Wearable temperature monitoring device and method, electronic equipment and storage medium

Abstract

The invention provides a wearable temperature monitoring device and method, electronic equipment and a storage medium, and the method comprises the steps: a thermal imaging sensor which is configured to obtain the infrared radiation of all objects in a surrounding environment, and converts the infrared radiation into temperature information; the target identification module is configured to obtain an infrared image of the surrounding environment and detect and identify each object in the infrared image through a deep learning model; the temperature comparison module is configured to compare the temperature information of each object with preset standard temperature information corresponding to each object to obtain a comparison result; and the message prompt module is configured to generate prompt information according to the comparison result. According to the method provided by the invention, portable mobile temperature monitoring can be realized, early warning can be carried out on an abnormal temperature object, and a user can conveniently know potential dangers.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature monitoring, and in particular to a wearable temperature monitoring device, method, electronic device and storage medium. Background Art

[0002] In daily life, temperature detection devices are often used to measure the temperature of various objects, such as water temperature, chassis temperature, etc. They are also often used to measure human body temperature. Such devices are large in size and have a single detection function. They are generally used to measure the temperature of known objects or living things. In outdoor scenarios, they cannot monitor potential dangers. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide a wearable temperature monitoring device, method, electronic device and storage medium.

[0004] In a first aspect of an embodiment of the present disclosure, a wearable temperature monitoring device is provided, comprising: a thermal imaging sensor, configured to acquire infrared radiation from objects in a surrounding environment and convert the infrared radiation into temperature information; a target recognition module, configured to acquire an infrared image of the surrounding environment and detect and recognize objects in the infrared image through a deep learning model; a temperature comparison module, configured to compare the temperature information of each object with preset standard temperature information corresponding to each object to obtain a comparison result; and a message prompt module, configured to generate prompt information based on the comparison result.

[0005] In a second aspect of an embodiment of the present disclosure, a wearable temperature monitoring method is provided, including: acquiring infrared radiation from each object in the surrounding environment, and converting the infrared radiation into temperature information; acquiring an infrared image of the surrounding environment, and detecting and identifying each object in the infrared image through a deep learning model; comparing the temperature information of each object with preset standard temperature information corresponding to each object to obtain a comparison result; and, based on the comparison result, generating prompt information.

[0006] In a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the method provided in the second aspect of the embodiment of the present disclosure.

[0007] In a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method provided in the second aspect of the embodiment of the present disclosure are implemented.

[0008] In the disclosed embodiment, based on the wearable temperature monitoring device, the temperature of various external objects can be detected. Not only is the device small in size and convenient for mobile detection, but it can also issue early warning prompts for objects with abnormal temperatures, allowing users to be aware of potential dangers in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A schematic diagram of the structure of a wearable temperature monitoring device provided in one embodiment of the present disclosure;

[0011] Figure 2 Another structural schematic diagram of a wearable temperature monitoring device provided by an embodiment of the present disclosure;

[0012] Figure 3 Another structural schematic diagram of a wearable temperature monitoring device provided by an embodiment of the present disclosure;

[0013] Figure 4 A schematic flow chart of a wearable temperature monitoring method provided in one embodiment of the present disclosure; and

[0014] Figure 5 A schematic diagram of the structure of an electronic device provided in one embodiment of the present disclosure. DETAILED DESCRIPTION

[0015] In order to make the purpose, features, and advantages of the invention disclosed in the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in 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.

[0016] It should be understood that the term "including" and other similar expressions in the specification or claims of the present disclosure and the above-mentioned drawings are intended to cover non-exclusive inclusions, such as a process, method, system, or device including a series of steps or units is not limited to the listed steps or units. In addition, "first" and "second" are used to distinguish different objects, not to describe a specific order.

[0017] See also Figure 1, a schematic diagram of the structure of a wearable temperature monitoring device provided by an embodiment of the present disclosure. The device 10 may include a thermal imaging sensor 110, a target recognition module 120, a temperature comparison module 130 and a message prompt module 140.

[0018] The thermal imaging sensor 110 is configured to acquire infrared radiation from various objects in the surrounding environment and convert the infrared radiation into temperature information.

[0019] In the disclosed embodiment, the thermal imaging sensor is a micro-electro-mechanical system (MEMS) chip, which is a detector array sensitive to long-wave infrared electromagnetic radiation (LWIR) in the wavelength range of 8 to 14 microns. All objects and all organisms above 0 degrees Kelvin emit radiation in this spectrum, and the intensity of this radiation represents their surface temperature. The thermal imaging sensor receives the infrared radiation of the object itself and uses photoelectric conversion, electrical signal processing and other means to instantly visualize the temperature distribution of the object and convert the infrared radiation into a specific temperature value.

[0020] For example, the thermal imaging sensor may be MLX90640, RTD617MR, IRSX series, DS-2TD9167-100ZD4F / W, etc., which are not specifically limited here.

[0021] Since the infrared radiation generated by objects will be received by thermal imaging sensors, the temperature and position information of each object in the environment can be collected through thermal imaging sensors, and the temperature of the objects can be monitored in real time.

[0022] In the disclosed embodiment, each object refers to an object whose infrared radiation can be collected by the thermal imaging sensor when the monitoring device 10 collects infrared radiation at a fixed viewing angle, or an object that appears in the infrared image. Objects are generally common objects in daily life, such as chairs, people, water cups, etc. Objects can be distinguished between living and non-living objects. Non-living objects can include water cups, metal objects, handrails, hospital medical equipment, etc. Living objects can include animals, people, etc. Living and non-living objects can be further distinguished, which is not further limited here.

[0023] In the disclosed embodiment, the temperature information is a specific temperature value obtained by the thermal imaging sensor by receiving the thermal radiation of the object, such as 53.4°C. The temperature difference of the object can be distinguished by different colors on the thermal image, for example, red is used to represent a higher temperature, and purple is used to represent a lower temperature.

[0024] The target recognition module 120 is configured to obtain an infrared image of the surrounding environment and detect and recognize each object in the infrared image through a deep learning model.

[0025] In the disclosed embodiment, the infrared image (also known as the thermal image) is obtained by the thermal imaging sensor 110 by collecting infrared radiation from each object and converting the infrared radiation of the object into a temperature distribution representation. The thermal radiation in the infrared image will be marked with different colors to form a temperature gradient image. Through the color and temperature correspondence table, the temperature distribution of the target object can be obtained, and the outline of the target can also be obtained.

[0026] The deep learning model is a model obtained by learning the contour features of objects in infrared images through a deep learning network, which can adopt a convolutional neural network (CNN) model based on candidate regions and a YOLO model based on regression analysis.

[0027] The CNN model based on candidate regions first proposes a candidate region proposal box for the image, and then classifies and locates the object in the candidate box. The YOLO model based on regression analysis directly solves the target classification as a regression problem. The image passes through the network once, and the object position, category, and confidence are predicted based on the bounding box regression.

[0028] For example, an infrared image is collected, and labelImg is used to mark the outlines and names of objects in the infrared image. The labeled infrared image is used as a training set to train and verify the YOLO V5 model. The trained YOLO V5 model is used to recognize the names of objects in the collected infrared image or to recognize the types of objects.

[0029] The temperature comparison module 130 is configured to compare the temperature information of each object with the preset standard temperature information corresponding to each object to obtain a comparison result.

[0030] In the embodiment of the present disclosure, when the deep learning model of the target recognition module 120 recognizes an object in an infrared image, the object temperature information can be compared with the preset standard temperature information corresponding to the object to determine whether the object temperature is abnormal.

[0031] The preset standard temperature information corresponding to the object refers to the normal temperature range of the object. For example, the standard temperature value of a water cup is 30-50°C, the standard temperature value of a human body is 36-37.3°C, and the standard temperature value of an animal is 37.5-39°C.

[0032] For example, the comparison result may include normal temperature, too low temperature, or too high temperature.

[0033] For example, the temperature of a water cup acquired by the thermal imaging sensor is 80°C. The water cup temperature of 80°C is compared with the standard value of the water cup temperature (30-50°C). The comparison result generated indicates that the temperature of the water cup is too high to prevent the user from being scalded by the water cup.

[0034] For example, the thermal imaging sensor acquires a human body temperature of 38°C. The human body temperature of 38°C is compared with the standard human body temperature value (36-37.3°C). The generated comparison result indicates that the human body temperature is too high, prompting the user to stay away from the person to prevent infection.

[0035] For example, the thermal imaging sensor acquires an animal body temperature of 40°C. The animal body temperature of 40°C is compared with the standard value of human body temperature (37.5-39°C). The generated comparison result indicates that the animal's temperature is too high, prompting the user to stay away from the animal.

[0036] The message prompt module 140 is configured to generate prompt information according to the comparison result.

[0037] In the disclosed embodiment, the prompt information is generated based on the comparison result of the object temperature. For example, when the human body temperature comparison result indicates that the human body temperature is too high, a corresponding message can be generated to prompt to stay away from the person.

[0038] In the disclosed embodiment, the prompt information can be used to prompt the user in the form of special symbols, text, images or voice. For example, a red exclamation mark is used to prompt the user of danger, a text prompt of "the temperature of the object is too high" is used, the outline of the dangerous object is marked in the infrared image, or a voice broadcast indicates that the object is dangerous.

[0039] According to the embodiments of the present disclosure, based on the detection and recognition of the object in the infrared image by the target recognition module, the temperature of the object collected by the thermal imaging sensor is compared with the preset standard temperature of the object, so as to realize the early warning of the abnormal temperature object and monitor the potential safety risks. At the same time, the integrated design of the thermal imaging sensor, the target recognition module, the temperature comparison module and the message prompt module can facilitate the miniaturization of the monitoring device and facilitate mobile detection.

[0040] In the disclosed embodiment, the wearable thermal imaging temperature monitoring device is a portable thermal imaging body temperature monitoring device. For example, the device can be a badge similar in size to a work badge, so as to facilitate the temperature monitoring of objects other than the user and the wearable use of the user.

[0041] Figure 2 Another structural schematic diagram of a wearable temperature monitoring device provided by an embodiment of the present disclosure. Figure 2As shown, the device 20 may include a thermal imaging sensor 210, a target recognition module 220, a temperature comparison module 230, a message prompt module 240, and a data association module 250. It can be understood that the functions of the thermal imaging sensor 210, the target recognition module 220, the temperature comparison module 230, and the message prompt module 240 are similar or identical to those of the thermal imaging sensor 110, the target recognition module 120, the temperature comparison module 130, and the message prompt module 140, respectively. For the sake of simplicity, the thermal imaging sensor 210, the target recognition module 220, the temperature comparison module 230, and the message prompt module 240 are not described in detail here.

[0042] The data association module 250 is coupled to the thermal imaging sensor 210 and the target recognition module 220 , and is used to obtain the object recognition result of the target recognition module 220 , and associate the object recognition result with the temperature information of the corresponding object in the thermal imaging sensor 210 .

[0043] In the disclosed embodiment, the data association module 250 can associate the object recognition result with the object temperature information. On the one hand, caching the associated data can facilitate the data call of the subsequent temperature comparison module. On the other hand, the associated data can be uploaded, so that the cloud can not only store, verify and monitor the recognition data, but also facilitate the subsequent upgrade and optimization of the deep learning model based on these associated data.

[0044] When the object recognition result is associated with the object temperature information, the object name and the object temperature can be associated. For example, a water cup is -52℃. The object number and the temperature can also be associated, such as 14-52℃. The association can also be represented by a string. The specific association method is not detailed here. After the data is associated, it can be stored in the form of key-value.

[0045] It should be noted that after associating the object recognition result with the object's temperature information, a timestamp needs to be added to the associated data.

[0046] In one embodiment, the data association module 250 includes: a labeling unit, which is used to label the object recognition result and the temperature information of the object in the corresponding infrared image after the target recognition module recognizes the object in the infrared image.

[0047] Since the deep learning model will generate a target detection frame during the process of recognizing infrared images, the target detection frame can be used as an object annotation in the infrared image, and the object recognition results and object temperature information can be superimposed on the infrared image in a specific color or a color with high contrast within the pixel range of the target detection frame. In other words, the object detection frame, object recognition results and object temperature can be directly marked in the infrared image.

[0048] In some embodiments, the device further includes: a display module 260 configured to display the infrared image generated by the thermal imaging sensor, the object recognition result and the object temperature value.

[0049] The labeling unit in the data association module labels the object recognition result and the object temperature information. When displaying the infrared image, the object recognition result, the object temperature value and other information can be displayed together. In the display module, the pre-displayed infrared image and the object recognition result, the object temperature value and other information marked on the infrared image can be encoded together and sent to the display screen, which is decoded and displayed by the display screen. The display screen can be an LED display screen or a liquid crystal display screen.

[0050] In some embodiments, the apparatus further includes: a communication module configured to enable the apparatus to communicate with a user terminal device.

[0051] For example, the user terminal device may be a mobile phone, a computer, a movable device, etc.

[0052] For example, the communication method can be wireless wifi, 4G / 5G network, etc.

[0053] In the disclosed embodiment, by displaying the annotated infrared image, it is not only convenient for the user to obtain the infrared imaging information of the object, but also it is possible to intuitively display the position, temperature, etc. of the object, so as to facilitate the user to identify the danger source.

[0054] Figure 3 Another structural schematic diagram of a wearable temperature monitoring device provided by an embodiment of the present disclosure. Figure 3 As shown, the device 30 may include a thermal imaging sensor 310 , a target recognition module 320 , a temperature comparison module 330 , a message prompt module 340 and a data storage module 350 .

[0055] The data storage module 350 is coupled to the target recognition module 320 and the temperature comparison module 330 and is used to store standard temperature information of various objects.

[0056] The data storage module 350 can be used to store standard temperature information of various objects. For example, the standard temperature value of a water cup is 30-50°C, the standard temperature value of a human body is 36-37.3°C, etc. These preset standard temperature information are stored in the memory to facilitate direct calling of the temperature comparison module.

[0057] In one embodiment, the temperature comparison module 330 includes: a data reading unit, which is used to read the standard temperature information corresponding to the object in the data storage module after the target recognition module outputs the object recognition result to the data storage module.

[0058] The data reading unit can obtain the corresponding standard temperature information in the data storage module after the target recognition module outputs the object recognition result to the data storage module. For example, if the target recognition module outputs the recognition result as a dog, the corresponding temperature standard value can be read in the data storage module as 37.5-38.5°C.

[0059] In the disclosed embodiment, the data storage module can be directly accessed through the data reading unit, so as to facilitate reading of data in the memory and facilitate temperature comparison.

[0060] In some embodiments, the target recognition module in the wearable temperature monitoring device is further configured as follows: when the deep learning model cannot recognize the object in the infrared image, the object category is determined and a category label is generated for the corresponding object; when the deep learning model cannot determine the category of the object, a detection frame is generated for the object and marked as unrecognizable.

[0061] In real life, since the objects in the environment are very diverse, but the training sample set is relatively limited, it is impossible to identify all types of objects. In addition, infrared images generally have poor imaging clarity, which affects the judgment of the deep learning model. Therefore, in addition to training the deep learning model with common objects, the model can also be trained to judge the category of objects.

[0062] Object categories can be divided into living objects and non-living objects, moving objects and stationary objects, etc., and can be set according to the application scenario. For example, in a wild scene, the category can also be set to animals, plants, etc.

[0063] When the deep learning model recognizes objects in infrared images, when the object recognition confidence is low (lower than a certain set value), the object category can be judged. When the deep learning model cannot recognize the object category (confidence is lower than the set value), it can be marked as unrecognizable and identified in the infrared image.

[0064] In the disclosed embodiment, when the deep learning model is unable to accurately identify an object, the introduction of object type judgment can ensure the normal operation of the target recognition module. At the same time, through object category recognition and marking of unrecognizable objects, it can facilitate users to judge potential security risks.

[0065] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0066] Figure 4 The structure diagram of the wearable temperature monitoring method provided by the embodiment of the present disclosure includes steps S401 to S404.

[0067] In operation S401 , infrared radiation of each object in the surrounding environment is acquired, and the infrared radiation is converted into temperature information.

[0068] In operation S402, an infrared image of the surrounding environment is acquired, and each object in the infrared image is detected and identified through a deep learning model.

[0069] In operation S403, the temperature information of each object is compared with the preset standard temperature information corresponding to each object to obtain a comparison result.

[0070] In operation S404, prompt information is generated according to the comparison result.

[0071] In the embodiment of the present disclosure, the apparatus 10 may be used to implement method steps S401 to S404.

[0072] For example, the operation of step S401 is performed using the thermal imaging sensor 110 , the operation of step S402 is performed using the target recognition module 120 , the operation of step S403 is performed using the temperature comparison module 130 , and the operation of step S404 is performed using the message prompt module 140 .

[0073] In some embodiments, step S402 further includes: obtaining an object recognition result of the target recognition module, and associating the object recognition result with temperature information of the corresponding object.

[0074] In the embodiment of the present disclosure, after the target recognition module 120 recognizes the object in the infrared image, the object recognition result and the temperature information of the object are marked in the corresponding infrared image.

[0075] In some embodiments, after marking the object recognition result and the object temperature information in the corresponding infrared image, the method further includes: displaying the infrared image generated by the thermal imaging sensor, the object recognition result and the object temperature value.

[0076] In some embodiments, before comparing the temperature information of each object with the preset standard temperature information corresponding to each object in S403, the step further includes: storing the standard temperature information of each type of object.

[0077] In the disclosed embodiment, step S403 includes: obtaining an object recognition result, and reading standard temperature information corresponding to the object.

[0078] In some embodiments, step S402 also includes: when the deep learning model cannot recognize the object in the infrared image, determining the object category and generating a category label for the corresponding object; when the deep learning model cannot determine the category of the object, generating a detection frame for the object and marking it as unrecognizable.

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0080] Figure 5 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. The electronic device is used for object temperature monitoring. Figure 5 As shown, the electronic device 5 of this embodiment includes: a memory 510, a processor 520 and a system bus 530, wherein the memory 510 includes an executable program 5101 stored thereon, and those skilled in the art can understand that Figure 5 The electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0081] Combine the following Figure 5 A detailed introduction to the various components of electronic equipment:

[0082] The memory 510 can be used to store software programs and modules, and the processor 520 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 510. The memory 510 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc. The data storage area may store data (such as cache data) created according to the use of the electronic device, etc. In addition, the memory 510 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0083] The memory 510 includes an executable program 5101 of the network request method, and the executable program 5101 can be divided into one or more modules / units, which are stored in the memory 510 and executed by the processor 520 to realize object temperature monitoring, etc. The one or more modules / units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 5101 in the electronic device 5. For example, the computer program 5101 can be divided into functional modules such as a target detection module, a temperature comparison module, and a message prompt module.

[0084] The processor 520 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 510, and calling data stored in the memory 510, it performs various functions of the electronic device and processes data, thereby monitoring the overall status of the electronic device. Optionally, the processor 520 may include one or more processing units; preferably, the processor 520 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 520.

[0085] The system bus 530 is used to connect the various functional components inside the computer, and can transmit data information, address information, and control information. Its types can be, for example, PCI bus, ISA bus, CAN bus, etc. The instructions of the processor 520 are transmitted to the memory 510 through the bus, and the memory 510 feeds back data to the processor 520. The system bus 530 is responsible for the data and instruction exchange between the processor 520 and the memory 510. Of course, the system bus 530 can also be connected to other devices, such as network interfaces, display devices, etc.

[0086] In the embodiment of the present disclosure, the executable program executed by the processor 520 included in the electronic device includes: obtaining infrared radiation from each object in the surrounding environment and converting the infrared radiation into temperature information; obtaining an infrared image of the surrounding environment, and detecting and identifying each object in the infrared image through a deep learning model; comparing the temperature information of each object with the preset standard temperature information corresponding to each object to obtain a comparison result; and generating prompt information based on the comparison result.

[0087] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0088] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0089] As described above, the above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A wearable temperature monitoring device, characterized in that: include: A thermal imaging sensor configured to acquire infrared radiation from various objects in the surrounding environment and convert the infrared radiation into temperature information; A target recognition module is configured to obtain an infrared image of the surrounding environment and detect and recognize each object in the infrared image through a deep learning model; A temperature comparison module is configured to compare the temperature information of each object with the preset standard temperature information corresponding to each object to obtain a comparison result; as well as The message prompt module is configured to generate prompt information according to the comparison result.

2. The device according to claim 1, characterized in that Also includes: A data association module is coupled to the thermal imaging sensor and the target recognition module, and is used to obtain the object recognition result of the target recognition module and associate the object recognition result with the temperature information of the corresponding object in the thermal imaging sensor.

3. The device according to claim 2, characterized in that The data association module comprises: The marking unit is used to mark the object recognition result and the temperature information of the object in the corresponding infrared image after the target recognition module recognizes the object in the infrared image.

4. The device according to claim 3, characterized in that Also includes: The display module is configured to display the infrared image generated by the thermal imaging sensor, the object recognition result and the object temperature value.

5. The device according to claim 1, characterized in that Also includes: The data storage module is coupled to the target recognition module and the temperature comparison module, and is used to store standard temperature information of various objects.

6. The device according to claim 4, characterized in that The temperature comparison module comprises: The data reading unit is used to read the standard temperature information corresponding to the object in the data storage module after the target recognition module outputs the object recognition result to the data storage module.

7. The device according to claim 1, characterized in that The target recognition module is also configured as follows: When the deep learning model cannot identify the object in the infrared image, it determines the object category and generates a category label for the corresponding object; and When the deep learning model cannot determine the category of an object, a detection box is generated for the object and marked as unrecognizable.

8. A wearable temperature monitoring method, characterized in that: include: Obtain infrared radiation from various objects in the surrounding environment and convert it into temperature information; Obtain infrared images of the surrounding environment and detect and identify objects in the infrared images through deep learning models; Compare the temperature information of each object with the preset standard temperature information corresponding to each object to obtain a comparison result; as well as Generate prompt information based on the comparison result.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method of claim 8.

10. A computer-readable storage medium storing a computer program, characterized in that: The computer program implements the steps of the method according to claim 8 when executed.

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