CN117481461A - Intelligent child lifting table control system and method capable of identifying sitting postures - Google Patents
Intelligent child lifting table control system and method capable of identifying sitting postures Download PDFInfo
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Abstract
The invention discloses an intelligent child lifting table control system and method capable of identifying sitting postures, and relates to the technical field of office furniture, wherein a lifting table control module is used for controlling the lifting of a table top of a child lifting table through motor driving; the manual control module comprises an input module and an information display module, wherein the input module is used for inputting control instructions, and the information display module is used for displaying the current height of the lifting table and fault information thereof through a nixie tube; acquiring a face image of a user through a face calibration system, extracting face data, and calibrating the face of the user through image processing; the sitting posture identification system identifies the sitting postures of the user according to the collected sitting posture pictures and classifies the sitting postures; the voice broadcasting module carries out voice reminding on a user when the user has bad sitting posture or keeps the same sitting posture for a long time. The invention can automatically adjust the height of the lifting table, monitor the sitting position of the user in real time and remind the user to correct the sitting position through voice.
Description
Technical Field
The invention relates to the technical field of office furniture, in particular to an intelligent child lifting table control system and method capable of identifying sitting postures.
Background
In recent years, students with Chinese myopia are gradually aged down, the number of people is increased, and according to data, the majority of the students with Chinese myopia are shown to be students, and the reason for the myopia of the students is that the sitting posture of the students is not standard during learning; meanwhile, poor sitting postures can cause non-negligible harm to the parts of the spine, neck, legs, buttocks, back and the like of students. Therefore, the method has important significance for researching sitting posture detection.
At present, the research on the human body posture detection method at home and abroad mainly has two directions: one is sensor-based contact gesture detection and the other is image processing-based gesture detection. The contact type gesture detection based on the sensor is convenient and reliable in data acquisition, but the accuracy is influenced by factors such as sensor hardware, noise and environment in a signal transmission process, and the like, and a human body is generally required to be contacted. The gesture detection based on image processing has the characteristics of non-contact, not only has small constraint feeling, but also has the advantages that the processing capacity of the image reaches a new height along with the acceleration of the running speed of a processor and a display card, is relatively stable, is less influenced, but can be influenced by factors such as environment, equipment, algorithm and the like.
Therefore, there is a need for an intelligent child lift table that can identify a sitting posture, automatically adjust the height of the table, monitor the sitting posture of a user in real time, and prompt the user when a bad sitting posture occurs.
Disclosure of Invention
The invention aims to provide an intelligent child lifting table system and method capable of identifying sitting postures, which can automatically adjust the required height, monitor the sitting postures of a user in real time and remind the user of correcting the sitting postures through voice.
In order to achieve the above object, the present invention provides the following solutions:
an intelligent child lift table control system capable of recognizing sitting postures, comprising: the system comprises a lifting table control system, a face calibration system, a sitting posture recognition system and a voice broadcasting module;
the lifting table control system comprises a lifting table control module and a manual control module, wherein the manual control module comprises an input module and an information display module, the input module is used for inputting control instructions, and the information display module is used for displaying the current height and fault information of the lifting table through a nixie tube; the lifting table control module is connected with the manual control module and is used for controlling the lifting of the tabletop of the lifting table through motor driving according to the control instruction;
the face calibration system comprises a camera module, wherein the camera module is used for collecting face images of a user, extracting face data and calibrating the face of the user through image processing;
the sitting posture identification system is used for collecting sitting posture pictures of the user through the camera module, identifying the sitting postures of the user and classifying the sitting postures;
the voice broadcasting module is connected with the face calibration system and the sitting posture recognition system, and is used for carrying out voice prompt on a user when the user has bad sitting postures or the time for keeping the same sitting postures exceeds the set time and carrying out voice prompt when the lifting table is reset.
Further, the input module includes a set of up control keys and down control keys.
Furthermore, the intelligent child lifting table control system capable of identifying the sitting postures further comprises a feedback module and a client, wherein the feedback module is connected with the sitting posture identification system and used for transmitting the bad sitting postures detected by the sitting posture identification system to the client, dividing the bad sitting postures according to time periods, logging in the client by parents, and checking the sitting posture conditions of the users in real time.
Further, the manual control module is a manual controller, the nixie tube and the input module are integrated in the manual controller, the manual controller is connected with the lifting table control module, and the lifting table control module receives control information of the manual controller and displays the control information in the nixie tube.
Furthermore, the input module comprises a storage key S and three gear keys 1, 2 and 3, and the current lifting table height is stored by clicking the storage key S and clicking the corresponding gear.
Furthermore, the input module further comprises a restarting button, and when the restarting button is pressed, the intelligent child lifting table control system capable of identifying the sitting posture restarts and restarts sitting posture identification and face calibration.
Furthermore, the intelligent child lifting table control system capable of identifying sitting postures further comprises a data analysis module, wherein the data analysis module is used for classifying the stored sitting postures of the user and the sitting postures, counting in a first setting to obtain statistical data, generating a sitting posture analysis report and obtaining health advice; and deleting the statistical data after the statistical data retention reaches the second set time.
The invention also provides a sitting-posture-identifiable intelligent child lifting table control method which is applied to the sitting-posture-identifiable intelligent child lifting table control system and comprises the following steps of:
s1, after a user electrifies the lifting table, an intelligent child lifting table control system capable of identifying sitting postures is started automatically, the lifting table is required to be reset when being used for the first time, the user presses a descending button in an input module for a long time to enable the lifting table to descend to the lowest position, and when the prompting sound of a voice broadcasting module is heard, the lifting table is reset successfully; the lowest position is the lowest height of the lifting table input in advance by the input module;
s2, the camera module starts to work, whether a user sits in front of the lifting table or not is detected, and if the user does not detect the face, the user is reminded of sitting at a proper position in a voice mode;
s3, when a user sits in front of the lifting table for the first time, the camera module collects face images of the user, positions the face of the user through a face positioning algorithm, and the lifting table control module rapidly controls the lifting table to ascend so that the face is located at a preset comfortable height of the sitting posture of the human body, and adjustment is completed; the user inputs a control instruction through the input module to adjust the lifting table to reach the designated height;
s4, after the adjustment of the user is finished, pressing a storage key S, pressing a number corresponding to a gear key on the hand controller, and storing the final height of the lifting table adjusted by the user by the input module;
s5, after the lifting table is adjusted, the lifting table control system closes an automatic adjusting thread, the sitting posture recognition system is opened, and the sitting posture condition of a user is counted in a specified time period; and according to whether the sitting postures of the users are correctly classified, the voice broadcasting module carries out corresponding voice reminding on the bad sitting postures of the users.
Further, the method further comprises:
s6, when the lifting table control system is started, the timing function is started at the same time, when the sitting time of the same user in front of the lifting table exceeds a set threshold value, the user is judged to be in a sedentary state, and at the moment, the user is reminded of rising activities through the voice broadcasting module.
Further, the method further comprises:
s7, when different users sit in front of the lifting table, the height of the lifting table can be redetected and adjusted according to the conditions of the users only by pressing the restarting key;
s8, the data analysis module classifies the stored sitting posture pictures and sitting postures of the user, performs statistics in a first setting to obtain statistical data, generates a sitting posture analysis report and obtains health advice; and deleting the statistical data after the statistical data retention reaches the second set time.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the intelligent child lifting table control system and method capable of identifying sitting postures provided by the invention have the following advantages:
1. the automatic adjusting function is provided, and the position of the table can be automatically adjusted to a proper height according to the actual situation of a user;
2. the sitting posture detecting function is provided, so that the sitting posture of the child can be detected and the voice prompt can be carried out, and parents can be helped to correct the bad sitting posture of the child;
3. through saving the information such as the sitting posture pictures and the sitting posture classification of the user, counting in fixed time, generating a sitting posture analysis report, providing relevant sitting posture health suggestions for parents to reference through long-term sitting posture habit analysis, facilitating parents to correct the sitting posture of children, also guaranteeing that teenagers and children can develop healthily and develop good habits.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a control system for an intelligent child lift table capable of recognizing sitting postures according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a device binding interface according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a device unbinding page according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a device detail display interface according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a sitting posture situation analysis interface according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide an intelligent child lifting table control system and method capable of identifying sitting postures, which can automatically adjust the required height, monitor the sitting postures of a user in real time and remind the user of correcting the sitting postures through voice.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, an intelligent child lifting table control system capable of identifying sitting postures according to an embodiment of the present invention includes: the system comprises a lifting table control system, a face calibration system, a sitting posture recognition system and a voice broadcasting module;
the lifting table control system comprises a lifting table control module and a manual control module, wherein the manual control module comprises an input module and an information display module, the input module is used for inputting control instructions, the information display module is used for displaying the current height and fault information of the lifting table through a nixie tube, and when the lifting table encounters a fault, the corresponding error information is displayed for overhauling; the lifting table control module is connected with the manual control module and is used for controlling the lifting of the tabletop of the lifting table through motor driving according to the control instruction;
the face calibration system comprises a camera module, wherein the camera module is used for collecting face images of a user, extracting face data and calibrating the face of the user through image processing; in this embodiment, the camera module may be used to collect face images of each user, process the collected face images through OpenCV software, calculate the distance ratio between the face and the frame in the face images, determine the center position of the face and perform calibration, for example, use the camera fixed in front of the table to take a photograph and sample different users, then perform geometric operations such as horizontal overturn and vertical overturn on the collected images to enhance the data, because each collected photo has the same size, and determine the center position of the face and perform calibration by calculating the distance ratio between the face and the frame.
The sitting posture identification system is used for acquiring sitting posture pictures of the user through the camera module, identifying the sitting postures of the user through judgment of the algorithm model, and classifying according to different sitting postures; the sitting posture picture acquired by the camera module is used for detecting the sitting posture by using a neural network algorithm, so that the accuracy of the sitting posture detection is greatly improved, and the complexity and the singleness of the traditional hardware sitting posture detection are optimized. In this embodiment, the algorithm model may be a sitting posture detection model based on the yolov2 target detection algorithm.
The voice broadcasting module is connected with the face calibration system and the sitting posture recognition system, and is used for carrying out voice prompt on a user when the user has bad sitting postures or keeps the same sitting postures for more than a set time, and carrying out voice prompt when the lifting table is reset.
In this embodiment, the intelligent child lifting table control system capable of identifying sitting postures further comprises: the external detection system comprises an infrared detection module and an illumination detection module; the infrared detection module is used for emitting infrared radiation through the infrared sensor, detecting whether a user exists in front of the table, and if the user is detected to be out of the seat (such as leave the seat), the whole intelligent child lifting table control system can be dormant. The illumination detection module is connected with the voice broadcasting module and is used for detecting the intensity of light of the environment where the desk is located, and if the light of the environment where the desk is located is detected to be higher than or lower than a set value, a user can be reminded of adjusting the light intensity through the voice broadcasting module. In a further embodiment, the infrared detection module comprises an infrared sensor, and the infrared sensor emits infrared radiation to detect whether a user exists in front of the desk; the illumination detection module comprises an illumination sensor, and the intensity of light of the environment where the desk is located is detected through the illumination sensor.
In this embodiment, the input module includes a set of up control keys and down control keys; the user can manually adjust the height of the table through the two keys, and the current height of the table can be displayed on the nixie tube in real time.
In this embodiment, the intelligent child lifting table control system capable of identifying sitting postures further includes a data analysis module, configured to count stored information such as sitting posture pictures and sitting posture classifications of the user in a first set time to obtain statistical data, such as daily sitting posture duration statistics, different sitting posture occupation ratios, and the like, so that all sitting postures can be classified more carefully, a sitting posture analysis report is generated, and health advice is obtained; and deleting the statistical data after the statistical data retention reaches the second set time.
In this embodiment, the intelligent child lifting table control system capable of identifying sitting postures further includes a feedback module and a client, where the feedback module is connected with the sitting posture identifying system, and is configured to transmit the bad sitting postures detected by the sitting posture identifying system to the client, divide the bad sitting postures according to time periods, log in the client by parents, and view the sitting posture situation of the user in real time, as shown in fig. 5.
In a further embodiment, as shown in fig. 2-4, the data analysis module, the feedback module and the client may be integrated in a cloud applet, when the device is in a networking state, the system may transmit all detected incorrect sitting postures to the cloud end through Wi-Fi signals, and divide the detected incorrect sitting postures according to time periods, so that parents can grasp sitting postures of children in real time on the applet; the user can register user information on a small program matched with the intelligent child table and can be associated with the mobile phone number and WeChat of the user. The user can bind the purchased equipment number of the lifting table in the binding page of the cloud applet and associate the lifting table with the user information. The device networking is needed before binding, a user fills in the WIFI name and the password, then a two-dimensional code is generated, a user identity key is arranged in the two-dimensional code, information is read after the device scans the code, on one hand, the WIFI connection is carried out, on the other hand, a binding request is sent to the cloud, and the binding of the device and the user is achieved. The cloud end stores the pictures and the analysis results, and the picture data are deleted after exceeding one week; the data analysis module can fix time statistic data, and the statistic data can be maintained for a long time and then deleted.
Through networking and uploading all data information to the cloud applet, sitting postures can be more accurately classified, and meanwhile, the running load of local hardware is reduced. The cloud applet can generate a sitting posture analysis report, and can provide relevant sitting posture health suggestions for parents to reference through long-term sitting posture habit analysis, so that the parents can conveniently correct the sitting posture of the child, and the teenager child can be healthily developed to form good habits.
In this embodiment, the manual control module is a manual controller, the nixie tube and the input module are integrated in the manual controller, the manual controller is connected with the lifting table control module, and the lifting table control module receives the control information of the manual controller and displays the control information in the nixie tube.
In this embodiment, the input module includes a storage key "S" and three gear keys "1", "2" and "3", and by clicking the storage key "S" and then clicking the corresponding gear, the current lifting table height is stored.
In this embodiment, the input module further includes a restart button, where when the restart button is pressed, the intelligent child lifting table control system capable of identifying the sitting posture restarts and restarts sitting posture identification and face calibration, and the lifting table also automatically adjusts according to the new face position, and the restart button does not restart the lifting table power supply.
In this embodiment, the sitting posture includes: askew sitting, low head, bending over, humpback, etc.
Example 2
The embodiment provides a sitting-posture-identifiable intelligent child lifting table control method, which is applied to the sitting-posture-identifiable intelligent child lifting table control system and comprises the following steps:
s1, after the lifting table is electrified, an intelligent child lifting table control system capable of identifying sitting postures is started automatically, the lifting table is required to be reset when being used for the first time, a user presses a descending button in an input module for a long time to enable the lifting table to descend to the lowest position, and when the prompting sound of a voice broadcasting module is heard, the lifting table is reset successfully; the lowest position is the lowest height of the lifting table input in advance by the input module;
s2, the camera module starts to work, whether a user sits in front of the lifting table or not is detected, and if the user does not detect the face, the user is reminded of sitting at a proper position in a voice mode;
s3, when a user sits in front of the lifting table for the first time, the camera module collects face images of the user, positions the face of the user through a face positioning algorithm, and the lifting table control system rapidly controls the lifting table to ascend so that the face is located at a preset comfortable height of the sitting posture of the human body, and adjustment is completed; the user inputs a control instruction through the input module to adjust the lifting table to reach the designated height;
s4, after the adjustment of the user is finished, pressing a storage key S, pressing a corresponding number on the hand controller, and storing the final height of the lifting table adjusted by the user by the input module;
s5, after the lifting table is adjusted, the lifting table control system closes an automatic adjusting thread, the sitting posture recognition system is opened, and the sitting posture condition of a user is counted in a specified time period; and according to whether the sitting postures of the users are correctly classified, the voice module carries out corresponding voice reminding on the bad sitting postures of the users.
In this embodiment, the step S1 further includes:
s1.1, a user registers user information on a cloud applet matched with a lifting table (namely a sitting lifting check cloud applet) and can be related to a user account number, such as a mobile phone number, a WeChat and the like;
s1.2, the user can bind the purchased equipment number of the lifting table in the binding page of the applet and associate the lifting table with the user information. Before binding, networking is needed to be conducted on equipment, a user fills in a WIFI name and a password, then a two-dimensional code is generated, a user identity key is arranged in the two-dimensional code, and networking information and customer information are read after the equipment scans the code: and performing WIFI connection, and sending a binding request to the cloud to realize the binding of the equipment and the user.
In this embodiment, the method further includes:
after the intelligent child lifting table control system capable of recognizing sitting postures is started automatically, whether a user is in front of the table or not is detected in real time through the infrared detection module, and when the user is detected to be not in a seat, the whole intelligent child lifting table control system can be dormant. The light intensity of the environment where the desk is located is detected in real time through the illumination detection module, and if the light intensity of the environment where the desk is located is detected to be higher or lower than a set value, a user is reminded of adjusting the light intensity through the voice broadcasting module.
In this embodiment, the method further includes:
s6, when the lifting table control system is started, the timing function is started at the same time, when the sitting time of the same user in front of the lifting table exceeds a set threshold value, the user is judged to be in a sedentary state, and at the moment, the user is reminded of rising activities through the voice module.
In this embodiment, the method further includes:
s7, when different users sit in front of the table, the height of the lifting table can be redetected and adjusted according to the conditions of the users by only pressing a restarting key;
s8, the data analysis module counts the stored information such as sitting posture pictures and sitting posture classifications of the user in a fixed time to obtain statistical data, generates a sitting posture analysis report and obtains health advice; the statistical data is maintained for a long time and then deleted;
in this embodiment, when the device is in a networking state, the system transmits all detected incorrect sitting postures to the cloud through Wi-Fi signals, and classifies the detected incorrect sitting postures according to time periods, so that parents can grasp the sitting postures of children in real time on a small program.
In the embodiment, S5, after the lifting table is adjusted, the lifting table control system closes an automatic adjusting thread, the sitting posture recognition system is opened, and the sitting posture condition of a user is counted in a specified time period; and according to whether the sitting posture of the user is correctly classified, the voice module carries out corresponding reminding voice on the bad sitting posture of the user, and the voice module specifically comprises the following steps:
after the automatic adjustment of the lifting table is finished, the system can close the automatic adjustment thread, then the sitting posture detection system can be started, and the system can count the sitting posture condition of the user within the period of time every 5 minutes; the sitting posture detection algorithm is adopted to detect whether the user sits correctly or not, if the user sits incorrectly, the user can classify the incorrect sitting postures, the system carries out voice reminding through the voice broadcasting module, different incorrect sitting postures have corresponding reminding voices, the existing algorithm can divide the incorrect sitting postures into 'low head' and 'askew sitting', and the like, and various classifications can be added according to requirements.
In this embodiment, the method further includes: the data analysis module can store information such as sitting position pictures and analysis results through a cloud, the picture data are deleted after exceeding one week, and the statistical data can be maintained for a long time and then deleted. Through a high-precision sitting posture detection algorithm integrated in a cloud applet, carrying out careful classification on all sitting postures, generating a sitting posture analysis report, displaying sitting posture condition statistical results in different chart forms, including daily sitting posture duration statistics, different sitting posture ratios and the like, and obtaining practical health suggestions through data analysis.
In summary, the intelligent child lifting table control system and method capable of identifying sitting postures can automatically adjust the table position to a proper height according to the actual situation of a user, and help parents to correct the bad sitting postures of children by detecting the sitting postures of the children and prompting by voice; the camera is used for collecting pictures and then the pictures are subjected to a neural network algorithm to detect the sitting posture, so that the accuracy of detecting the sitting posture is greatly improved, and the complexity and the singleness of detecting the sitting posture by the traditional hardware are optimized; under the condition of networking, the cloud end can upload the data information, meanwhile, sitting postures can be more accurately classified, and the running load of local hardware is reduced. The cloud applet can generate a sitting posture analysis report, and can provide relevant sitting posture health suggestions for parents to reference through long-term sitting posture habit analysis, so that the parents can conveniently correct the sitting posture of the child, and the teenager child can develop healthily and develop good habits.
In the other technical features of the embodiment, those skilled in the art can flexibly select to meet different specific actual requirements according to actual conditions. However, it will be apparent to one of ordinary skill in the art that: no such specific details are necessary to practice the invention. In other instances, well-known compositions, structures, or components have not been described in detail so as not to obscure the invention, and are within the scope of the invention as defined by the appended claims.
Modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the invention as defined by the appended claims. In the above description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that: no such specific details are necessary to practice the invention. In other instances, well-known techniques, such as specific construction details, operating conditions, and other technical conditions, have not been described in detail in order to avoid obscuring the present invention.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. Intelligent child lifting table control system capable of identifying sitting postures, which is characterized by comprising: the system comprises a lifting table control system, a face calibration system, a sitting posture recognition system and a voice broadcasting module;
the lifting table control system comprises a lifting table control module and a manual control module, wherein the manual control module comprises an input module and an information display module, the input module is used for inputting control instructions, and the information display module is used for displaying the current height and fault information of the lifting table through a nixie tube; the lifting table control module is connected with the manual control module and is used for controlling the lifting of the tabletop of the lifting table through motor driving according to the control instruction;
the face calibration system comprises a camera module, wherein the camera module is used for collecting face images of a user, extracting face data and calibrating the face of the user through image processing;
the sitting posture identification system is used for collecting sitting posture pictures of the user through the camera module, identifying the sitting postures of the user and classifying the sitting postures;
the voice broadcasting module is connected with the face calibration system and the sitting posture recognition system, and is used for carrying out voice prompt on a user when the user has bad sitting postures or the time for keeping the same sitting postures exceeds the set time and carrying out voice prompt when the lifting table is reset.
2. An intelligent child lift table control system that recognizes a sitting position according to claim 1, wherein the input module comprises a set of up control keys and down control keys.
3. The intelligent child lifting table control system capable of identifying sitting postures according to claim 1, further comprising a feedback module and a client, wherein the feedback module is connected with the sitting posture identification system and is used for transmitting the bad sitting postures detected by the sitting posture identification system to the client, dividing the bad sitting postures according to time periods, logging in the client by parents, and checking sitting postures of users in real time.
4. The intelligent child lifting table control system capable of identifying sitting postures according to claim 1, wherein the manual control module is a manual controller, the nixie tube and the input module are integrated in the manual controller, the manual controller is connected with the lifting table control module, and the lifting table control module receives control information of the manual controller and displays the control information in the nixie tube.
5. The intelligent child lifting table control system capable of identifying sitting postures according to claim 1, wherein the input module comprises a storage key "S" and three gear keys "1", "2" and "3", and the current lifting table height is stored by clicking the storage key "S" and clicking the corresponding gear.
6. The intelligent child lift table control system of claim 1, wherein the input module further comprises a restart button, and wherein the intelligent child lift table control system of claim 1 restarts and restarts the position recognition and face calibration when the restart button is pressed.
7. The intelligent child lift table control system capable of recognizing sitting postures according to claim 1, further comprising a data analysis module for classifying the stored sitting postures and sitting postures of the user, counting in a first set time to obtain statistical data, generating a sitting posture analysis report, and obtaining health advice; and deleting the statistical data after the statistical data retention reaches the second set time.
8. A sitting-identifiable intelligent child lifting table control method applied to the sitting-identifiable intelligent child lifting table control system according to any one of claims 1-7, comprising the following steps:
s1, after a user electrifies the lifting table, an intelligent child lifting table control system capable of identifying sitting postures is started automatically, the lifting table is required to be reset when being used for the first time, the user presses a descending button in an input module for a long time to enable the lifting table to descend to the lowest position, and when the prompting sound of a voice broadcasting module is heard, the lifting table is reset successfully; the lowest position is the lowest height of the lifting table input in advance by the input module;
s2, the camera module starts to work, whether a user sits in front of the lifting table or not is detected, and if the user does not detect the face, the user is reminded of sitting at a proper position in a voice mode;
s3, when a user sits in front of the lifting table for the first time, the camera module collects face images of the user, positions the face of the user through a face positioning algorithm, and the lifting table control system rapidly controls the lifting table to ascend so that the face is located at a preset comfortable height of the sitting posture of the human body, and adjustment is completed; the user inputs a control instruction through the input module to adjust the lifting table to reach the designated height;
s4, after the adjustment of the user is finished, pressing a storage key S, pressing a number corresponding to a gear key on the hand controller, and storing the final height of the lifting table adjusted by the user by the input module;
s5, after the lifting table is adjusted, the lifting table control system closes an automatic adjusting thread, the sitting posture recognition system is opened, and the sitting posture condition of a user is counted in a specified time period; and according to whether the sitting postures of the users are correctly classified, the voice broadcasting module carries out corresponding voice reminding on the bad sitting postures of the users.
9. A method of intelligent child lift table control capable of recognizing a sitting posture according to claim 8, further comprising:
s6, when the lifting table control system is started, the timing function is started at the same time, when the sitting time of the same user in front of the lifting table exceeds a set threshold value, the user is judged to be in a sedentary state, and at the moment, the user is reminded of rising activities through the voice broadcasting module.
10. A method of intelligent child lift table control capable of recognizing a sitting posture according to claim 8, further comprising:
s7, when different users sit in front of the lifting table, the height of the lifting table can be redetected and adjusted according to the conditions of the users only by pressing the restarting key;
s8, the data analysis module classifies the stored sitting posture pictures and sitting postures of the user, counts the sitting postures in a first set time to obtain statistical data, generates a sitting posture analysis report and obtains health advice; and deleting the statistical data after the statistical data retention reaches the second set time.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117981965A (en) * | 2024-04-07 | 2024-05-07 | 圣奥科技股份有限公司 | Control method and system for office table and chair |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117981965A (en) * | 2024-04-07 | 2024-05-07 | 圣奥科技股份有限公司 | Control method and system for office table and chair |
| CN117981965B (en) * | 2024-04-07 | 2024-06-11 | 圣奥科技股份有限公司 | Control method and system for office table and chair |
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