KR102405023B1 - Self-driving-based Temperature Monitoring Robot and its Temperature Monitoring Method - Google Patents

Abstract

An embodiment of the present invention includes: a first sensor that acquires an image of an object and produces image data; a second sensor that measures the distance of the object and generates distance data; a third sensor that measures the temperature of the object and produces temperature data; a control unit that generates a signal based on data of a measurement unit including the first sensor, the second sensor, and the third sensor and controls the robot; a processing unit for receiving a signal from the control unit and processing operation of image data, distance data, and temperature data; and an output unit for outputting a signal from the control unit, wherein the processing unit checks data of a preset environment variable, and selects data of the measurement unit that exceeds or falls short of a preset reference value based on the data of the environment variable, It is possible to provide a body temperature monitoring robot that generates an alarm based on the selected data.

Description

Self-driving-based Temperature Monitoring Robot and its Temperature Monitoring Method}

The present embodiment relates to a body temperature monitoring robot and a body temperature monitoring method for accurately measuring body temperature in consideration of data measured by a plurality of sensors and environmental variables.

Humanity is constantly threatened by various infectious diseases, and new epidemics such as the Black Death in the 14th century and smallpox in the 15th century, as well as measles, influenza, malaria, and cholera are repeating.

In recent years, as the coronavirus has spread around the world, efforts to prevent the spread of infectious diseases are continuing in each country, such as new infectious diseases that cause dozens of new infections for each infected person.

In general, it is a widely known fact that people infected with infectious diseases are accompanied by fever, and as a way to detect those infected with these infectious diseases at an early stage, those who have a fever outside the normal body temperature are first classified as suspected and isolated or treated in advance. Measures are being used to prevent the spread of the epidemic.

In the case of a general adult, the average body temperature is around 37℃, and the method of determining whether a subject has a fever exceeding normal body temperature is the contact method of attaching a temperature measuring device to the body of the subject to measure the temperature, and the method of measuring the temperature at a certain distance. There is a non-contact method that measures the temperature of an object to be measured without contact with the body using a measuring device.

Thermal imaging cameras are widely used for non-contact temperature measurement, and thermal imaging cameras are based on the principle that all objects above absolute zero (-273℃) emit infrared light based on the infrared wavelength emitted by the measuring object. measure the temperature of

A thermal imaging camera installed at a fixed location can measure only the temperature of a subject that exists at a field of view or a limited distance, so it can measure the body temperature of a subject distributed in a wide space or the body temperature of some subjects. The disadvantage is that it can only be measured.

In addition, thermal imaging cameras have limitations in accurate temperature measurement because it is not easy to distinguish thermal image data according to distance. have.

In addition, as the robot including the thermal imaging camera continuously moves, it measures the temperature only based on the infrared wavelength emitted by the object without considering the distance of the measurement target, thus measuring the temperature more inaccurately, and a single robot There is a problem in that the measured temperature cannot verify the difference between the actual measured object temperature and the measured temperature.

Against this background, an object of the present embodiment is to provide an autonomous driving-based body temperature monitoring robot and body temperature monitoring method capable of accurate temperature calculation in consideration of external environmental variables.

The purpose of this embodiment is, on the other hand, to provide temperature data correction using distance data, and autonomous driving-based body temperature monitoring that enables more accurate temperature calculation through mutual cross-validation with temperature using an internal sensor of a separate body temperature monitoring robot It is to provide a method for monitoring a robot and body temperature.

In order to achieve the above object, an embodiment includes a measurement unit including a first sensor for producing image data of an object, a second sensor for producing distance data, and a third sensor for producing temperature data; a control unit that generates a signal based on data of a measurement unit including the first sensor, the second sensor, and the third sensor and controls the robot; a processing unit that receives a signal from the control unit and processes calculations of image data, distance data, and temperature data, wherein the processing unit includes an artificial intelligence module and an environment module; an output unit including an image unit that converts the signal of the control unit and displays the temperature of the object measured by the third sensor; a data unit including at least one of a first memory configured to store distance data and a second memory configured to store temperature data using the signal of the controller; and an alarm unit for generating an alarm based on the data selected by the processing unit, wherein the data of the measurement unit is stored in the data unit, and the artificial intelligence module assigns an object identification value based on the data stored in the data unit and the processing unit stores the matched unique identification number by matching the identification number of the object stored in the data unit with the identification value of the given object, and the processing unit is based on the identification value of the object in the data unit and the matched unique identification number A body temperature monitoring robot that identifies an object or confirms a specific ID of a user may be provided.

The body temperature monitoring robot air processing unit checks the data of a preset environment variable, and selects the data of the measurement unit according to a preset reference value based on the data of the environment variable, The environment variable preset in the environment module is Temperature, surrounding environment humidity, surrounding environment wind speed, density of people, whether or not the air conditioner is running, rain or not, the season, the presence of a heat source in the vicinity, the intensity of sunlight and carbon dioxide concentration, including any one of the temperature monitoring robot can provide

In the body temperature monitoring robot, the processing unit includes a first memory and a second memory, and the processing unit calculates the temperature data of the second memory based on the distance data of the first memory to improve the accuracy of temperature measurement. A robot can be provided.

Provide a body temperature monitoring robot that produces temperature data from the body temperature monitoring robot to a third sensor disposed in the body temperature monitoring robot, stores it in the data unit, and transmits the temperature data to a separate body temperature monitoring unit for temperature data calibration can do.

In the body temperature monitoring robot, the processing unit calibrates the temperature data of the third sensor based on the temperature measurement value transmitted from the separate body temperature monitoring robot, and the temperature measurement value transmitted from the separate body temperature monitoring robot is the separate body temperature monitoring robot. It is possible to provide a body temperature monitoring robot, which is measured by a sensor disposed on the robot.

In the body temperature monitoring robot, the third sensor may measure a black body having a specific temperature in advance, and the processing unit may provide a body temperature monitoring robot that corrects the temperature data of the object based on the temperature data of the black body.

The body temperature monitoring robot may further include a driving unit for moving the robot, and the controller may provide a body temperature monitoring robot that operates the driving unit to collect temperature data for each distance.

In order to achieve the above object, in another embodiment, in a method for monitoring body temperature using an artificial intelligence module and an environment module, the artificial intelligence module analyzes image data when the number of measured objects is less than or equal to a reference value. specifying the person; specifying a person by analyzing distance data when the degree of similarity in the appearance of the measured object is greater than or equal to a reference value; and determining whether the body temperature is normal based on a preset environment variable, wherein the environment module includes: measuring a preset environment variable; and comparing the measured temperature data of the object with a preset environmental variable; and may provide a body temperature monitoring method.

In the body temperature monitoring method, the artificial intelligence module may provide a body temperature monitoring method, further comprising: correcting image data based on distance data.

In the body temperature monitoring method, the artificial intelligence module may provide a body temperature monitoring method, further comprising: correcting the temperature data of the object based on the previously measured temperature of the black body.

In the body temperature monitoring method, the artificial intelligence module provides a body temperature monitoring method, further comprising: calibrating the temperature data measured by a third sensor based on the temperature data measured by a separate body temperature monitoring robot can do.

In the body temperature monitoring method, the separate body temperature monitoring robot includes a temperature sensor disposed inside the robot to measure an internal temperature of the robot, and the artificial intelligence module is measured by a temperature sensor inside the separate body temperature monitoring robot. comparing the one temperature data with the temperature data measured by the second sensor; calculating a difference between temperature data measured by a temperature sensor inside the separate body temperature monitoring robot and temperature data measured by a second sensor; calculating a correction value based on a difference between temperature data measured by a temperature sensor inside the separate body temperature monitoring robot and temperature data measured by a second sensor; and correcting the temperature data measured by the second sensor by applying a correction value calculated based on the difference between the temperature data measured by the temperature sensor inside the separate body temperature monitoring robot and the temperature data measured by the second sensor. It is possible to provide a body temperature monitoring method further comprising;

In the body temperature monitoring method, the environment module may include: checking an ambient temperature; checking the density of people; and checking whether the air conditioner is in operation.

As described above, according to the present embodiment, it is possible to provide a temperature monitoring robot capable of accurate temperature calculation and a temperature monitoring method, and to accurately measure the temperature of an object.

1 is a diagram illustrating a process in which a body temperature monitoring robot measures an object according to an embodiment.
FIG. 2 is a diagram illustrating an internal block diagram of the body temperature monitoring robot of FIG. 1 .
3 is a view for explaining a method of specifying and tagging a person according to an embodiment.
4 is a diagram illustrating a method of identifying a person by identifying a person's face according to an exemplary embodiment.
5 is a diagram illustrating the movement of a body temperature monitoring robot according to an embodiment.
6 is a view for explaining an error generation method for each distance of a thermal imaging camera and a method of improving the error.
7 is a diagram illustrating a first method for correcting an error of a thermal imaging camera.
8 is a diagram illustrating a second method for correcting an error of a thermal imaging camera.
9 is a block diagram illustrating a method of monitoring the temperature of an object according to an embodiment.
10 is a block diagram illustrating a method of checking an environment variable according to an embodiment.
11 is a block diagram illustrating a method of determining whether a body temperature is normal based on a reference value of an environmental variable according to an exemplary embodiment.
12 is a block diagram illustrating a method of correcting measured temperature data based on received temperature data according to an embodiment.

Hereinafter, some embodiments of the present invention will be described in detail with reference to exemplary drawings. In adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals as much as possible even though they are indicated on different drawings. In addition, in the description of the present invention, detailed descriptions of related well-known structures or functions that are determined to obscure the gist of the present invention will be omitted.

In addition, in describing the components of the present invention, terms such as first, second, a, and b may be used. These terms are only for distinguishing the elements from other elements, and the essence, order, or order of the elements are not limited by the terms. When a component is described as being “connected”, “coupled” or “connected” to another component, the component may be directly connected to or connected to the other component, but another component is between each component. It should be understood that elements may also be “connected,” “coupled,” or “connected.”

1 is a diagram illustrating a process in which a body temperature monitoring robot measures an object according to an embodiment.

FIG. 2 is a diagram illustrating an internal block diagram of the body temperature monitoring robot of FIG. 1 .

1 and 2 , the body temperature monitoring robot 100 may measure an image, a distance, and a temperature of a target object 200 .

The body temperature monitoring robot 100 may include a measuring unit 10 , a processing unit 20 , an output unit 30 , a driving unit 40 , a data unit 50 , and a control unit 60 .

The measurement unit 10 may include an image measurement unit 12 , a distance measurement unit 14 , and a temperature measurement unit 16 .

The image measurement unit 12 may include a first sensor that acquires an image of the object and produces image data, for example, the first sensor identifies the object using visible light, infrared light, etc., and an RGB camera can be

The RGB camera may acquire a color image of an object by combining Red (red), Green (green), and Blue (blue), and the type may be an analog or digital camera, but is not limited thereto.

The image measuring unit 12 may additionally include a receiving unit for receiving an image image of an object, and a CCD or CMOS image sensor may be used as the sensor for receiving the image.

A CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) sensor is a sensor that converts light into electric charge to obtain an image.

The distance measuring unit 14 may include a second sensor for measuring a distance to an object and generating distance data, for example, the second sensor is a Time Of Flight (TOF) method, a structured light The camera can be used in various ways using a method, a stereo type, or a stereo type.

By using the image data obtained by the image measurement unit 12, the existence of an object, the size of the object, the movement of the object, the characteristics of the object, etc. may be determined.

In addition, the second sensor 12 may be, for example, lidar, radar, or ultrasound, and the distance data may include azimuth, speed, and depth information.

The distance or depth information of an object can be acquired in various ways depending on the type of camera and the measurement method, and the accuracy of depth recognition, scanning speed, range of distance measurement according to the position of the object, and surrounding It may be appropriately selected in consideration of the performance in case of weak lighting considering the intensity of light, the complexity of the software used together, and the cost of the module.

The temperature measuring unit 16 may include a third sensor that measures the temperature of the object and produces temperature data, for example, the third sensor may be a thermal imaging camera.

Thermal imaging cameras measure the temperature by recognizing blackbody radiation from humans, animals, and other heat-emitting objects, and can calculate the exact temperature by measuring the wavelength corresponding to the temperature.

In general, an infrared camera may measure thermal energy emitted from a target object, and may acquire thermal image information using visible light, infrared light, or the like. The acquired temperature data is converted into an electrical signal and transmitted to the processing unit 20 or the output unit 30 to perform additional calculations, and is transmitted to the data unit 50 as necessary to be utilized to determine whether the body temperature is normal can be

Illustratively, as the thermal imaging camera, a cooled infrared detector or an uncooled infrared detector included in a vacuum sealed case may be utilized, but may be appropriately selected according to a target temperature range.

For example, the third sensor may be a spot type thermometer. A spot-type thermometer is different from a thermal imaging camera that reads the temperature of each pixel of an image in that it reads the temperature of a single point, and may be appropriately selected according to necessity.

According to an embodiment, as the measurement range of the third sensor, an appropriate measurement range may be set using a spot size ratio (SSR) or an instantaneous field of view (IFOV) according to a distance.

When a thermal imaging camera or thermometer is used, appropriate temperature data may not be obtained depending on the distance to the object and whether the object is moving.

According to an embodiment, by selecting one or more of the first sensor of the image measuring unit 12, the second sensor of the distance measuring unit 14, and the third sensor of the temperature measuring unit 16, the accuracy of the temperature data is measured. can be raised

The measurement unit 10 may further include an auxiliary member (not shown) for improving the performance of the image measurement unit 12 , the distance measurement unit 14 , and the temperature measurement unit 16 . The member (not shown) may be an optical path changing member such as one or more lenses, prisms, and diffusers.

The processing unit 20 may perform an operation by utilizing an artificial intelligence (AI) module 22 and/or an environment module 24 . By receiving a signal from the control unit, calculation of image data, distance data, and temperature data may be processed.

In the artificial intelligence module 22, each operation may be performed by using methods such as machine learning, artificial neural network, deep learning, and cognitive computing, and known computer programming may be utilized. For example, the artificial intelligence module 22 may be utilized for calculation speed, accuracy of judgment, reduction of errors, and the like.

The environmental variables utilized by the environmental module 24 are the temperature of the surrounding environment, the humidity of the surrounding environment, the wind speed of the surrounding environment, the density of people, the operation of the air conditioner, the presence of rain, the season, the presence of a surrounding heat source, the intensity of sunlight and carbon dioxide concentration.

Errors that may occur in the temperature measurement process may be divided into errors occurring in internal factors of the temperature detection target object and errors occurring in external factors of the temperature detection target object.

The environment variable utilized by the environment module 24 may be for appropriately calculating and correcting an error occurring in an external factor of the temperature detection target.

The monitoring method using the environment module 24 may include measuring a preset environmental variable or comparing the measured temperature data of the object with a preset environmental variable.

The monitoring method using the environment module 24 may include checking the ambient temperature, checking the density of people, or checking whether the air conditioner is operating.

The processing unit 20 may utilize the environment module 24 to check data of a preset environment variable, and select data of the measurement unit that exceeds or falls below a preset reference value based on the data of the environment variable.

The processing unit 20 may calculate the temperature data of the second memory based on the distance data of the first memory.

The data of the measurement unit 10 may be stored in the first memory 52 of the data unit 50 , and an object identification value may be assigned by the AI module based on the data stored in the first memory. In this case, the second memory 54 stores the unique identification number of the object, and the processing unit 20 matches the identification value of the object stored in the first memory with the unique identification number of the object stored in the second memory, and the matched The unique identification number may be stored in the second memory 54 .

The processing unit 20 may specify the object based on the identification value of the object in the second memory and the matched unique identification number or confirm the specific ID of the user.

The processing unit 20 calibrates the temperature data of the second sensor based on the temperature measurement value transmitted from the separate body temperature monitoring robot, and the temperature measurement value transmitted from the separate body temperature monitoring robot is the separate body temperature monitoring robot. It can be measured by a sensor placed on the

The second sensor may measure the black body having a specific temperature in advance, and the processing unit 20 may correct the temperature data of the object based on the temperature data of the black body.

The output unit 30 may include an image unit 32 , an audio unit 34 , and an alarm unit 36 .

The image unit 32 may display an image, and includes a cathode-ray tube (CRT), a plasma display panel (PDP), a light EEmitting diode (LED) display, an organic LED (OLED) display, an active-matrix (AMOLED) display. , a liquid crystal display (LCD) display, and the like.

The type of the sound unit 34 is not limited as long as it can generate a sound signal by receiving a signal from the control unit, and for example, a Bluetooth speaker, a smart speaker, or the like may be used.

The alarm unit 36 may select the data processed by the processing unit, and generate an alarm based on data in which the measured temperature data of the object exceeds or falls below a reference value. If necessary, the signal of the control unit may be converted to generate an alarm.

The driving unit 40 may include a robot moving unit 42 for moving the body temperature monitoring robot and a robot adjusting unit 44 for controlling individual parts of the robot.

The robot moving unit 42 may include moving elements that can move the robot, such as wheels and rails.

The robot control unit 44 may adjust the arms, legs, neck, eyes, etc. of the robot as needed, and may adjust the parts by receiving a signal from the control device for each part according to a desired situation.

Illustratively, the arm of the robot can be folded when passing through a narrow passage, and a blackbody or any reference point measurement that is a reference point for thermal sensing can be easily deformed. In addition, the neck of the robot may be appropriately rotated or tilted in consideration of the position or direction of the measurement target.

The data unit 50 may include a first memory 52 and a second memory 54, and if necessary, the number of storage devices is not limited.

According to an embodiment, the data unit 50 may store the signal of the control unit in any storage device among the first memory 52 and the second memory 54 , for example, the first memory 52 . may store distance data, and the second memory 54 may store temperature data.

According to an embodiment, the distance data stored in the first memory 52 may be transferred to the processing unit 20 to calculate the temperature data, and the temperature data may be stored in the second memory 54 .

According to an embodiment, the data of the measurement unit may be stored in the first memory 52 , and the artificial intelligence module 22 may assign an identification value of the object based on the data stored in the first memory. For example, the unique identification number of the object may be stored in the second memory 54 , and in the processing unit 20 , the identification value of the object stored in the first memory 52 and the object stored in the second memory 52 . Matches the unique identification number of , and the matched unique identification number may be stored again in the second memory 52 .

The data stored again in the second memory 52 may be used in the processing unit 20 to specify an object based on the identification value of the object and the matched unique identification number or to confirm a specific ID of a user.

The control unit 60 may transmit or receive the processed signal to the measuring unit 10 , the processing unit 20 , the output unit 30 , the driving unit 40 , and the data unit 50 .

According to an embodiment, the image data, distance data, and temperature data measured by the measurement unit 10 may be transmitted to the control unit 60 , and the control unit 60 transmits the data to the processing unit as necessary to the processing unit 20 . can be forwarded to The processing unit 20 may transmit data calculated by the artificial intelligence module 22 and/or the environment module 24 back to the control unit. The control unit 60 may transmit the received data or signal to the output unit 30 to be output as an image signal, a sound signal, an alarm signal, and the like. The control unit 60 may transmit a control signal to move the robot through the driving unit, or may control each part of the robot.

The controller 60 may transmit the signal or data received from the measurement unit 10 or the processing unit 20 to the data unit 50 and store it in the data unit 50 temporarily or researchly. According to an embodiment, the control unit 60 selectively performs a storage function in the first memory 52 or the second memory 54 of the data unit 50 according to the purpose of use, the type of data, the amount of data, and the like. can do.

3 is a view for explaining a method of specifying and tagging a person according to an embodiment.

Referring to FIG. 3 , the measurement unit 10 of the temperature monitoring robot may acquire image data of a measurement object or person, and may manage it by tagging a specific ID of the measurement object or person. According to an embodiment, a series of steps for specifying and tagging a person may be performed in real time, and may be automatically performed by the artificial intelligence module 22, or an administrator may directly tag and manage a specific ID for each object or person. .

According to an embodiment, it may include a data unit for storing data of the measurement unit, and based on the data stored in the data unit, the identification value of the object may be assigned by the artificial intelligence module. Based on the identification value of the object given by the artificial intelligence module, an object may be specified or a user's specific ID may be identified.

According to an embodiment, the method of tagging and managing objects or persons may be performed by the body temperature monitoring robot 100 . The data of the measuring unit 10 of the body temperature monitoring robot 100 may be stored in the second memory 52, and based on the data stored in the first memory, the artificial intelligence module 22 may assign an identification value of the object. can The second memory may include or store the unique identification number of the object, and the processing unit 20 may match the identification value of the object stored in the first memory 52 with the unique identification number of the object stored in the second memory. . The unique identification number matched in the above manner may be stored in the second memory 54 . The processing unit 20 may specify the object or confirm the user's specific ID based on the identification value of the object in the second memory 54 and the MatchOdin unique identification number. This specific ID matching or tagging function may be performed automatically or manually.

According to an embodiment, the identification of a person through image analysis may be handled differently according to the number of objects or people. Image images such as fashion, hairstyle, and skin color may be analyzed according to a preset number of objects or people, and an object or a person may be specified accordingly.

The object or person may be tagged as a1, a2, a3, a4, etc. for example, and a person may be specifically represented without being limited thereto by using an appropriate expression method.

4 is a diagram illustrating a method of identifying a person by identifying a person's face according to an exemplary embodiment.

When it is difficult to analyze the object only by analyzing the video image, for example, when there are a plurality of people having similar appearances, the object or the person may be specified by using the distance data of the second sensor. For example, as a method of using distance data, a face may be recognized or a part of the body may be recognized using 3D distance information.

For example, by determining the face of a person, it is possible to tag or distinguish them with symbols such as b1, b2, and b3, but is not limited thereto.

5 is a diagram illustrating the movement of a body temperature monitoring robot according to an embodiment.

5 exemplifies the movement of body temperature monitoring, and shows a method for maximizing the efficiency of non-contact body temperature monitoring.

Since the existing non-contact body temperature monitoring has a limited field of view or measurement range in a fixed place, it is possible to measure objects existing in various places and locations through the movement of the robot.

In addition, when the distance of the object to be observed is long, accurate thermal image data or temperature data cannot be measured, and an error occurs. Therefore, the robot can move to a close distance to the measurement object and perform body temperature monitoring.

Illustratively, the body temperature monitoring robot periodically traverses a space where people to be observed are gathered, and people can check their body temperature. In the body temperature measurement process, the image, distance, and temperature data included in the measurement unit 10 may be transmitted to the processing unit 20 to calculate a more accurate temperature distribution.

For example, the processing unit 20 may calculate the temperature data of the second memory 54 based on the distance data of the first memory 52 .

6 is a view for explaining an error generation method for each distance of a thermal imaging camera and a method of improving the error.

Referring to FIG. 6 , the error of temperature data according to the distance of the object 200 in (A) is described. The accuracy of the temperature data measured by the temperature measuring unit 16 increases as the distance between the objects increases, and the accuracy decreases or the error increases as the distance between the objects increases.

According to an embodiment, in order to increase accuracy or reduce errors, the distance data of the distance measuring unit 14 and the temperature data of the temperature measuring unit 16 are correlated or compared to appropriately perform calibration. Needs to be. For example, a distance of a target object may be measured using a depth camera or a 3D camera, and an error in a temperature measurement value according to the distance may be compensated.

According to an embodiment, in order to increase accuracy or decrease error, it is necessary to move the distance of the distance measuring unit 14 closer to the object 200 . Illustratively, the robot may be moved by operating the driving unit 40 of the body temperature monitoring robot in such a way that the distance of the measuring unit 14 is close to the object 200 . When the robot moves close to the target, more accurate temperature data can be obtained.

7 is a diagram illustrating a first method for correcting an error of a thermal imaging camera.

Referring to FIG. 7 , a method for correcting an error in temperature data of the third sensor may be confirmed. For example, the third sensor may be a thermal imaging camera.

In the first method for correcting the error, a plurality of body temperature monitoring robots may be used. As a method of increasing or correcting the reliability of temperature data measured by one body temperature monitoring robot, cross-validation can be performed by receiving the temperature value measured inside a separate body temperature monitoring robot.

According to one embodiment, the separate body temperature monitoring robot may measure its own temperature by a sensor disposed inside or outside the separate body temperature monitoring robot, and in this case, the temperature is measured in a short distance to calculate the accurate temperature. . The temperature measurement value measured by a separate body temperature monitoring robot can be used as a reference point used for calibration or determination of measurement accuracy.

According to an embodiment, the processing unit 20 may calibrate the temperature data of the second sensor or determine the reliability of the measured temperature data based on a temperature measurement value transmitted from a separate body temperature monitoring robot. In this case, the difference in the numerical range can be confirmed by comparing the actual temperature data that the robot measured the surface of the separate body temperature monitoring robot with the temperature measured value measured by the separate body temperature monitoring robot. For example, when the actual temperature data is greater than the reference value, the difference from the actual temperature data may be corrected.

Illustratively, the correction method of the actual temperature data and the reference value may be corrected by adding or subtracting only the difference value, linearly internalizing, or deriving a non-linear function, and may be corrected through a preset algorithm.

The number of times of comparing the actual temperature data and the reference value may be a plurality of times. When a plurality of data is used, the deviation of the difference between the actual temperature data and the reference value can be reduced, or it can be applied to a more accurate optimization model. If necessary, correction may be performed by averaging a plurality of data.

The above method is a method for cross-verifying the reliability of temperature data measured by another body temperature monitoring robot based on the reliability of the temperature measurement value measured by the separate body temperature monitoring robot according to an embodiment.

In another embodiment, the temperature data may be verified or corrected by using the calculated value of a specific object rather than the surface of a separate body temperature monitoring robot. For example, by measuring the temperature of an object existing in an intermediate position between the two robots, the difference value may be corrected. As another example, each robot measures the same distance when measuring the temperature of another robot, and the difference value can be corrected.

In another embodiment, accuracy of temperature measurement may be verified or an error may be corrected by using an object located in space as a reference point.

Data accumulated in the error correction or verification process through a plurality of body temperature monitoring robots are stored in a server (not shown) and used to increase the reliability of measurement, or are stored in an internal storage device or data unit 50 and repeatedly can be used For example, the above data may be used in the machine learning process of the artificial intelligence module.

8 is a diagram illustrating a second method for correcting an error of a thermal imaging camera.

Referring to FIG. 8 , the body temperature monitoring robot 100 may measure a separate object serving as a reference point other than the object 200 . Illustratively, the separate object may be the blackbody 220 . The blackbody is an object having a specific temperature, and may serve as a reference point for correcting an error occurring in measuring the object, and may be used to verify the accuracy of temperature data measured by the third sensor.

9 is a block diagram illustrating a method of monitoring the temperature of an object according to an embodiment.

10 is a block diagram illustrating a method of checking an environment variable according to an embodiment.

11 is a block diagram illustrating a method of determining whether a body temperature is normal based on a reference value of an environmental variable according to an exemplary embodiment.

9 to 11 , a method of monitoring the body temperature of an object can be confirmed.

In the method 1000 for monitoring body temperature using the artificial intelligence module 22 and the environment module 24, the artificial intelligence module 22 analyzes image data to specify a person when the number of measured objects is less than or equal to a reference value. Step (S1010), when the degree of similarity of the appearance of the measured object is greater than or equal to the reference value, analyzing the distance data to specify the person (S1020) and determining whether the body temperature is normal based on preset environmental variables (S1050) may include In the body temperature monitoring method 1000 , the environment module 24 may include measuring a preset environmental variable ( S1040 ) and comparing the measured temperature data of the object with a preset environmental variable ( S1050 ).

The environmental variable check step (S1040) may include one or more of the ambient temperature check step (S1041), the density check step (S1043), the air conditioner operation check step (S1045), and the other environmental variable check step (S1047), but the sequence is not limited to

The body temperature determination step ( S1050 ) may include one or more of an environmental variable input step ( S1051 ), a reference value comparison step ( S1053 ), and an alarm step ( S1060 ), but the order is not limited.

As for the other environmental variables, one or more of the humidity of the surrounding environment, the wind speed of the surrounding environment, the presence or absence of rain, the season, the existence of a heat source nearby, the intensity of sunlight, and the concentration of carbon dioxide may be selected.

According to an exemplary embodiment, based on the calculated environment variable, it may be checked whether the body temperature is normal, and it may be determined whether the body temperature exceeds a reference value. An object or person having a body temperature exceeding the reference value may be identified as a heating element and an alarm may be generated.

12 is a block diagram illustrating a method of correcting measured temperature data based on received temperature data according to an embodiment.

Referring to FIG. 12 , the temperature data correction method 1100 may include a separate robot internal temperature data reception step S1110 , a temperature data comparison step S1120 , and a temperature data correction step S1130 .

In the method for monitoring body temperature of a plurality of body temperature monitoring robots according to an embodiment, reliability can be verified when receiving internal temperature data of separate robots and the temperature measurement value of the third sensor is the same as the received temperature reception value and, if they are not the same, the temperature data of the third sensor may be corrected.

According to an embodiment, a temperature value measured by a separate robot can be received to verify the measured value of its own temperature data, and when its own temperature measured value and the received received value are the same, the reliability of data measurement is determined can do. If the own temperature measurement value and the received value are different, calibration may be performed to improve data measurement accuracy and reduce errors.

100: temperature monitoring robot
10: measurement unit
12: image measurement unit
14: distance measuring unit
16: temperature measuring unit
20: processing unit
22: AI module
30: output unit
32: image unit
34: sound unit
36: alarm unit
40: drive unit
42: robot moving unit
44: robot control unit
50: data part
52: first memory
54: second memory
200: measurement object
220: black body
1000: temperature monitoring method
S1010: image analysis step
S1020: Distance analysis step
S1030: temperature analysis step
S1040: Environment variable check step
S1041: Ambient temperature check step
S1043: density check step
S1045: Checking the operation of the air conditioner
S1047: Checking other environment variables
S1050: body temperature determination step
S1051: Environment variable input step
S1053: reference value comparison step
S1060: Alarm stage
1100: Temperature data calibration method
S1110: Step of receiving internal temperature data of a separate robot
S1120: temperature data comparison step
S1130: temperature data calibration step

Claims (13)

a measurement unit including a first sensor, a second sensor, and a third sensor for generating image, distance, and temperature data of an object;
a control unit for controlling the robot based on the data of the measurement unit;
a processing unit for receiving a signal from the control unit and processing data calculation, the processing unit including an artificial intelligence module and an environment module;
an output unit including an image unit displaying the temperature of the object measured by the third sensor; and
It includes a data unit for storing the data of the measurement unit,
The artificial intelligence module tags and stores an ID for specifying the object based on the image data measured by the first sensor of the measurement unit,
The environment module determines the temperature of the surrounding environment, the density of people, and whether the air conditioner is operating as a preset environmental variable,
The processing unit compares the environmental variable with the temperature data to determine whether the object is at a normal temperature, body temperature monitoring robot. ◈Claim 2 was abandoned when paying the registration fee.◈ According to claim 1,
The processing unit checks the data of a preset environment variable, and selects the data of the measurement unit according to a preset reference value based on the data of the environment variable,
The environmental variable preset in the environment module further includes at least one of humidity of the surrounding environment, wind speed of the surrounding environment, the presence of rain, the season, the presence of a surrounding heat source, the intensity of sunlight, and the concentration of carbon dioxide. According to claim 1,
The processing unit includes a first memory and a second memory,
The processing unit measures the distance data of the first memory, and measures the temperature data of the second memory only when the object is within a predetermined distance, body temperature monitoring robot. According to claim 1,
The third sensor placed in the body temperature monitoring robot produces temperature data and stores it in the data unit,
A body temperature monitoring robot that transmits the temperature data to a separate body temperature monitoring robot for temperature data calibration and verifies the temperature data of the third sensor by comparing it with a temperature measurement value of the separate body temperature monitoring robot. According to claim 1,
The processing unit compares the received temperature value received from the separate body temperature monitoring robot with the temperature data of the third sensor, and corrects the temperature data of the third sensor when the received temperature value and the temperature data are not the same ), a body temperature monitoring robot. ◈Claim 6 was abandoned when paying the registration fee.◈ According to claim 1,
The third sensor disposed on the arm of the robot sets reference temperature data by measuring the wavelength of a black body having a specific temperature in advance,
The processing unit corrects the temperature data of the object based on the reference temperature data, the body temperature monitoring robot. According to claim 1,
Further comprising a driving unit for moving the robot,
The control unit operates the driving unit to change the distance between the object and the robot, and collects temperature data for each distance of the object, the body temperature monitoring robot. A method of monitoring body temperature using an artificial intelligence module and an environment module, the method comprising:
The environment module includes the steps of measuring the ambient temperature of the object, the density of people, and whether the air conditioner is operated, which are preset environmental variables,
The artificial intelligence module is
specifying a person by analyzing image data when the number of measured objects is less than or equal to a reference value;
specifying a person by analyzing distance data when the degree of similarity in the appearance of the measured object is greater than or equal to a reference value; and
Comparing preset environmental variables and temperature data, determining whether the body temperature is normal; including; body temperature monitoring method. 9. The method of claim 8,
The artificial intelligence module is
Compensating the image data based on the distance data; further comprising a body temperature monitoring method. 9. The method of claim 8,
The artificial intelligence module is
The body temperature monitoring method further comprising; correcting the temperature data of the object based on the previously measured temperature of the black body. 9. The method of claim 8,
The artificial intelligence module is
The body temperature monitoring method further comprising; calibrating the temperature data measured by a third sensor based on the temperature data measured by a separate body temperature monitoring robot. 12. The method of claim 11,
The separate body temperature monitoring robot includes a temperature sensor disposed inside the robot to measure the internal temperature of the robot,
The artificial intelligence module is
comparing the temperature data measured by the internal temperature sensor of the separate body temperature monitoring robot with the temperature data measured by the second sensor;
calculating a difference between temperature data measured by a temperature sensor inside the separate body temperature monitoring robot and temperature data measured by a second sensor;
calculating a correction value based on a difference between temperature data measured by a temperature sensor inside the separate body temperature monitoring robot and temperature data measured by a second sensor; and
correcting the temperature data measured by the second sensor by applying a correction value calculated based on the difference between the temperature data measured by the temperature sensor inside the separate body temperature monitoring robot and the temperature data measured by the second sensor; Body temperature monitoring method further comprising a. delete

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