information. The combination of visual coarse positioning and ultrasonic fine ranging makes the correction command more accurate; combined with voice guidance to encourage the user to actively adjust their position, the success rate of temperature measurement and user experience are greatly improved.

[0011] Optionally, on any subject, the process of acquiring any first data by the binocular stereo camera includes, in sequence: feature extraction, stereo matching, 3D reconstruction, and dynamic tracking.

[0012] Optionally, feature extraction includes: acquiring an image, extracting low-level features, and constructing a feature point set. Low-level features include corner points, edges, and textures. Stereo matching includes: matching each feature point in the corresponding feature point set of the image based on epipolar constraints and the disparity principle to obtain a disparity map. 3D reconstruction includes: converting the disparity map into corresponding 3D coordinates (X, Y, Z) using triangulation. X and Y correspond to two axes parallel to the ground, and the Z direction represents the depth value from the body temperature measurement module. Dynamic tracking includes: updating the 3D coordinates in real time using Kalman filtering or optical flow. By fusing multiple low-level features and epipolar constraints, the robustness of recognition in complex environments is enhanced. Kalman filtering / optical flow smooths the trajectory, eliminates jitter interference, and improves positioning accuracy.

[0013] Optionally, on any body, the process of the ultrasonic ranging sensor acquiring any second data includes: calculating the distance between the user's head / forehead and the ultrasonic ranging sensor using the pulse-echo method with ultrasound, and then weighted and fused the depth value with the distance value to obtain the corresponding second data. The pulse-echo method has high ranging accuracy and is not affected by lighting and color; by combining it with visual depth weighted fusion, the advantages of both are combined to obtain more reliable distance data.

[0014] Optionally, each unit is equipped with a vertical slide rail; each temperature measurement module and its corresponding ultrasonic ranging sensor are height-adjusted via a motor on the corresponding slide rail. Automatic height adjustment accommodates users of different heights, ensuring the temperature measurement point is always aligned with the forehead.

[0015] Optionally, each unit is equipped with two vertical slides: an adult slide and a children's slide. Each slide is equipped with a corresponding temperature measurement module and an ultrasonic ranging sensor. The maximum height of the adult slide is greater than that of the children's slide. After the user's personal information is entered into the identity recognition unit, the controller selects whether to use the adult or children's slide based on that information. This separation of adult and children's slides avoids the situation where a single slide's adjustment range is insufficient. Simultaneously, rapid switching based on identity prediction shortens waiting time and improves passage efficiency when measuring the temperature of multiple people.

[0016] Optionally, each unit is equipped with multiple body temperature measurement modules and multiple ultrasonic ranging sensors. Each body temperature measurement module and each ultrasonic ranging sensor of the same height form a measurement group, and each measurement group has a different height. After the user's personal information is entered into the identity recognition unit, the controller selects the corresponding measurement group based on the personal information. Multiple fixed-height sensors eliminate the need for motor adjustment, resulting in faster response, higher reliability, and accurate matching of the user's height.

[0017] The beneficial effects of this invention compared to the prior art are: The technical solutions of this invention: 1) Significantly improve efficiency and reduce labor costs: Enables fully self-service operation, effectively reducing the tedious process and manpower requirements of manual operation; 2) Ensure measurement accuracy: Through spatial positioning technology and distance triggering mechanism using binocular vision + ultrasound fusion, ensures that the patient is in the optimal temperature measurement position, reducing temperature measurement errors; 3) Achieve intelligent statistical analysis and early warning: Quickly bind identity, time, and location information and upload it to the cloud platform to achieve electronic and structured data storage, supporting the automatic generation of spatiotemporal heat maps and periodic abnormal body temperature statistical analysis reports, providing data support for epidemic monitoring and resource allocation; 4) Effectively prevent contact infection: The entire process can be self-service operated by the patient, without the need for close contact with staff, reducing the risk of cross-infection. Attached Figure Description

[0018] Figure 1 A schematic diagram of an adult self-service body temperature measurement machine with multiple fixed-height body temperature measurement modules; Figure 2 A schematic diagram of an adult self-service body temperature measurement machine with a single liftable body temperature measurement module and a first slide rail; Figure 3 A schematic diagram of a self-service body temperature measurement machine for children with multiple fixed-height body temperature measurement modules; Figure 4 A schematic diagram of a child self-service body temperature measurement machine with a single liftable body temperature measurement module and a second slide. Figure 5 A schematic diagram of a self-service body temperature measurement machine for both adults and children, featuring multiple fixed-height body temperature measurement modules. Figure 6 A schematic diagram of a self-service body temperature measurement machine for both adults and children, featuring two adjustable body temperature measurement modules and first and second slides 13. Figure 7 A schematic diagram of a self-service temperature measurement machine for infants and young children, designed to set up a temperature measurement platform.

[0019] Figure 8 This diagram illustrates how the communication module transmits data packets to the integrated information processing platform, and how the integrated information processing platform sends the generated information to the cloud platform via an IoT box.

[0020] Reference numerals: 1 Body, 2 Barcode Scanner, 3 Touch Screen, 4 Voice Prompt, 5 Binocular Stereo Camera, 6 Controller, 7 IoT Box, 8 Body Temperature Measurement Module, 9 Ultrasonic Ranging Sensor, 10 Communication Module, 11 Integrated Information Processing Platform, 12 First Slide, 13 Second Slide, 14 Temperature Measurement Platform, 15 Cloud Platform. Detailed Implementation

[0021] The following will be combined with the present invention Figures 1 to 8 The technical solutions in the embodiments of the present invention will be described in detail below.

[0022] A self-service body temperature measurement system specifically includes a cloud platform 15, a frame for each self-service body temperature measurement machine (each body 1), and multiple components mounted on each body 1. For any body 1, the multiple components include: an identity recognition unit, a spatial positioning guidance module, a body temperature measurement module 8, a controller 6, a communication module 10, and a comprehensive information processing platform 11. The cloud platform 15 collects data from each comprehensive information processing platform 11 in a coordinated manner, enabling holistic intelligent analysis.

[0023] In this embodiment, the identity recognition unit is used to input each user's personal information, which is then transmitted to the controller 6 via the communication module 10. The controller 6 is used for data processing and controlling the operation of other components to ensure stable system operation. The identity recognition unit includes a barcode scanner 2 and a touchscreen 3. The barcode scanner 2 is used to scan medical barcodes, ID cards, or health codes to obtain the user's personal information, such as age and height. The touchscreen 3 supports manual input of personal information by the user, thus achieving a dual mode of fast barcode scanning and manual input, balancing efficiency and compatibility. Simultaneously, the display screen can also provide visual guidance. For example, when the controller 6 determines that the user has deviated from the preset optimal temperature measurement area, the display screen shows the corresponding location and distance, or displays an arrow indicating the direction the user needs to move for visual guidance.

[0024] In this embodiment, the spatial positioning guidance module includes a binocular stereo camera 5, an ultrasonic ranging sensor 9, and a voice prompt device 4. The binocular stereo camera 5 is used to acquire first data for each user, including the spatial position information of the user's head / forehead, and to initially determine the user's distance and orientation from the system. When acquiring any first data, the process includes, in sequence: feature extraction, stereo matching, 3D reconstruction, and dynamic tracking. Feature extraction includes: acquiring (head / forehead) images, extracting low-level features (using known algorithms such as SIFT or ORB), and constructing a feature point set. The low-level features include corner points, edges, and textures. Stereo matching includes: matching each feature point in the feature point set corresponding to the image based on epipolar constraints and the disparity principle to obtain a disparity map. 3D reconstruction includes: based on the disparity map, converting the disparity in the disparity map into corresponding 3D coordinates (X, Y, Z) using triangulation (the actual calibration parameters of the binocular stereo camera 5, such as focal length, baseline distance, and distortion coefficient, are known). X and Y correspond to two axes parallel to the ground, and the directions of X and Y can be selected by the user. The direction of Z is the depth value from the body temperature measurement module 8. The coordinate origin is the combination of the center point of the infrared temperature sensor in the body temperature measurement module 8 (Z-axis origin) and the projection point (X / Y-axis origin) of the midpoint of the line connecting the optical centers of the two cameras built into the binocular stereo camera 5 onto the horizontal plane. Dynamic tracking includes real-time updates of the three-dimensional coordinates using Kalman filtering or optical flow methods to compensate for motion blur or attitude changes. The fusion of multiple low-level features and epipolar constraints enhances robustness in complex environments. Kalman filtering / optical flow smooths the trajectory, eliminating jitter interference and improving positioning accuracy.

[0025] The ultrasonic ranging sensor 9 calculates the distance between the user's head / forehead and the ultrasonic ranging sensor 9 using the pulse-echo method. The depth value and the distance value are then weighted and fused to obtain the corresponding second data. Each first and second data point is transmitted to the controller 6 via the communication module 10. When any first data point exceeds the preset optimal temperature measurement area (i.e., the spatial position of the user's head / forehead is detected to be outside the optimal temperature measurement area), the controller 6 generates position correction information using the corresponding second data. This position correction information includes orientation and distance data. Then, the controller 6, via the communication module 10, controls the voice prompt device 4 to receive each position correction information and issue corresponding voice commands. Each voice command reminds the user to move to the optimal temperature measurement area (e.g., setting the distance to the temperature measurement module 8 / ultrasonic ranging sensor 9 to be between 30-50mm). The combination of the binocular stereo camera 5 and the ultrasonic ranging sensor 9 achieves a combination of visual coarse positioning and ultrasonic fine ranging, resulting in more accurate correction commands. Combined with voice guidance to encourage users to actively adjust their position, this significantly improves the success rate of temperature measurement and the user experience.

[0026] After obtaining the three-dimensional coordinates (X, Y, Z), where the Z-axis direction represents the depth value from the body temperature measurement module 8, it can be denoted as D. vision Meanwhile, the ranging value measured by the ultrasonic ranging sensor 9 is recorded as D. ultra The following is about D. vision and D ultra Perform weighted fusion calculation.

[0027] Before weighted fusion, based on the inherent accuracy characteristics of binocular visual positioning and ultrasonic ranging, different weights need to be assigned to the two data points. Since ultrasonic ranging has higher accuracy at close range (in actual human body temperature measurement scenarios), while binocular visual positioning is easily affected by factors such as lighting and occlusion in actual temperature measurement scenarios, its accuracy may decrease. Therefore, we can denote D as... vision The corresponding weight is w vision D ultra The corresponding weight is w ultra w vision <w ultra And satisfy w vision +w ultra =1. (In addition, the weights of the two can be dynamically adjusted according to the actual scenario and sensor performance.) Then, using the assigned weights, the depth value D is... vision and distance measurement value D ultra Perform weighted fusion to calculate the final distance value D. final The weighted fusion formula is: D final =w vision ×D vision +w ultra ×D ultra To further eliminate noise interference and improve the stability and accuracy of distance values, the weighted fused distance value D can be further optimized. final Filtering processes, such as using the Kalman filter algorithm, can be employed to suppress noise and improve measurement accuracy.

[0028] The optimal temperature measurement area is [30mm, 50mm]. Controller 6 continuously monitors the weighted fused D... final If D finalIf the temperature falls within the specified range, it is considered to be in the "optimal position" of the optimal temperature measurement area; otherwise, adjustment logic is triggered. Based on the difference between the distance value and the target range, the direction and distance the user needs to move are determined (e.g., moving 10 centimeters due north). The user is then guided to the optimal temperature measurement position via voice prompts 4 or the touchscreen 3. When the user's position meets the optimal temperature measurement conditions multiple times consecutively, the current position is locked and the temperature measurement program is started. After the temperature measurement is completed, each data point generated during the temperature measurement and its corresponding timestamp can be encrypted in data packet form via the communication module 10 before being transmitted to the corresponding integrated information processing platform 11.

[0029] It should be noted that the pulse-echo method has high ranging accuracy and is not affected by lighting or color. It can be achieved by emitting high-frequency ultrasonic waves through the ultrasonic ranging sensor 9 and receiving the reflected signal. The distance from the user's head / forehead to the body temperature measurement module 88 / ultrasonic ranging sensor 9 is calculated by the time of flight. During weighted fusion, Kalman filtering can be used to eliminate the scale error of visual positioning and the noise interference of ultrasonic waves, and generate the final distance value as the second data.

[0030] In this embodiment, the system also includes an IoT box 7, which is connected to the cloud platform 15 and each integrated information processing platform 11 to support data transmission. The integrated information processing platform 11 receives each body temperature and generates a spatiotemporal distribution map of body temperature for people with fever. It can also store data or information generated by other components. The spatiotemporal distribution map of body temperature for people with fever can be automatically statistically analyzed on a daily / weekly / monthly basis, and then transmitted to the cloud platform 15 via the IoT box 7 to generate corresponding early warning reports. For example, it can output an early warning report for abnormal body temperature (≥37.3℃) and identify a clustered fever trend (e.g., the number of people with abnormal body temperature in area A of the outpatient hall corresponding to a certain self-service temperature measurement machine increased by 15% week-on-week).

[0031] In this embodiment, the operation of the system may include the following triggering logic: state-level triggering, dynamic voice guidance, closed-loop feedback mechanism, and exception handling design.

[0032] The status-based triggering includes: Level 1 trigger (distance abnormality), which means that when the first data is <30mm or >50mm, the voice prompt device 4 is activated; Level 2 trigger (continuous abnormality), which means that if the patient does not respond to the prompt, the prompt is repeated after 3 seconds and the volume is increased; if no adjustment is made after 5 seconds, it enters sleep mode to avoid false triggering; Level 3 trigger (safety threshold), which means that when the first data is <5mm (possibly due to the user touching the body temperature measurement module 8), the emergency stop procedure is triggered, the temperature measurement function is turned off and an alarm is triggered.

[0033] Dynamic voice guidance includes: direction judgment, which calculates the adjustment direction (e.g., forward / backward) and distance (e.g., "Please move backward 3 cm") based on the difference between the first data and the optimal temperature measurement area; multimodal prompts, which generate graded voice commands based on the difference, for example, if the distance is <30mm, then "Please move backward X cm to avoid affecting the temperature measurement accuracy if too close", if the distance is >50mm, then "Please move forward Y cm to ensure effective coverage of the temperature measurement module", if the distance is ∈ [30,50], then "The position is appropriate, start temperature measurement"; and visual assistance, which is that the touch screen 3 displays arrows to help the patient understand the direction of movement.

[0034] The closed-loop feedback mechanism includes: real-time monitoring, that is, after the user adjusts the position, the binocular stereo camera 5 and the ultrasonic ranging sensor 9 immediately resample and update the data; state locking, that is, when the first data of 3 consecutive samples is ∈ [30,50], the current position is locked and the temperature measurement program is started. If the deviation occurs again within 3 times, the guidance logic is retried; timeout handling, that is, if the user does not enter the optimal temperature measurement area within 20 seconds, the system automatically goes into sleep mode and prompts "Please restart the temperature measurement process".

[0035] The anomaly handling design includes: sensor redundancy, meaning that if either the stereo camera 5 or the ultrasonic ranging sensor 9 fails, the system switches to the other sensor and prompts for maintenance; anti-interference algorithms, such as using median filtering to process ultrasonic noise and using the RANSAC algorithm to remove outliers in the images from the stereo camera 5. Furthermore, user behavior learning can be implemented, for example, analyzing patient movement patterns using machine learning models (such as SVM) to optimize prompting strategies (e.g., using shorter instructions for children).

[0036] like Figure 1 The diagram shows a self-service temperature measurement machine for adults with multiple fixed-height temperature measurement modules 8. To accommodate differences in adult height, multiple measurement groups are fixedly installed at different heights on the front of the main body 1 (the side facing the user). Each measurement group has a different height (e.g., corresponding to 1.5m, 1.6m, 1.7m, and 1.8m respectively). The temperature measurement module 8 and the ultrasonic ranging sensor 9 in any measurement group are kept at the same height and on the same surface, both facing the user simultaneously for measurement. Each temperature measurement module 8 includes its own infrared temperature sensor. During operation, the binocular stereo camera 5 identifies the patient's head height. When it finds the optimal temperature measurement area, the controller 6 selects and activates the temperature measurement module 8 that best matches that height. In addition, if the user's personal information includes specific height data, the controller 6 can also directly select the corresponding height measurement group based on the height data. The voice prompt 4 and the touch screen 3 guide the patient to fine-tune their position to the optimal measurement area, triggering the temperature measurement module 8 to perform temperature measurement.

[0037] like Figure 2 The diagram shows a self-service temperature measurement machine for adults, which is equipped with a single height-adjustable temperature measurement module 8 and a first slide rail 12. A vertical first slide rail 12 (adult slide rail) can be set on each body 1. The binocular stereo camera 5 captures images of the patient's head / forehead and sends them to the controller 6 to determine whether the captured content has been successfully identified as the user's head / forehead. If it is incorrect, the controller 6 adjusts the height of the measurement group on the corresponding first slide rail 12 through the motor, so that it can automatically raise and lower to adapt to users of different heights and ensure that the temperature measurement point is always aligned with the user's head / forehead.

[0038] like Figure 3 The image shown is a schematic diagram of a child self-service temperature measurement machine with multiple fixed-height temperature measurement modules 8. Figure 3 Mainly in Figure 1 Based on this, the height of each measurement group has been reduced (e.g., 1.0m, 1.1m, 1.2m, 1.3m) to better suit the usage scenarios of children.

[0039] like Figure 4 The diagram shown is a schematic of a child self-service temperature measurement machine with a single liftable temperature measurement module 8 and a second slide rail 13. Figure 4 Mainly in Figure 2 Based on the previous version, the position and height of the slides have been modified. The second slide, 13, is the children's slide, and the height range is set according to the height of children.

[0040] like Figure 5 The diagram shows a self-service body temperature measurement machine suitable for both adults and children, equipped with multiple fixed-height body temperature measurement modules 8. Multiple measurement groups for adults and multiple measurement groups for children can be installed simultaneously on any one of the main bodies 1. The binocular stereo camera 5 and the controller 6 first determine whether the user is an adult or a child. Then, the controller 6 selects and activates the optimal body temperature measurement module 8 from the corresponding height group to perform temperature measurement.

[0041] like Figure 6 The diagram shows a self-service body temperature measurement machine for both adults and children, equipped with two adjustable body temperature measurement modules 8 and a first slide rail 12 and a second slide rail 13. Figure 6 Two vertical slides are installed on each of the two main bodies 1, and each slide has a corresponding measurement group. The measurement groups of the two slides can be raised and lowered independently. The maximum height of the adult slide is greater than that of the child slide. After the user's personal information is entered into the identity recognition unit, the controller 6 selects to use the adult slide or the child slide based on the personal information or the image from the binocular stereo camera 5. Adult and child slides are adapted separately to avoid the situation where the adjustment range of a single slide is insufficient. At the same time, the controller can quickly switch according to the identity prediction, shorten the waiting time, and improve the passage efficiency when measuring the temperature of multiple people.

[0042] like Figure 7 The diagram shown is a schematic of a self-service temperature measurement machine for infants and young children with a temperature measurement platform 14. Figure 7 It is mainly designed for infants and young children who cannot stand on their own. A temperature measuring platform 14 (such as a flat plate with a soft pad) is set on the main body 1. The infant or young child is placed on the temperature measuring platform 14 by a family member in a supine or side-lying position, and then the position of the infant or young child's forehead is identified by a binocular stereo camera 5.

[0043] like Figure 8 The diagram shows the communication module 10 transmitting data packets to the integrated information processing platform 11 and the integrated information processing platform 11 sending the generated information to the cloud platform 15 through the IoT box 7. Figure 8 The communication module 10 shown uses 5G communication, which can provide higher bandwidth and lower latency wireless connection, ensuring fast and reliable data transmission with the integrated information processing platform 11 in densely populated places or when real-time transmission of high-definition positioning data and video auxiliary information is required (if added).

[0044] In summary, this invention enables fully automated operation, effectively reducing the tedious process and manpower requirements of manual operation: Through spatial positioning technology combining binocular vision and ultrasound, and a distance triggering mechanism, it ensures the patient is in the optimal temperature measurement position, reducing measurement errors and guaranteeing accuracy; it quickly binds identity, time, and location information to the cloud platform, achieving electronic and structured data storage, supporting the automatic generation of spatiotemporal heat maps and periodic abnormal body temperature statistical analysis reports, providing data support for epidemic monitoring and resource allocation; it also supports fully self-service operation by patients, eliminating the need for close contact with staff, reducing the risk of cross-infection, and demonstrating significant advancements.

[0045] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A self-service body temperature measurement machine system, characterized in that, It includes a cloud platform (15), a frame for each self-service body temperature measurement machine used as each body (1), and multiple components set on each body (1); the multiple components on any body (1) include an identity recognition unit, a spatial positioning guidance module, a body temperature measurement module (8), a controller (6), a communication module (10), and an integrated information processing platform (11). On any body (1), the identity recognition unit is used to record the personal information of each user and then transmit it to the controller (6) through the communication module (10); the spatial positioning guidance module includes a binocular stereo camera (5), an ultrasonic ranging sensor (9) and a voice prompt (4). The binocular stereo camera (5) is used to acquire the first data of each user, and the ultrasonic ranging sensor (9) is used to acquire the second data of each user. Each first data and each second data are transmitted to the controller (6) through the communication module (10). The controller (6) is used to generate each position correction information using the corresponding second data when any first data exceeds the preset optimal temperature measurement area. The voice prompt (4) receives each position correction information through the communication module (10) and issues each corresponding voice command. Each voice command is used to remind each user to move to the optimal temperature measurement area; the body temperature measurement module (8) is at the same height as the ultrasonic ranging sensor (9). The body temperature measurement module (8) is used to measure the body temperature of each user when each user is in the optimal temperature measurement area; the integrated information processing platform (11) is used to receive each body temperature and generate a spatiotemporal distribution map of body temperature of people with fever. The cloud platform (15) is used to receive the spatiotemporal distribution map of feverish populations from each integrated information processing platform (11) and generate a corresponding early warning report.

2. The self-service body temperature measurement machine system according to claim 1, characterized in that, On any body (1), the identity recognition unit includes a barcode scanner (2) and a touch screen (3). The barcode scanner (2) is used to scan and obtain the user's personal information, and the touch screen (3) is used for the user to manually input personal information.

3. The self-service body temperature measurement machine system according to claim 1, characterized in that, It also includes an Internet of Things (IoT) box (7), which is connected to the cloud platform (15) and each integrated information processing platform (11) respectively, for transmitting the spatiotemporal distribution map of body temperature of people with fever.

4. The self-service body temperature measurement machine system according to claim 1, characterized in that, On any body (1), any first data acquired by the binocular stereo camera (5) includes the spatial position information of the user's head / forehead; after the controller (6) identifies that the spatial position information of the user's head / forehead exceeds the optimal temperature measurement area, the ultrasonic ranging sensor (9) acquires the corresponding second data of the user, and the controller (6) compares the second data with the optimal temperature measurement area and generates the corresponding position correction information, and then the controller (6) controls the voice prompt device (4) to issue the voice command corresponding to the position correction information.

5. A self-service body temperature measurement machine system according to claim 1, characterized in that, On any ontology (1), the process of the binocular stereo camera (5) acquiring any first data includes, in sequence: feature extraction, stereo matching, three-dimensional reconstruction and dynamic tracking.

6. The self-service body temperature measurement machine system according to claim 5, characterized in that, Feature extraction includes: acquiring images, extracting low-level features, and constructing a feature point set. Low-level features include corner points, edges, and textures. Stereo matching includes: matching each feature point of the corresponding feature point set of the image based on epipolar constraints and the principle of disparity to obtain a disparity map. Three-dimensional reconstruction includes: converting the disparity map into corresponding three-dimensional coordinates (X, Y, Z) using triangulation. X and Y correspond to two axes parallel to the ground, and the direction of Z is the depth value of the distance from the body temperature measurement module (8). Dynamic tracking includes: updating the three-dimensional coordinates in real time using Kalman filtering or optical flow.

7. A self-service body temperature measurement machine system according to claim 6, characterized in that, On any body (1), the process of the ultrasonic ranging sensor (9) acquiring any second data includes: calculating the distance value between the user's head / forehead and the ultrasonic ranging sensor (9) using the pulse echo method with ultrasonic waves, and then weighting and fusing the depth value and the distance value to obtain the corresponding second data.

8. A self-service body temperature measurement machine system according to claim 1, characterized in that, Each body (1) is equipped with a vertical slide; any body temperature measurement module (8) and the corresponding ultrasonic ranging sensor (9) are adjusted in height on the corresponding slide by a motor.

9. A self-service body temperature measurement machine system according to claim 1, characterized in that, Each body (1) is equipped with two vertical slides, namely an adult slide and a children's slide. Each slide is equipped with a corresponding body temperature measurement module (8) and an ultrasonic ranging sensor (9). The maximum height of the adult slide is greater than that of the children's slide. After the user's personal information is entered into the identity recognition unit, the controller (6) selects to use the adult slide or the children's slide based on the personal information.

10. A self-service body temperature measurement machine system according to claim 1, characterized in that, Multiple body temperature measurement modules (8) and multiple ultrasonic ranging sensors (9) are set on any body (1). Each body temperature measurement module (8) and each ultrasonic ranging sensor (9) of the same height form a measurement group. The height of each measurement group is different. After the user's personal information is entered into the identity recognition unit, the controller (6) selects the corresponding measurement group based on the personal information.

Images