Temperature detection method and device based on portable temperature measuring device

Abstract

The application discloses a temperature detection method and device based on a portable temperature measuring device, relates to the technical field of detection, and mainly aims to solve the problem that the existing temperature measurement cannot meet flexible temperature measurement requirements. The method comprises the following steps: sending a connection instruction to an Internet of Things platform through a preset integrated networking protocol; after a connection with the Internet of Things platform is established, acquiring temperature data and distance data collected by a temperature sensor and a distance sensor in the portable temperature measuring device respectively and a correction parameter, wherein the correction parameter is used for representing an influence factor of a mapping relationship between the temperature data and the distance data; based on the mapping relationship between the temperature and the distance, the temperature data and the distance data are fused and processed to determine a compensation value of the temperature data; and based on a trained temperature compensation processing model, the compensation value, the temperature data and the distance data are detected to determine a detected target temperature value.

Description

Technical Field

[0001] This invention relates to the field of detection technology, and in particular to a temperature detection method and apparatus based on a portable temperature measuring device. Background Technology

[0002] With the rapid development of electronic technology, portable temperature measuring devices can meet the needs of various scenarios that require rapid and convenient temperature measurement. For example, staff at indoor entrances can use portable temperature measuring devices to detect the temperature of people entering the room.

[0003] Currently, existing portable temperature measuring devices require a specified distance from a specific location on the body to ensure accurate temperature detection. However, for handheld portable temperature measuring devices, inaccurate distances often lead to measurement errors during testing, resulting in poor temperature measurement accuracy and inaccurate results, and failing to meet the needs for processing the measured temperature data. Summary of the Invention

[0004] In view of this, the present invention provides a temperature detection method and apparatus based on a portable temperature measuring device, the main purpose of which is to solve the problem that existing methods cannot meet the needs of flexible temperature measurement.

[0005] According to one aspect of the present invention, a temperature detection method based on a portable temperature measuring device is provided, comprising:

[0006] By using a preset integrated networking protocol, a connection instruction is sent to the Internet of Things (IoT) platform so that the terminal device connected to the IoT platform can record data collected by at least two portable temperature measuring devices.

[0007] After establishing a connection with the IoT platform, the temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device are obtained. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data.

[0008] Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine the compensation value of the temperature data.

[0009] The temperature compensation processing model, which has been trained, is used to detect and process the compensation value, the temperature data, and the distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters.

[0010] According to another aspect of the present invention, a temperature detection device based on a portable temperature measuring device is provided, comprising:

[0011] The sending module is used to send a connection instruction to the Internet of Things (IoT) platform through a preset integrated networking protocol, so that the terminal device connected to the IoT platform records data collected by at least two portable temperature measuring devices;

[0012] The acquisition module is used to acquire temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device after establishing a connection with the IoT platform. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data.

[0013] The first determining module is used to perform fusion processing on the temperature data and distance data based on the mapping relationship between temperature and distance, and determine the compensation value of the temperature data.

[0014] The second determining module is used to perform detection processing on the compensation value, the temperature data, and the distance data based on the temperature compensation processing model that has been trained, and to determine the target temperature value to be detected. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters.

[0015] According to another aspect of the present invention, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the temperature detection method based on the portable temperature measuring device described above.

[0016] According to another aspect of the present invention, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0017] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the temperature detection method based on the portable temperature measuring device described above.

[0018] By employing the above-described technical solutions, the technical solutions provided by the embodiments of the present invention have at least the following advantages:

[0019] This invention provides a temperature detection method and apparatus based on portable temperature measuring devices. Compared with existing technologies, this invention sends a connection instruction to an IoT platform via a preset integrated networking protocol, enabling terminal devices connected to the IoT platform to record data collected by at least two portable temperature measuring devices. After establishing a connection with the IoT platform, it acquires temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring devices, respectively. The correction parameters characterize the influencing factors affecting the mapping relationship between the temperature data and the distance data. Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine a compensation value for the temperature data. A pre-trained temperature compensation processing model is used to detect and process the compensation value, temperature data, and distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing model weights based on the correction parameters, avoiding inaccurate temperature detection due to distance errors during testing, improving the accuracy of temperature measurement, and achieving a more quantifiable temperature detection and display effect, greatly satisfying the need for processing measured temperature data.

[0020] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0021] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0022] Figure 1 A flowchart of a temperature detection method based on a portable temperature measuring device provided by an embodiment of the present invention is shown;

[0023] Figure 2 This diagram illustrates a detection method based on a portable temperature measuring device according to an embodiment of the present invention.

[0024] Figure 3 This diagram illustrates a data communication method for an Internet of Things (IoT) platform according to an embodiment of the present invention.

[0025] Figure 4 This diagram illustrates a block diagram of a temperature detection device based on a portable temperature measuring device according to an embodiment of the present invention.

[0026] Figure 5A schematic diagram of the structure of a terminal provided in an embodiment of the present invention is shown. Detailed Implementation

[0027] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0028] This invention provides a temperature detection method based on a portable temperature measuring device, such as... Figure 1 As shown, the method includes:

[0029] 101. Send a connection instruction to the IoT platform through a preset integrated networking protocol.

[0030] The temperature detection method in this embodiment of the invention is based on a system comprising an Internet of Things (IoT) platform, terminal devices connected to at least two portable temperature measuring devices, a client, and a currently executing server. Each terminal device acquires temperature data from different users based on the two connected portable temperature measuring devices. An integrated networking protocol is pre-built to ensure the IoT platform can store all data collected by the terminal devices and the address information of each terminal device, and data communication connections are established to obtain relevant data. Specifically, when it is necessary to determine the temperature of a target user, the server, acting as the current executing entity, sends a connection instruction to the IoT platform through the pre-defined integrated networking protocol, enabling the terminal devices connected to the IoT platform to record data collected by at least two portable temperature measuring devices. Specifically, the two portable temperature measuring devices are handheld or stand-mounted body temperature measuring devices, such as thermometers. In this embodiment, every two portable temperature measuring devices are connected to one terminal device and installed or placed in locations where the temperature of a large number of people needs to be detected. The two portable temperature measuring devices are placed facing each other at a 45-degree angle to simultaneously detect the temperature of one user. In addition, both portable temperature measuring devices are equipped with distance sensors to detect the distance between the user and the device during temperature measurement. Generally, since the user will be relatively close to one of the devices during measurement, the corresponding distance data will be two different distance values. Of course, there are also cases where the two distance values ​​are equal, such as... Figure 2 The schematic diagram of the portable temperature measuring device shown is not specifically limited in the embodiments of the present invention.

[0031] It should be noted that each terminal device stores a large amount of user temperature data according to time, location, and other ranges. In order for the current server to obtain the temperature and distance data collected by the corresponding terminal devices in each location, the terminal devices send all collected data to the Internet of Things (IoT) for backup based on a preset integrated networking protocol. The preset integrated networking protocol is a pre-determined data communication protocol for transmission between the IoT platform and terminal devices, and between the IoT platform and the current server; this embodiment of the invention does not impose specific limitations on it. The IoT cloud platform refers to a platform that can receive data reported by devices, send data to devices, forward, analyze, calculate, display, and manage the data.

[0032] 102. After establishing a connection with the IoT platform, acquire the temperature data, distance data, and calibration parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device.

[0033] In embodiments of the present invention, such as Figure 3 The diagram illustrates data communication on an IoT platform. After establishing a connection, the current server transmits data with the IoT platform to acquire temperature data, distance data, and correction parameters from various portable temperature measuring devices. The correction parameters characterize the influencing factor affecting the mapping relationship between the temperature data and the distance data. That is, there is a mapping relationship between each temperature data and its corresponding distance data. When different portable temperature measuring devices determine compensation values ​​based on this mapping relationship for the collected temperature and distance data, an influencing factor is needed as the correction content for the hardware device; this is the correction parameter. In this embodiment, the correction parameters are determined according to the model, usage time, manufacturer, and acceptable error range of the portable temperature measuring device. The numerical range of the correction parameters is configured as 0-1. Different portable temperature measuring devices correspond to different correction parameters; this embodiment does not impose specific limitations.

[0034] It should be noted that, since the temperature detection scenario in this embodiment of the invention is a location with a large flow of people, it is not necessary to identify each user in this embodiment of the invention. Instead, the temperature data, distance data, and corresponding correction parameters collected by all portable temperature measuring devices are obtained to calculate the individual temperature data.

[0035] 103. Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine the compensation value of the temperature data.

[0036] In this embodiment of the invention, since the temperature detected by the user varies at different locations, it is necessary to compensate for the temperature data based on distance. The compensation data serves as an input parameter to the temperature compensation processing model, used to define or assist in calculating the actual user body temperature corresponding to different on-site temperatures and detection distances. Specifically, since greater distances result in larger errors in temperature detection, a mapping relationship between temperature and distance is pre-established to fuse temperature and distance data to obtain the compensation value. This mapping relationship follows a correspondence that the greater the distance, the lower the temperature, and the temperature and distance are fused accordingly.

[0037] It should be noted that, in this embodiment of the invention, the temperature-distance fusion formula is used for fusion, and the temperature-distance fusion formula is Y = -0.01X. 2 +0.02X+b; where X is the difference between the two distance sensors and the detected target, and b is the temperature data detected by the temperature sensor at the corresponding distance.

[0038] 104. Based on the temperature compensation processing model that has been trained, the compensation value, the temperature data, and the distance data are processed to determine the target temperature value.

[0039] In this embodiment of the invention, a temperature compensation processing model is pre-built and trained. The compensation value, temperature data, and distance data are used as model parameters for model calculation to obtain the user's actual body temperature value in the location, i.e., the target temperature value. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters, thereby completing the improvement and training of the temperature compensation processing model.

[0040] In one embodiment of the present invention, for further explanation and limitation, after determining the target temperature value to be detected, the method further includes: determining the location information of the portable temperature device according to a global positioning system or a preset location identifier; statistically analyzing the associated target temperature values ​​corresponding to the associated portable temperature measuring devices within a preset time range that are within a preset detection range of the location information, wherein the associated temperature data is determined based on the associated temperature data and associated distance data collected by the associated temperature sensor and associated distance sensor corresponding to the associated portable temperature measuring device in the Internet of Things platform, respectively; and if the associated target temperature value is greater than an abnormal temperature index, sending an alarm message corresponding to the location information.

[0041] To monitor the detection of abnormal body temperatures in various locations in real time, after determining the target temperature value, the location of each portable temperature measuring device is determined. This can be done using a Global Positioning System (GPS) to locate portable temperature measuring devices with individual identifiers, or by determining the location information of portable temperature measuring devices based on pre-marked locations; this embodiment of the invention does not impose specific limitations. Furthermore, since portable temperature measuring devices can be deployed in various locations, other portable temperature measuring devices with a certain detection range related to the currently determined location information can be identified as associated portable temperature measuring devices. Simultaneously, the associated portable temperature measuring devices collect the associated target temperature value determined by the associated question and answer process according to steps 101-104, which serves as the accurate value of the body temperature detected by the associated portable temperature measuring device. Further, to achieve location-based alarms based on temperature anomalies, the comparison relationship between the associated target temperature value and the abnormal temperature index is determined. If the value is greater than the abnormal temperature index, an alarm message is sent based on the determined location information, thereby alerting that this location also has a risk of abnormal temperature. For example, after determining the location information 11 of portable temperature measuring device a, the associated target temperature value of the associated portable temperature measuring device b belonging to the same community is uniformly determined within a week. If the associated target temperature value is greater than 37.2 degrees, an alarm message is sent to the location information 11.

[0042] In one embodiment of the present invention, for further explanation and limitation, after statistically analyzing the associated target temperature values ​​corresponding to the portable temperature measuring devices whose location information belongs to the preset detection range within the preset time range, the method further includes: detecting whether the client has enabled data sharing permission with the Internet of Things platform; if the client has enabled the data sharing permission, generating a temperature status distribution map based on the associated target temperature values, and outputting the associated target temperature values ​​and the temperature status distribution map to the client; if the client has not enabled the data sharing permission, outputting a request command for the target temperature values ​​and the temperature status distribution map to generate the temperature status distribution map.

[0043] To facilitate temperature monitoring in different locations, after determining the associated target temperature value, the system checks whether the client has enabled data sharing permissions on the IoT platform. Data sharing permissions restrict client users to accessing associated temperature data obtained from associated portable temperature measuring devices within a preset detection range. To improve the visualization of temperature data, a temperature status distribution map is generated based on the associated target temperature value. This map displays all associated target temperature values ​​within the preset detection range, and different colors can be used to render different temperature ranges, thus better illustrating the temperature status distribution. This output is only possible if data analysis permissions are enabled. If the client connected to the current server does not have sharing permissions enabled, it means the client cannot obtain the associated target temperature value and the temperature status distribution map. Therefore, the current server directly outputs the target temperature value and a request command to the client to enable permissions, thereby generating the temperature status distribution map.

[0044] In one embodiment of the present invention, for further explanation and limitation, the step of generating a temperature state distribution map based on the associated target temperature value includes: loading the detection count and location information of the associated portable temperature measuring device from the Internet of Things platform; calculating the average temperature based on the determined associated target temperature value and the detection count; marking the average temperature on the detection map information drawn based on the location information to obtain a temperature state distribution map, wherein the average temperature is updated based on a preset detection count and / or a preset detection time.

[0045] Since the IoT platform stores the detection count and location information recorded by each terminal device, the temperature distribution map is generated by loading data from the IoT platform. The average temperature is then calculated based on the associated target temperature value and the number of detections; that is, the summation is divided by the number of detections to obtain the average temperature. Simultaneously, a detection map is drawn based on the location information, and the average temperature is marked on the map, thus obtaining the temperature distribution map. To achieve real-time temperature detection, the average temperature is updated according to a preset number of detections or a preset detection time. For example, the average temperature is recalculated after 5 detections or after 1 day of detection; this embodiment of the invention does not impose specific limitations.

[0046] In one embodiment of the present invention, for further explanation and limitation, before marking the average temperature on the detection map information drawn based on the location information to obtain the temperature state distribution map, the method further includes: if the associated target temperature value is greater than the abnormal temperature index, it is determined to be an abnormal temperature state, and the location information of the associated portable temperature measuring device corresponding to the abnormal temperature state is abnormally rendered and marked on the temperature state distribution map.

[0047] If the associated target temperature value is greater than the abnormal temperature index, it indicates that an abnormal temperature has occurred at the location of the associated portable temperature measuring device. Therefore, the location of the associated portable temperature measuring device, identified as having an abnormal temperature state, is highlighted in red and marked on the temperature status distribution map. In this case, it is no longer necessary to calculate the average temperature value; instead, it is treated directly as a temperature anomaly.

[0048] In one embodiment of the invention, for further explanation and limitation, the method further includes: constructing a temperature compensation processing network based on a convolutional neural network, wherein the kernel size in the temperature compensation processing network is configured based on kernel parameters that match the correction parameters; obtaining a temperature compensation training sample dataset and correction parameters that match different detection compensation service requirements, and replacing the model weights based on the correction parameters, wherein the correction parameters are proportional values ​​that match the number of model weights and are within the range of 0-1; and training the temperature compensation processing network based on the temperature compensation training sample dataset to obtain a trained temperature compensation processing model.

[0049] To achieve temperature compensation processing between temperature and distance based on machine learning algorithms, a temperature compensation processing network is constructed based on a convolutional neural network. The size of the convolutional kernel in this network is configured with correction parameters. Specifically, since the correction parameters are configured with a value range of 0-1 and are determined according to the model, usage time, manufacturer, and acceptable error range of the portable temperature measuring device, the size of the constructed convolutional kernel is configured based on the kernel parameters matched to the correction parameters. In this embodiment, a correspondence between different correction parameters and convolutional kernel parameters is pre-established. After determining the correction parameters, the convolutional kernel parameters are configured. For example, if the correction parameter is 0-0.5, the convolutional kernel parameters are configured as 3*3*Ci*C0, where C represents the number of channels, Ci is the number of input channels, and C0 is the number of output channels. During model training, to meet the temperature and distance compensation correction requirements, different correction parameters are matched for different detection compensation service needs. These requirements characterize the accuracy of temperature and distance compensation needs under different scenarios; the higher the accuracy, the larger the correction parameter. To make the convolutional neural network model's processing more suitable for compensation and correction scenarios and improve data processing accuracy, model weights are replaced based on correction parameters. These correction parameters are proportional values ​​matching the number of model weights and falling within the range of 0-1. For example, if the determined correction parameter is 0.3 and there are 3 model weights, then during replacement, three model weight values ​​are determined according to a ratio of 0.3 to 1, resulting in model weights of 0.3, 0.3, and 0.1, which are then used for replacement. Finally, the temperature compensation processing network is trained using a temperature compensation training sample dataset, resulting in a trained temperature compensation processing model. This dataset stores compensation value sample data, temperature data sample data, and distance data sample data for model training. This embodiment of the invention does not impose specific limitations on the training process.

[0050] This invention provides a temperature detection method based on a portable temperature measuring device. Compared with existing technologies, this invention sends a connection instruction to an IoT platform via a preset integrated networking protocol, enabling terminal devices connected to the IoT platform to record data collected by at least two portable temperature measuring devices. After establishing a connection with the IoT platform, it acquires temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device, respectively. The correction parameters characterize the influencing factors affecting the mapping relationship between the temperature data and the distance data. Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine a compensation value for the temperature data. A pre-trained temperature compensation processing model is used to detect the compensation value, the temperature data, and the distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing model weights based on the correction parameters, avoiding inaccurate temperature detection due to distance errors during testing, improving the accuracy of temperature measurement, and achieving a more quantifiable temperature detection and display effect, greatly satisfying the need for processing measured temperature data.

[0051] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this invention provides a temperature detection device based on a portable temperature measuring device, such as... Figure 3 As shown, the device includes:

[0052] The sending module 21 is used to send a connection instruction to the Internet of Things (IoT) platform through a preset integrated networking protocol, so that the terminal device connected to the IoT platform records data collected by at least two portable temperature measuring devices;

[0053] The acquisition module 22 is used to acquire temperature data, distance data and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device after establishing a connection with the Internet of Things platform. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data.

[0054] The first determining module 23 is used to perform fusion processing on the temperature data and distance data based on the mapping relationship between temperature and distance, and determine the compensation value of the temperature data.

[0055] The second determining module 24 is used to perform detection processing on the compensation value, the temperature data, and the distance data based on the temperature compensation processing model that has been trained, and to determine the target temperature value to be detected. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters.

[0056] This invention provides a temperature detection device based on a portable temperature measuring device. Compared with existing technologies, this invention sends a connection instruction to an IoT platform via a preset integrated networking protocol, enabling terminal devices connected to the IoT platform to record data collected by at least two portable temperature measuring devices. After establishing a connection with the IoT platform, it acquires temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device, respectively. The correction parameters characterize the influencing factors affecting the mapping relationship between the temperature data and the distance data. Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine a compensation value for the temperature data. A pre-trained temperature compensation processing model is used to detect and process the compensation value, temperature data, and distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing model weights based on the correction parameters, avoiding inaccurate temperature detection due to distance errors during testing, improving the accuracy of temperature measurement, and achieving a more quantifiable temperature detection and display effect, greatly satisfying the need for processing measured temperature data.

[0057] According to one embodiment of the present invention, a storage medium is provided, the storage medium storing at least one executable instruction, the computer-executable instruction being able to execute the temperature detection method based on a portable temperature measuring device in any of the above method embodiments.

[0058] Figure 4 The diagram shows a structural schematic of a terminal according to an embodiment of the present invention. The specific implementation of the terminal is not limited by the specific embodiments of the present invention.

[0059] like Figure 4 As shown, the terminal may include: a processor 302, a communications interface 304, a memory 306, and a communications bus 308.

[0060] The processor 302, communication interface 304, and memory 306 communicate with each other via communication bus 308.

[0061] Communication interface 304 is used to communicate with other network elements such as clients or other servers.

[0062] The processor 302 is used to execute program 310, which can specifically execute the relevant steps in the above-described embodiment of the temperature detection method based on a portable temperature measuring device.

[0063] Specifically, program 310 may include program code that includes computer operation instructions.

[0064] Processor 302 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The terminal may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0065] Memory 306 is used to store program 310. Memory 306 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0066] Specifically, program 310 can be used to cause processor 302 to perform the following operations:

[0067] By using a preset integrated networking protocol, a connection instruction is sent to the Internet of Things (IoT) platform so that the terminal device connected to the IoT platform can record data collected by at least two portable temperature measuring devices.

[0068] After establishing a connection with the IoT platform, the temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device are obtained. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data.

[0069] Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine the compensation value of the temperature data.

[0070] The temperature compensation processing model, which has been trained, is used to detect and process the compensation value, the temperature data, and the distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters.

[0071] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0072] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A temperature detection method based on a portable temperature measuring device, characterized in that, include: By using a preset integrated networking protocol, a connection instruction is sent to the Internet of Things (IoT) platform so that the terminal device connected to the IoT platform can record data collected by at least two portable temperature measuring devices. After establishing a connection with the IoT platform, the temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device are obtained. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data. Based on the mapping relationship between temperature and distance, the temperature data and distance data are fused to determine the compensation value of the temperature data. The temperature compensation processing model, which has been trained, is used to detect and process the compensation value, the temperature data, and the distance data to determine the target temperature value. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters. After determining the target temperature value to be detected, the method further includes: The location information of the portable temperature device is determined according to the Global Positioning System or a preset location identifier; Within a preset time range, the associated target temperature values ​​of portable temperature measuring devices that are associated with the location information and belong to a preset detection range are statistically analyzed. The associated temperature data is determined based on the associated temperature data and associated distance data collected by the associated temperature sensor and associated distance sensor of the associated portable temperature measuring device in the Internet of Things platform, respectively. If the associated target temperature value is greater than the abnormal temperature index, then an alarm message corresponding to the location information is sent. The method further includes: A temperature compensation processing network is constructed based on a convolutional neural network, wherein the kernel size in the temperature compensation processing network is configured based on kernel parameters that match the correction parameters; The temperature compensation training sample dataset and the correction parameters that match different detection compensation business requirements are obtained, and the model weights are replaced based on the correction parameters. The correction parameters are proportional values ​​that match the number of model weights and are in the range of 0-1. The temperature compensation processing network is trained using the temperature compensation training sample dataset to obtain a trained temperature compensation processing model.

2. The method according to claim 1, characterized in that, After calculating the associated target temperature values ​​of portable temperature measuring devices corresponding to the location information within a preset detection range within a preset time range, the method further includes: Detect whether the client has enabled data sharing permissions with the IoT platform; If the client enables the data sharing permission, a temperature status distribution map is generated based on the associated target temperature value, and the associated target temperature value and the temperature status distribution map are output to the client. If the client does not have the data sharing permission enabled, then the target temperature value and temperature status distribution map request command are output to generate the temperature status distribution map.

3. The method according to claim 1, characterized in that, The generation of the temperature state distribution map based on the associated target temperature value includes: Load the detection count and location information of the associated portable temperature measuring device from the IoT platform; Based on the determined associated target temperature value and the average temperature value calculated from the number of detections; The average temperature is marked on the detection map information drawn based on the location information to obtain a temperature state distribution map, wherein the average temperature is updated based on a preset number of detections and / or a preset detection time.

4. The method according to claim 3, characterized in that, Before marking the average temperature on the detection map information drawn based on the location information to obtain the temperature state distribution map, the method further includes: If the associated target temperature value is greater than the abnormal temperature index, it is determined to be an abnormal temperature state. The location information of the associated portable temperature measuring device corresponding to the abnormal temperature state is then rendered abnormally and marked in the temperature state distribution map.

5. A temperature detection device based on a portable temperature measuring device, characterized in that, include: The sending module is used to send a connection instruction to the Internet of Things (IoT) platform through a preset integrated networking protocol, so that the terminal device connected to the IoT platform records data collected by at least two portable temperature measuring devices; The acquisition module is used to acquire temperature data, distance data, and correction parameters collected by the temperature sensor and distance sensor in the portable temperature measuring device after establishing a connection with the IoT platform. The correction parameters are used to characterize the influence factors that affect the mapping relationship between the temperature data and the distance data. The first determining module is used to perform fusion processing on the temperature data and distance data based on the mapping relationship between temperature and distance, and determine the compensation value of the temperature data. The second determining module is used to perform detection processing on the compensation value, the temperature data, and the distance data based on the temperature compensation processing model that has been trained, and to determine the target temperature value to be detected. The temperature compensation processing model is obtained by replacing the model weights based on the correction parameters. The first determining module is further configured to determine the location information of the portable temperature device based on a global positioning system or a preset location identifier; Within a preset time range, the associated target temperature values ​​of portable temperature measuring devices that are associated with the location information and fall within a preset detection range are statistically analyzed. The associated temperature data is determined based on the associated temperature data and associated distance data collected by the associated temperature sensor and associated distance sensor of the associated portable temperature measuring device in the IoT platform, respectively. If the associated target temperature value is greater than the abnormal temperature index, an alarm message corresponding to the location information is sent. The second determining module is further configured to construct a temperature compensation processing network based on a convolutional neural network, wherein the kernel size in the temperature compensation processing network is configured based on kernel parameters that match the correction parameters; acquire a temperature compensation training sample dataset and correction parameters that match different detection compensation business requirements, and replace the model weights based on the correction parameters, wherein the correction parameters are proportional values ​​that match the number of model weights and are within the range of 0-1; train the temperature compensation processing network based on the temperature compensation training sample dataset to obtain a trained temperature compensation processing model.

6. A storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the temperature detection method based on a portable temperature measuring device as described in any one of claims 1-4.

7. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the temperature detection method based on the portable temperature measuring device as described in any one of claims 1-4.

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