A computer for preventing game addiction

Abstract

The application discloses an anti-addiction computer, which comprises a monitoring module, a storage module, a processing module and an output module, wherein the monitoring module is used for monitoring the program running state of the computer, the sitting posture of the user and the distance between the user and the screen; the processing module is used for analyzing and operating the information obtained by the monitoring module, and controlling the program running state and the brightness of the screen to prevent the user from being addicted; through the above manner, the application can set the limiting time for various programs according to the actual situation of the user, and has stronger pertinence and flexibility; and the brightness of the screen is controlled according to the distance between the user and the screen and the sitting posture of the user, so as to guide the user to independently keep the correct distance and sitting posture, thereby helping the minors to form good computer use habits, protecting the physical and mental health of the minors, and having high economic and social values.

Description

TECHNICAL FIELD

[0001] The present application relates to the computer technical field, in particular to a computer for preventing addiction. BACKGROUND

[0002] With the development of science and technology and the progress of society, computers and the Internet have rapidly spread and have become an essential part of people's daily life. While computers bring convenience to people's work and life, their rich entertainment options also make many people addicted, especially minors. For minors whose physical and psychological development is not yet mature, computer addiction not only affects their learning and life, but also leads to vision decline, mental fatigue, hunchback and other problems, which pose a serious threat to the physical health of minors. Therefore, in order to protect the physical and mental health of minors, various anti-addiction products have emerged.

[0003] Currently, the commonly used anti-addiction computer mainly uses a timer to count time, sends an alarm when the set time is reached, and controls the computer start switch to turn off the computer, thereby achieving the effect of preventing addiction. However, this method directly turns off the computer, which can adversely affect the working performance and service life of the computer. Moreover, this method only controls the use time and does not limit the use posture, which cannot effectively solve the problems of vision decline, hunchback and other problems caused by improper sitting posture.

[0004] Therefore, the patent with publication number CN106327811A provides a computer anti-addiction device that prevents addiction by turning off the computer network card when the limited time is reached, solving the problem of performance impact caused by directly turning off the computer. It also controls the user's sitting posture and the distance from the user's face to the screen through the use of a camera and an infrared distance sensor, solving the problem of not limiting the use posture. However, this patent uses a fixed time limit of 2 hours for minors and 3 hours for adults when preventing addiction, which is too single and lacks flexibility. When the use time exceeds the limit, it only prevents the user from being addicted to the network by disconnecting the network, but the user can still use single-player games and other applications that do not require a network, and the computer addiction problem has not been substantially solved. At the same time, when the camera and infrared distance sensor are used to control the user's sitting posture and the distance from the user's face to the screen, only the state that does not meet the standard is alarmed through a prompt sound, and the user can ignore the reminder by turning off the sound, making the actual control effect unsatisfactory. Therefore, it is still necessary to study a more reasonable and effective anti-addiction computer to guide minors to use the computer correctly and protect their physical and mental health. SUMMARY

[0005] The computer for preventing indulgence in the application is characterized in that: the computer for preventing indulgence in the application comprises a monitoring module, a storage module, a processing module and an output module, the monitoring module, the storage module and the output module are connected with the processing module, the output module comprises a screen, the monitoring module comprises a program monitoring unit, a camera and a distance sensor, which are used for monitoring the running state of the program, the sitting posture of the user and the distance between the user and the screen respectively, the processing module comprises a calculation submodule and a control submodule, the calculation submodule is connected with the monitoring module through the control submodule, is used for analyzing and calculating the information obtained by the monitoring module and outputting the result to the control submodule, and the control submodule is connected with the monitoring module, the storage module, the output module and the calculation submodule respectively, is used for controlling the running of the modules, and controls the running state of the program and the brightness of the screen to prevent the user from indulging.

[0006] To achieve the above object, the technical scheme adopted by the application is:

[0007] The computer for preventing indulgence in the application is characterized in that: the computer for preventing indulgence in the application comprises a monitoring module, a storage module, a processing module and an output module, the monitoring module, the storage module and the output module are connected with the processing module, the output module comprises a screen, the monitoring module comprises a program monitoring unit, a camera and a distance sensor, which are used for monitoring the running state of the program, the sitting posture of the user and the distance between the user and the screen respectively, the processing module comprises a calculation submodule and a control submodule, the calculation submodule is connected with the monitoring module through the control submodule, is used for analyzing and calculating the information obtained by the monitoring module and outputting the result to the control submodule, and the control submodule is connected with the monitoring module, the storage module, the output module and the calculation submodule respectively, is used for controlling the running of the modules, and controls the running state of the program and the brightness of the screen to prevent the user from indulging.

[0008] Further, the camera is arranged at the top middle part of the screen and is used for collecting the sitting posture image information of the user, and the distance sensor is arranged at the bottom middle part of the screen and is used for detecting the distance between the user and the screen.

[0009] Further, the program monitoring unit comprises a program identification layer and a time acquisition layer, the program identification layer is used for identifying the program currently started, and the time acquisition layer is used for acquiring the time point at which the program displays the operation interface, the time point at which the program switches to the background running and the time point at which the program is closed.

[0010] Further, the control submodule comprises a main control unit, a setting unit, a program control unit and a screen brightness adjusting unit, the setting unit, the program control unit and the screen brightness adjusting unit are connected with the main control unit respectively, and control the parameter setting of the computer, the program running and the screen brightness respectively.

[0011] Further, the operation sub-module comprises an addiction state analysis unit, a sitting posture recognition unit and a distance recognition unit; the addiction state analysis unit is configured to count the program running data monitored by the program monitoring unit, and analyze the current addiction state of the user and the future trend thereof; the sitting posture recognition unit is configured to analyze and recognize the image information collected by the camera, and determine whether the sitting posture of the user meets the requirements; the distance recognition unit is configured to recognize the distance information collected by the distance sensor, and determine whether the distance between the user and the screen meets the requirements.

[0012] Further, the addiction state analysis unit comprises an operation duration calculation layer, a data statistical layer, a trend prediction layer and a threshold adjustment layer; the operation duration calculation layer is configured to calculate the actual operation duration of each application program in the running process without background running time, and transmit the same to the data statistical layer; the data statistical layer is configured to receive the duration data output by the operation duration calculation layer and perform statistics, and transmit the same to the trend prediction layer; the trend prediction layer is configured to predict the development trend of the use duration of each application program and the computer login duration, so as to determine the addiction state and transmit the same to the threshold adjustment layer; the threshold adjustment layer is configured to adjust the threshold of each duration according to the addiction state, and transmit the adjusted threshold to the control sub-module.

[0013] Further, the sitting posture recognition unit comprises a contour extraction layer, a sitting posture modeling layer and a sitting posture matching layer; the contour extraction layer is configured to extract the contours of the head, neck and shoulder of the user, and transmit the contour information to the sitting posture modeling layer; the sitting posture modeling layer is configured to establish a coordinate system for the sitting posture contour, and extract the coordinates of the head vertex, and transmit the same to the sitting posture matching layer; the sitting posture matching layer is configured to match the coordinates of the head vertex pixel point with the pre-stored normal coordinates, and determine whether the sitting posture of the user is correct.

[0014] Further, the distance recognition unit comprises a signal processing layer and a distance matching layer; the signal processing layer is configured to amplify the signal input by the distance sensor, convert the same from an analog signal to a digital signal, and then transmit the same to the distance matching layer; the distance matching layer is configured to match the monitored distance data with the pre-set distance threshold, and determine whether the user is within a reasonable distance.

[0015] Further, the operation sub-module further comprises an identity recognition unit; the identity recognition unit is configured to extract the facial features in the image information collected by the camera, and match the same with the facial information in the pre-stored user information, to identify the current user identity; the user information comprises facial information, identity information and permission information.

[0016] Further, the storage module comprises a program storage unit and a data storage unit, respectively used for storing various application programs and data, wherein the data comprises various data generated by the monitoring module, the control sub-module and the operation sub-module during operation.

[0017] Compared with the prior art, the present application has the following beneficial effects:

[0018] 1. The anti-addiction computer can set corresponding time thresholds for various application programs according to the actual situation of the user, and has stronger pertinence and flexibility; meanwhile, the anti-addiction computer can control the brightness of the screen according to the distance between the user and the screen and the sitting posture of the user, thereby guiding the user to maintain the correct distance and sitting posture.

[0019] 2. The anti-addiction computer can match different permissions for minors and their parents respectively, monitor the computer use situation of the minor user, count the actual operation time of each application program, analyze and predict the addiction state of the minor user, and set corresponding time thresholds for various application programs, so as to realize anti-addiction control according to the actual situation of the user; meanwhile, the parents can view the use situation of various application programs of the minor user and the analysis and prediction of the addiction state, and adjust the corresponding time thresholds, thereby further preventing the minor from being addicted to the computer.

[0020] 3. The anti-addiction computer can monitor the distance between the user and the screen and the sitting posture of the user, and control the change of the brightness of the screen; when the distance between the user and the screen is less than a set value or the sitting posture is incorrect, the brightness of the screen is reduced, thereby reducing the use experience of the user and prompting the user to restore the correct distance and correct sitting posture; meanwhile, for the user who does not restore the correct distance and correct sitting posture as required, the brightness of the screen is adjusted to 0, thereby avoiding the user from continuing to use the computer in an improper posture.

[0021] 4. The anti-addiction computer can effectively control the use time of the user and guide the user to maintain a good sitting posture, which is beneficial to help the minors develop good computer use habits and protect the physical and mental health of the minors, and has high economic and social value. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is a principle block diagram of an anti-addiction computer of the present application;

[0023] Figure 2 is a main flowchart of the anti-addiction computer of the present application in use;

[0024] Figure 3 is a flowchart of the anti-addiction computer of the present application for adjusting the brightness of the screen according to the sitting posture of the user;

[0025] Figure 4 This is a flowchart of an anti-addiction computer that adjusts screen brightness based on the distance between the user and the screen according to the present invention. Detailed Implementation

[0026] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby providing a clearer and more explicit definition of the scope of protection of the present invention. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Example

[0028] Please see Figure 1 This invention provides an anti-addiction computer, including a monitoring module, a storage module, a processing module, and an output module. The monitoring module, storage module, and output module are respectively connected to the processing module. The output module includes a screen. The monitoring module includes a program monitoring unit, a camera, and a distance sensor, used to monitor the program's running status, the user's posture, and the distance between the user and the screen, respectively. The processing module includes a calculation submodule and a control submodule. The calculation submodule is connected to the monitoring module through the control submodule, used to analyze and calculate the information acquired by the monitoring module, and output the results to the control submodule. The control submodule is connected to the monitoring module, storage module, output module, and calculation submodule, used to control the operation of each module, and to control the program's running status and the screen's brightness to prevent user addiction.

[0029] The camera is located at the top center of the screen to capture the user's sitting posture image information; the distance sensor is located at the bottom center of the screen to detect the distance between the user and the screen; the program monitoring unit includes a program identification layer and a time acquisition layer, the program identification layer is used to identify the currently launched program, and the time acquisition layer is used to acquire the time point when the program displays the operation interface, the time point when the program switches to background operation, and the time point when the program closes.

[0030] Specifically, the control submodule includes a main control unit, a setting unit, a program control unit, and a screen brightness adjustment unit. The setting unit, program control unit, and screen brightness adjustment unit are respectively connected to the main control unit and control the computer's parameter settings, program operation, and screen brightness.

[0031] The operation sub-module includes an addiction state analysis unit, a sitting posture recognition unit, a distance recognition unit and an identity recognition unit; the addiction state analysis unit is used for statistics on the program running data monitored by the program monitoring unit, and analysis on the current addiction state of the user and its future trend; the sitting posture recognition unit is used for analysis and recognition on the image information collected by the camera, and judgment on whether the sitting posture of the user meets the requirements; the distance recognition unit is used for recognition on the distance information collected by the distance sensor, and judgment on whether the distance between the user and the screen meets the requirements; the identity recognition unit is used for extraction of the facial features in the image information collected by the camera, and matching with the facial information in the pre-stored user information to identify the current user identity; the user information includes facial information, identity information and permission information.

[0032] The addiction state analysis unit includes an operation duration calculation layer, a data statistics layer, a trend prediction layer and a threshold adjustment layer; the operation duration calculation layer is used for calculation of the actual operation duration of each application program in the running process without background running time, and transmission of the same to the data statistics layer; the data statistics layer is used for reception of the duration data output by the operation duration calculation layer and statistics, and transmission of the same to the trend prediction layer; the trend prediction layer is used for prediction of the development trend of the use duration of each application program and the computer login duration, so as to judge the addiction state and transmit the same to the threshold adjustment layer; the threshold adjustment layer is used for adjustment of the threshold of each duration according to the addiction state, and transmission of the adjusted threshold to the control sub-module.

[0033] The sitting posture recognition unit includes a contour extraction layer, a sitting posture modeling layer and a sitting posture matching layer, the contour extraction layer is used for extraction of the contours of the head, neck and shoulder of the user, and transmission of the contour information to the sitting posture modeling layer; the sitting posture modeling layer is used for establishment of a coordinate system for the sitting posture contour, and extraction of the coordinates of the head vertex, and transmission of the same to the sitting posture matching layer; the sitting posture matching layer is used for matching of the coordinates of the head vertex pixel point with the pre-stored normal coordinates to judge whether the sitting posture of the user is correct.

[0034] The distance recognition unit includes a signal processing layer and a distance matching layer, the signal processing layer is used for amplification processing on the signal input by the distance sensor, and conversion of the same from an analog signal to a digital signal, and then transmission to the distance matching layer; the distance matching layer is used for matching of the monitored distance data with the pre-set distance threshold to judge whether the user is within a reasonable distance.

[0035] The storage module includes a program storage unit and a data storage unit, respectively used for storage of various application programs and data, the data includes various data generated in the running process of the monitoring module, the control sub-module and the operation sub-module.

[0036] In combination withFigure 2 When a user uses the anti-addiction computer provided in this embodiment, the camera collects the user's facial information, extracts facial features through the identity recognition unit, and matches them with the facial information stored in the user information in the storage unit to identify the current user's identity and match corresponding permissions. If no matching information is found, the user is prompted to enter information. Users who need to enter information can enter user information through the setting unit according to the prompts. The user information includes facial information, standard sitting posture information, identity information, and permission information, which is stored in the storage module after entry. The facial information and standard sitting posture information are collected by the camera, and the identity information is the ID card number, which is entered through the keyboard. The initial permission information is automatically matched according to the identity information, including login duration, monitoring status, and monitoring result information.

[0037] In this embodiment, the initial allowed usage time for each application is consistent with the allowed login time for the computer. The initial login time for users of different ages is as follows:

[0038] Users under the age of 14 are allowed 1 hour of login time per session, with a total daily login time of 2 hours; users aged 14-18 are allowed 2 hours of login time per session, with a total daily login time of 4 hours; and users aged 18 and above are allowed 4 hours of login time per session, with a total daily login time of 8 hours.

[0039] The login duration mentioned above is only an initial value and can be automatically adjusted based on the user's actual usage. Meanwhile, monitoring for underage users is enabled by default, and they can only view their own monitoring results; underage users cannot modify any of their permissions. Monitoring for adult users is disabled by default, but adult users can view their own and underage users' monitoring results and modify their own and underage users' permissions.

[0040] For users whose user information has been entered and whose monitoring status is enabled, when they use the anti-addiction computer provided in this embodiment, the program monitoring unit monitors the usage status of their various programs, and the camera and distance sensor monitor the user's own status.

[0041] Specifically, the program monitoring unit monitors the user's program running status in real time. It identifies the currently running program through the program identification layer and obtains the time point ta when the program's interface is displayed, the time point tb when the program switches to background operation, and the time point tc when the program closes through the time acquisition layer. This data is then transmitted to the main control unit. The main control unit reads this data and calculates the actual operation time of the application during its operation, excluding background operation time, through the operation duration calculation layer in the addiction state analysis unit. Before the program closes, the current monitoring time point is used as the program closing time point in the calculation. The specific calculation method is as follows:

[0042] Arranging the time points in time sequence, every two a group, if the last remaining single time point, directly discarded; again from each group by the latter time minus the former time to get the operation time length of each group, and cumulative, that is, the actual operation time length of this application program.

[0043] For example, if a program experiences the process of opening, running in the background, opening again, and is still in the opening state, the current monitoring time point is taken as the closing time point, the corresponding time length is arranged in sequence, every two a group, represented as ta1, tb1, ta2 and tc2 in turn, then the actual operation time length of the application t=(tb1-ta1)+(tc2-ta2); if a program experiences the process of opening, running in the background, opening again, running in the background again, and directly closing, the corresponding time length is arranged in sequence, every two a group, represented as ta1, tb1, ta2, tb2 and tc3 in turn, then the actual operation time length of the application t=(tb1-ta1)+(tb2-ta2).

[0044] The operation time length calculation layer calculates the actual operation time length of the application program used by the user in the above manner, which excludes the time occupied by the program running in the background compared with only counting the program running time, and the result is more accurate and reasonable.

[0045] The time length data calculated by the operation time length calculation layer is counted by the data counting layer, which counts the operation time length of each application program every day respectively, and accumulates the operation time length of each application in the same day to obtain the cumulative use time length of the day.

[0046] In the use process of the anti-addiction computer, the user can view the operation time length and the cumulative time length of the current applications, if the operation time length of a certain application program of the user reaches the set threshold value or the cumulative use time length of the user reaches the set threshold value, the main control unit sends an instruction to the program control unit to prompt that the application will be closed, so as to facilitate the user to save relevant data, and forcibly closes the program after 10 minutes to prevent the user from being addicted.

[0047] At the same time, the data counted by the data counting layer every day is predicted by the trend prediction layer, which respectively performs exponential smoothing on the time series of the use time length and the computer login time length of each application program, so as to predict the development trend of each time length and judge the addiction state. Taking a certain application program as an example, the application program has been used for i days, and the use time length of each day is represented as x1-xi in turn, the specific steps of the trend prediction layer for trend prediction and addiction state judgment of the application program are as follows:

[0048] S1.1, with 0.1 as the smoothing coefficient σ, the length of data for the previous i-1 days is three times exponential smoothing, respectively, to get three times exponential smoothing value and The formula is as follows:

[0049]

[0050]

[0051]

[0052] S1.2, according to the calculated three times exponential smoothing value, calculate the prediction parameter a i-1 , b i-1 and c i-1 , and according to the prediction parameter, the length of the i day x′ i is predicted, and the formula is as follows:

[0053]

[0054]

[0055]

[0056] x′ i =a i-1 +b i-1 +c i-1

[0057] S1.3, in the range of 0.1-0.8, according to the step length of 0.01, the smoothing coefficient σ is iterated, and the predicted value x′ i of the length of the i day under different smoothing coefficient σ is calculated according to steps S1.1 and S1.2, and compared with the actual length of the i day xi, the smoothing coefficient corresponding to the predicted value closest to the actual length is selected as the optimal smoothing coefficient, and the length of the i+1 day is predicted according to the same method;

[0058] S1.4, according to steps S1.1-S1.3, the length of the i+2, i+3, i+4 and i+5, i+6 and i+7 days is predicted in turn, so as to obtain the future 7 days of use length prediction value, and compare it with the original length threshold of the application program, if the prediction value of 3-5 days in the 7 days reaches or exceeds the original length threshold, it is judged that the user is in the state of addiction, if the prediction value of more than 5 days in the 7 days reaches or exceeds the original length threshold, it is judged that the user is in the state of serious addiction.

[0059] The tendency prediction layer performs threshold adjustment on the addiction state determined by the prediction data through the threshold adjustment layer: for the user determined as the addiction state, the original time length threshold of the application program of the user is reduced by 10%, and is output to the main control unit; for the user determined as the serious addiction state, the original time length threshold of the application program of the user is reduced by 20%, and is output to the main control unit. After receiving and reading the threshold output by the threshold adjustment layer, the main control unit controls the setting unit to update the set threshold.

[0060] In the above manner, the anti-addiction computer provided in the embodiment can determine the addiction state of the user according to the actual use condition of the user, and increase the restriction on the addicted user to prevent the user from continuing to be addicted.

[0061] Meanwhile, the anti-addiction computer provided in the embodiment can also monitor the state of the user himself through the camera and the distance sensor, and control the brightness of the screen according to the state.

[0062] The camera is used to collect the sitting posture image of the user, and the collected image information is read by the main control unit and recognized by the sitting posture recognition unit. The specific recognition steps are as follows:

[0063] S2.1, the sitting posture image information collected by the camera is read by the main control unit and the contour of the sitting posture image is extracted by the contour extraction layer in the sitting posture recognition unit, mainly including the following steps:

[0064] S2.1.1, the average gray value of the image pixels is calculated, and a frame of image with close gray value and small time interval is selected to assist in contour extraction; wherein, the calculation formula of the average gray value μ of the image pixels is as follows:

[0065]

[0066] In the formula, n represents the number of pixel points in the image, and ∑f(i,j) represents the sum of pixel values of each pixel point in the image;

[0067] S2.1.2, the current image and the image with close gray value and small time interval are converted into gray images, and the difference image is obtained by subtraction, and the fuzzy sitting posture contour is obtained;

[0068] S2.1.3, the difference image is binarized to obtain the sitting posture contour with only black and white pixel points, and the sitting posture contour is filtered to eliminate noise and obtain a relatively clear sitting posture contour;

[0069] S2.2, the contour information extracted by the contour extraction layer is modeled by a sitting posture modeling layer, the sitting posture modeling layer establishes a rectangular coordinate system with a line connecting two end pixel points of a shoulder contour as an x-axis, a midpoint of the two end pixel points as an origin, and a direction in which a head contour is located as a positive direction of a y-axis, and detects a coordinate (xm, yn) of a top pixel point of the head;

[0070] S2.3, the coordinate (xm, yn) of the top pixel point of the head detected by the sitting posture matching layer is matched with a coordinate of a top pixel point of a head in standard sitting posture information pre-stored in a storage module, a deviation threshold is set to 10%, and if the threshold is exceeded, it is determined that the user's sitting posture is incorrect.

[0071] The sitting posture state determined by the sitting posture matching layer is read by the main control unit and issues an instruction to the screen brightness adjusting unit to adjust the screen brightness, and the main process is as shown in Figure 3 The specific steps are as follows:

[0072] S3.1, the sitting posture information of the user is extracted by the main control unit, and whether the sitting posture is correct is determined by the sitting posture recognition unit, and the sitting posture state information is transmitted to the main control unit;

[0073] S3.2, the main control unit reads the sitting posture state information, if the sitting posture is correct, an instruction is issued to the screen brightness adjusting unit to control the screen to maintain normal brightness, and the brightness adjustment of this round is ended; if the sitting posture is incorrect, the next step is continued;

[0074] S3.3, the time when the sitting posture is incorrect is continuously detected, and whether the time when the sitting posture is incorrect exceeds 1 minute is determined; if it does not exceed 1 minute, it indicates that the user only has a short activity, then the main control unit issues an instruction to the screen brightness adjusting unit to control the screen to maintain normal brightness, and the brightness adjustment of this round is ended;

[0075] If the time when the sitting posture is incorrect exceeds 1 minute, the main control unit issues an instruction to the screen brightness adjusting unit to control the screen brightness to be lowered to 50% of the normal brightness value, and the next step is continued;

[0076] S3.4, after the screen brightness is lowered, the sitting posture is still continuously detected, if it returns to normal, the brightness is adjusted back to the normal value; if it does not return to normal, the lower brightness is continuously maintained, and the time when the screen is in a low brightness state is extracted;

[0077] S3.5, if the time length of the screen being in low brightness does not exceed 3 minutes, it indicates that the user adjusts the posture within 3 minutes, the screen brightness returns to normal, and the current round of brightness adjustment ends; if the time length of the screen being in low brightness exceeds 3 minutes, it indicates that the user still does not adjust the posture within 3 minutes, the main control unit sends an instruction to the screen brightness adjustment unit to adjust the screen brightness value to 0, so as to avoid the user continuing to use the computer in an improper posture, and the current round of brightness adjustment ends.

[0078] Meanwhile, the distance sensor is used to monitor the distance between the user and the screen, the monitoring result is recognized by the distance recognition unit called by the main control unit, and the screen brightness is adjusted according to the recognition result, and the main process is as shown in Figure 4 , and the specific steps are as follows:

[0079] S4.1, the distance between the user and the screen is monitored by the distance sensor, and the signal processing layer in the distance recognition unit is called by the main control unit to amplify and process the signal input by the distance sensor and convert the signal from an analog signal to a digital signal, and then transmit it to the distance matching layer; the measured distance is compared with the preset distance threshold value through the distance matching layer to determine whether the current distance is less than the set distance threshold value, and the distance threshold value is set to 50 cm in the embodiment;

[0080] S4.2, if the current distance is not less than the set distance threshold value, the main control unit sends an instruction to the screen brightness adjustment unit to control the screen to keep normal brightness, and the current round of brightness adjustment ends;

[0081] If the current distance is less than the set distance threshold value, the main control unit sends an instruction to the screen brightness adjustment unit to control the screen brightness to be lowered to 50% of the normal brightness value, and the next step is continued;

[0082] S4.3, the distance between the user and the screen is still detected after the screen brightness is lowered, if the distance is not less than the threshold value, the brightness is adjusted back to the normal value; if the distance is still less than the threshold value, the lower brightness is continuously kept, and the time length of the screen being in low brightness is extracted;

[0083] S4.4, if the time length of the screen being in low brightness does not exceed 3 minutes, it indicates that the user adjusts the distance from the screen within 3 minutes, the screen brightness returns to normal, and the current round of brightness adjustment ends; if the time length of the screen being in low brightness exceeds 3 minutes, it indicates that the user still does not adjust the distance from the screen within 3 minutes, the main control unit sends an instruction to the screen brightness adjustment unit to adjust the screen brightness value to 0, so as to avoid the user continuing to use the computer in an improper posture, and the current round of brightness adjustment ends.

[0084] Through the above manner, the computer for preventing indulging in games can set the limiting time for various programs according to the actual situation of the user, has stronger pertinence and flexibility; and controls the brightness of the screen according to the distance between the user and the screen and the sitting posture, guides the user to keep the correct distance and sitting posture, thereby helps the minors to form good computer use habits, protects the physical and mental health, has high economic and social value.

[0085] The above merely serves to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some or all of the technical features can be replaced equivalently; any equivalent structure or equivalent flow conversion made by using the content of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An anti-addiction computer, comprising a monitoring module, a storage module, a processing module, and an output module, wherein the monitoring module, storage module, and output module are respectively connected to the processing module, and the output module includes a screen; characterized in that: The monitoring module includes a program monitoring unit, a camera, and a distance sensor, which are used to monitor the program running status, the user's sitting posture, and the distance between the user and the screen, respectively. The processing module includes a calculation submodule and a control submodule. The calculation submodule is connected to the monitoring module through the control submodule and is used to analyze and calculate the information acquired by the monitoring module and output the results to the control submodule. The control submodule is connected to the monitoring module, storage module, output module and calculation submodule respectively, and is used to control the operation of each module, and to control the running status of the program and the brightness of the screen to prevent users from becoming addicted. The computational submodule includes an addiction state analysis unit; the addiction state analysis unit includes an operation duration calculation layer, a data statistics layer, a trend prediction layer, and a threshold adjustment layer; the operation duration calculation layer calculates the actual operation duration of each application during operation, excluding background running time, and transmits it to the data statistics layer; the data statistics layer receives the duration data output by the operation duration calculation layer, performs statistics, and transmits it to the trend prediction layer; the trend prediction layer performs exponential smoothing on the time series of application usage time and computer login time respectively, thereby predicting the development trend of each duration, judging the addiction state, and transmitting it to the threshold adjustment layer; the threshold adjustment layer adjusts the threshold of each duration according to the addiction state, and transmits the adjusted threshold to the control submodule; The camera is located at the top center of the screen and is used to capture the user's sitting posture image information; the distance sensor is located at the bottom center of the screen and is used to detect the distance between the user and the screen. The calculation submodule includes a posture recognition unit and a distance recognition unit; the posture recognition unit is used to analyze and recognize the image information captured by the camera and determine whether the user's posture meets the requirements; the distance recognition unit is used to recognize the distance information captured by the distance sensor and determine whether the distance between the user and the screen meets the requirements; and adjust the brightness of the screen according to the posture image information and the distance between the user and the screen. The sitting posture recognition unit includes a contour extraction layer, a sitting posture modeling layer, and a sitting posture matching layer. The contour extraction layer is used to extract the contours of the user's head, neck, and shoulders, and transmit the contour information to the sitting posture modeling layer. The sitting posture modeling layer is used to establish a coordinate system for the sitting posture contours, extract the coordinates of the head vertex, and transmit them to the sitting posture matching layer. The posture matching layer is used to match the coordinates of the top pixel of the head with the pre-stored normal coordinates to determine whether the user's posture is correct.

2. The anti-addiction computer according to claim 1, characterized in that: The computation submodule also includes an identity recognition unit, which is used to extract facial features from the image information captured by the camera and match them with facial information in the pre-stored user information to identify the current user's identity; the user information includes facial information, identity information and permission information.

3. The anti-addiction computer according to claim 1, characterized in that: The storage module includes a program storage unit and a data storage unit, which are used to store various applications and data, respectively. The data includes data generated by the monitoring module, control submodule and calculation submodule during operation.

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