Intelligent rudder and method for monitoring a driver of an intelligent rudder

Abstract

The present disclosure provides a kind of intelligent rudder and the driving personnel monitoring method of intelligent rudder, belong to the field of ship safety.The intelligent rudder includes: data acquisition module, for the driving personnel parameter corresponding to the driving personnel who drives the intelligent rudder is collected, data analysis module, for obtaining the health score;And based on the human parameter and standard health data, obtain fatigue coefficient and disease risk coefficient;Alarm module, for issuing alarm reminder.The present disclosure can avoid the accident risk caused by the physical discomfort of the driving personnel in advance, greatly reduce the probability of accident caused by human operation error when sailing.

Description

TECHNICAL FIELD

[0001] The present disclosure belongs to the field of ship safety, and particularly relates to an intelligent rudder and a method for monitoring a driver of the intelligent rudder. BACKGROUND

[0002] A rudder is mainly used to control the direction of a ship sailing, and is a crucial factor affecting the safety of the ship sailing. When driving a ship, a driver needs to not only master the rules of maritime traffic, but also consider various factors such as the relationship between sailing speed and water flow, ocean current, tide, climate and many other sudden sea conditions. Therefore, the decision of the driver of the rudder is related to the lives of all crew members. However, since the time of sea navigation is generally long, the driver is prone to fatigue driving or even sudden illness, which may cause the ship to be in a dangerous situation.

[0003] In the related art, the driving state of the driver of the rudder is mainly determined by video recording and manual supervision, which is prone to incorrect or missed judgments caused by human factors, and requires a high level of supervision personnel. SUMMARY

[0004] The present disclosure provides an intelligent rudder and a method for monitoring a driver of the intelligent rudder, which can avoid the risk of accidents caused by the driver's illness in advance, and greatly reduce the probability of accidents caused by human operation errors during sailing. The technical solution is as follows:

[0005] The present disclosure provides an intelligent rudder, a data acquisition module for acquiring a driver parameter corresponding to a driver driving the intelligent rudder, the driver parameter including a human body parameter and a driving parameter, the human body parameter being a physiological parameter for indicating the health status of the driver, and the driving parameter being for indicating the driving state of the driver; a data analysis module for obtaining a human body score of each of the human body parameters of the driver based on the human body parameter of the driver and standard health data, the standard health data being a human body parameter corresponding to a healthy person; obtaining a driving score of each of the driving parameters of the driver based on the driving parameter of the driver and standard driving data, the standard driving data being a driving parameter corresponding to the healthy person when driving the intelligent rudder; summing each of the human body scores and each of the driving scores to obtain a health score; and obtaining a fatigue coefficient and a disease risk coefficient based on the human body parameter and the standard health data; and an alarm module for issuing an alarm reminder according to the health score, the fatigue coefficient and the disease risk coefficient.

[0006] In yet another implementation manner of the present disclosure, the data analysis module is configured to determine the human body score in the following manner: if the human body parameter is within the range of the corresponding standard health data, the human body score is a first reference value; if the human body parameter is greater than the maximum value of the standard health data, the human body score is obtained according to the following formula:

[0007] y = B1 - A1(x1 - a max );

[0008] if the human body parameter is less than the minimum value of the standard health data, the human body score is obtained according to the following formula:

[0009] y = B1 - A2(a min - x1);

[0010] wherein y is the human body score, not less than zero, B1 is the first reference value; A1 and A2 are constants; x1 is the human body parameter; a max is the maximum value of the corresponding standard health data; a min is the minimum value of the corresponding standard health data.

[0011] In yet another implementation manner of the present disclosure, the data analysis module is configured to determine the driving score in the following manner: if the driving parameter is within the range of the corresponding standard driving data, the driving score is a second reference value, which is the same as the first reference value; if the driving parameter is greater than the maximum value within the range of the standard driving data, the driving score is obtained according to the following formula:

[0012] y = B2 - A3(x2 - b max );

[0013] if the human body parameter is less than the minimum value of the standard driving data, the driving score is obtained according to the following formula:

[0014] y = B2 - A4(b min - x2);

[0015] wherein y is the driving score, not less than zero, B2 is the second reference value; A3 and A4 are constants; x2 is the driving parameter; b max is the maximum value of the corresponding standard driving data; b min is the minimum value of the corresponding standard driving data.

[0016] In yet another implementation manner of the present disclosure, the data analysis module is configured to determine the fatigue coefficient and the disease risk coefficient in the following manner: if the driving parameter is not within the range of the standard driving data, the change value of the human body parameter within the same interval time during driving is greater than a first threshold value, and the human body parameter is always within the corresponding standard health data range before and after each change, then the fatigue coefficient is obtained according to the number of changes of the human body parameter; if the driving parameter is not within the range of the standard driving data, the change value of the human body parameter within the same interval time during driving is greater than a second threshold value, and the human body parameter is not within the standard health data range after each change, then the disease risk coefficient is obtained according to the number of changes of the human body parameter.

[0017] In yet another implementation manner of the present disclosure, the data analysis module obtains the fatigue coefficient or the disease risk coefficient according to the following formula:

[0018]

[0019] wherein y is the fatigue coefficient or the disease risk coefficient; b0

[0020] In yet another implementation manner of the present disclosure, the alarm module includes a buzzer, a vibrator and an alarm indicator light; the alarm module is configured to: when the health score is lower than a first score threshold value, or the fatigue coefficient is not less than a first coefficient threshold value, the buzzer is used to issue an alarm reminder at intervals, the vibrator is used to issue a high-frequency vibration reminder at intervals, and the alarm indicator light is used to issue a red light reminder continuously; when the health score is lower than a second score threshold value, and the disease risk coefficient is not less than a second coefficient threshold value, the buzzer is used to issue an alarm reminder continuously, the vibrator is used to issue a high-frequency vibration reminder continuously, and the alarm indicator light is used to issue a red light reminder continuously; wherein the first score threshold value is greater than the second score threshold value, and the second coefficient threshold value is less than the first coefficient threshold value.

[0021] In yet another implementation manner of the present disclosure, the human body parameter includes age, body mass index, body temperature, heart rate, blood pressure, blood oxygen and pulse; and the driving parameter includes the navigation time of the driver, the rest time during navigation and the corresponding time period during navigation.

[0022] In yet another implementation manner of the present disclosure, the intelligent rudder further includes a display module, and the display module is configured to display the driving personnel parameter, the health score, the fatigue coefficient, the disease risk coefficient and alarm information in real time and online.

[0023] In yet another implementation form of the present disclosure, the intelligent rudder further comprises a rudder adjustment module configured to adjust at least one of a rudder height, a rudder angle, and a rudder temperature in real time according to the driver.

[0024] In yet another implementation form of the present disclosure, a driver monitoring method for an intelligent rudder is also provided, which comprises: collecting driver parameters of a driver who drives the intelligent rudder, the driver parameters comprising human body parameters and driving parameters, the human body parameters being physiological parameters for indicating a physical health state of the driver, and the driving parameters being parameters for indicating a driving state of the driver; obtaining human body scores of each of the human body parameters of the driver based on the human body parameters of the driver and standard health data, the standard health data being human body parameters of healthy persons; obtaining driving scores of each of the driving parameters of the driver based on the driving parameters of the driver and standard driving data, the standard driving data being driving parameters of the healthy persons when driving the intelligent rudder; summing up each of the human body scores and each of the driving scores to obtain a health score; obtaining a fatigue coefficient and a disease risk coefficient based on the human body parameters and the standard health data; and issuing an alarm reminder according to the health score, the fatigue coefficient, and the disease risk coefficient.

[0025] The technical scheme provided by the embodiments of the present disclosure has the following beneficial effects:

[0026] In the embodiments of the present disclosure, the driver parameters of the driver who drives the intelligent rudder can be captured by the data acquisition module, and the human body scores and the driving scores corresponding to the driver can be obtained according to different human body parameters and different driving parameters in the driver parameters by the data analysis module, and the health score, the fatigue coefficient, and the disease risk coefficient can also be obtained. Meanwhile, the alarm module can determine whether there is fatigue driving according to the health score, the fatigue coefficient, and the disease risk coefficient of the driver, so as to issue an alarm reminder, and further to give a warning and intervention to the fatigue driving and other conditions of the driver, thereby avoiding accidents. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical scheme in the embodiments of the present disclosure, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0028] Figure 1 is a structural schematic diagram of an intelligent rudder provided by the embodiments of the present disclosure;

[0029] Figure 2 FIG. 1 is a flowchart of a method for monitoring a driver of an intelligent rudder according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] In order to make the objects, technical solutions and advantages of the present disclosure clearer, the embodiments of the present disclosure will be further described in detail below with reference to the drawings.

[0031] In order to clearly illustrate the intelligent rudder and the method for monitoring a driver of the intelligent rudder provided by the present disclosure, the basic structure of the intelligent rudder is described first.

[0032] The intelligent rudder comprises a rudder rim and a transmission shaft. The transmission shaft is connected with the rudder rim. A universal joint is arranged on the transmission shaft, which can adjust the inclination angle of the intelligent rudder. A lifting device is arranged on the transmission shaft, which can adjust the height of the intelligent rudder. The inclination angle and the height of the intelligent rudder can be matched according to the height and driving habit of different drivers.

[0033] A heating resistance wire, a small fan and an air duct are arranged in the rudder rim. The heating and blowing functions can be automatically started according to the room temperature and the body temperature of the human body, and the gears can be manually adjusted through the buttons on the rudder rim, so as to improve the comfort of the driver.

[0034] An embodiment of the present disclosure provides an intelligent rudder, as shown in Figure 1 The intelligent rudder comprises a data acquisition module 101, a data analysis module 102 and an alarm module 103.

[0035] The data acquisition module 101 is configured to acquire driver parameters corresponding to a driver driving the intelligent rudder. The driver parameters comprise human body parameters and driving parameters.

[0036] The human body parameters are physiological parameters used to represent the physical health state of the driver, and the driving parameters are used to represent the driving state of the driver.

[0037] In the embodiment, the data acquisition module 101 can be a sensor device and a navigation monitoring device. The sensor device is configured to acquire the human body parameters of the driver in real time. The navigation monitoring device is configured to acquire the driving parameters of the driver in real time.

[0038] The data analysis module 102 is configured to obtain a human body score of each human body parameter of the driver based on the human body parameter of the driver and standard health data corresponding to the human body parameter of a healthy person, and obtain a driving score of each driving parameter of the driver based on the driving parameter of the driver and standard driving data corresponding to the driving parameter of the healthy person when the intelligent rudder is driven. The human body scores and the driving scores are added to obtain a health score. The data analysis module 102 is further configured to obtain a fatigue coefficient and a disease risk coefficient based on the human body parameter and the standard health data.

[0039] The data analysis module 102 can include a processor and a memory. The processor is configured to analyze the driving parameter of the driver. The memory is configured to store the collected driving parameter of the driver.

[0040] In addition, the standard health data and the standard driving data can be stored in the memory in advance.

[0041] Of course, the driving parameter of the driver who has driven the intelligent rudder can also be stored in the memory. For example, the drivers A and B have both driven the intelligent rudder, and the memory stores the driving parameter corresponding to the drivers A and B.

[0042] The alarm module 103 is configured to issue an alarm reminder according to the health score, the fatigue coefficient and the disease risk coefficient.

[0043] The alarm module 103 includes a buzzer, a vibrator and an alarm indicator. The buzzer is configured to issue an alarm prompt sound, the vibrator is configured to issue vibrations of different frequencies to remind the driver, and the alarm indicator is configured to issue light of different colors.

[0044] The alarm indicator is arranged in the visual range of the driver. The buzzer is arranged on the left and right sides of the hull of the ship. The vibrator is a vibration motor. The vibrator is arranged on the rudder rim of the intelligent rudder.

[0045] In the embodiment of the present disclosure, the data collection module can capture the driving parameter of the driver driving the intelligent rudder. The data analysis module can obtain the corresponding human body score and driving score of the driver according to different human body parameters and different driving parameters in the driving parameter of the driver, and obtain the health score, the fatigue coefficient and the disease risk coefficient. The alarm module can determine whether there is fatigue driving according to the health score, the fatigue coefficient and the disease risk coefficient of the driver, and issue an alarm reminder accordingly, so as to early warn and intervene the fatigue driving of the driver and avoid accidents.

[0046] Optionally, the human body parameters include age, body mass index, body temperature, heart rate, blood pressure, blood oxygen and pulse. The driving parameters include the navigation time of the driver, the rest time during the navigation and the corresponding time period during the navigation.

[0047] By including the above in the human body parameter correspondence, the physical condition of the driver can be evaluated as much as possible to determine whether the driver's body is abnormal. By including the above in the driving parameter correspondence, the driver's fatigue can be simply evaluated according to the corresponding driving time, driving time period and the like during the actual driving process.

[0048] Optionally, the sensor device corresponding to the above human body parameters includes a thermometer, a heart rate sensor, a blood pressure sensor, a blood oxygen sensor and the like.

[0049] The above sensor devices can be arranged in the hand holding area of the rudder rim of the intelligent rudder, for example, the above sensor devices are arranged in close proximity to the hand holding area of the rudder rim, so as to ensure that the human body parameters can be detected at the same time. It should be noted that a safety gap should be left between the sensor device and other devices when arranging the sensor device. In this way, the corresponding human body parameters of the driver can be conveniently collected in real time.

[0050] Optionally, the data analysis module 102 is configured to determine the human body score in the following manner:

[0051] If the human body parameter is within the range of the corresponding standard health data, the human body score is a first reference value.

[0052] If the human body parameter is greater than the maximum value of the standard health data, the human body score is obtained according to the following formula (1):

[0053] y = B1 - Δ1 (x1 - amax); (1)

[0054] If the human body parameter is less than the minimum value of the standard health data, the human body score is obtained according to the following formula (2):

[0055] y = B1 - Δ1 (x1 - a min min); (2)

[0056] In the formula (1) and (2), y is the human body score, which is not less than zero, B1 is the first reference value; A1 and A2 are constants; x1 is the human body parameter; amax is the maximum value of the corresponding standard health data; a max min is the minimum value of the corresponding standard health data. min

[0057] The human body score can be quickly calculated by the above formula (1) and formula (2).

[0058] ​Exemplarily, the first reference value is merely for indicating the human body score corresponding to the human body parameter when the driver is in a healthy state, and therefore can be set according to specific conditions. In the embodiment, for the convenience of calculation, the first reference value is set to 10.

[0059] The above standard health data is standard data identified according to medical standards for human health conditions. For example, the normal body temperature of a human body is 36-37.2℃. The normal heart rate is 60-100 times per minute. The normal blood oxygen saturation is 95%-99%; the normal systolic pressure in blood pressure is 90-140 mmHg, and the normal diastolic pressure in blood pressure is 60-90 mmHg, and the like. It can be seen that for different human body parameters, a max and a min are different.

[0060] The normal body temperature of a human body in the standard health data is 36-37.2℃, that is, the minimum value a min of the body temperature is 36, and a max is 37.2℃. Assuming that the body temperature of the driver collected by the thermometer is 37.5, at this time, the human body score can be calculated by using formula (1).

[0061] In addition, the constant A1 can be calculated according to the maximum limit value corresponding to different types of human body parameters and the maximum value and the minimum value in the corresponding standard health data.

[0062] For example, for the body temperature, the calculation of A1 can be as follows:

[0063] Suppose the maximum limit value of the body temperature of a human body is 43.2℃, at this time, A1 can be obtained by back calculation according to formula (1). The maximum limit value of the body temperature of a human body 43.2℃ is brought into formula (1), at this time, since the body temperature of the driver is 43.2℃, at this time, the human body score is y=0 (that is, the human body score corresponding to the body temperature of the driver is 0). That is, A1 is 20. Correspondingly, A2 is also calculated in a similar manner.

[0064] That is, formula (1) can obtain the constant A1 by linear fitting according to the corresponding maximum limit value in the human body parameter and the maximum value in the standard health data. Of course, formula (2) can also obtain the constant A2 by linear fitting according to the corresponding minimum limit value in the human body parameter and the minimum value in the standard health data.

[0065] Optionally, the data analysis module is configured to determine the driving score in the following manner:

[0066] If the driving parameter is within the range of the corresponding standard driving data, the driving score is a second reference value, and the second reference value is the same as the first reference value.

[0067] If the driving parameter is greater than the maximum value within the range of the standard driving data, the driving score is obtained according to the following formula (3):

[0068] y = B2 - Δ3(x2 - b max ); (3)

[0069] If the human parameter is less than the minimum value of the standard driving data, the driving score is obtained according to the following formula:

[0070] y = B2 - A4(b min - x2); (4)

[0071] In the formula (3) and the formula (4), y is the driving score, not less than zero, B2 is the second reference value, A3 and A4 are constants, x2 is the driving parameter, b max is the maximum value of the corresponding standard driving data, and b min is the minimum value of the corresponding standard driving data.

[0072] In the embodiment, the standard driving data is the standard data corresponding to the driving personnel in the driving process according to the driving industry standard. For example, the navigation time in the standard driving data is 1-2h, the rest time is ≥30min, the driving time period is 8-12am and 14-17pm.

[0073] In the embodiment, for convenience of calculation, the first reference value and the second reference value can be both set as 10.

[0074] Correspondingly, the calculation process of the driving score is similar to the human evaluation described above, and the calculation of the constant speed A3 and A4 is also similar to A1 and A2. Here, the details are not described again.

[0075] Optionally, the data analysis module is configured to determine the fatigue coefficient and the disease risk coefficient in the following manner:

[0076] If the driving parameter is not within the range of the standard driving data, the change value of the human parameter within the same interval time is greater than the first threshold value in the driving process, and the human parameter is always within the range of the corresponding standard health data before and after each change, the fatigue coefficient is obtained according to the number of changes of the human parameter.

[0077] If the driving parameter is not within the range of the standard driving data, the change value of the human parameter within the same interval time is greater than the second threshold value in the driving process, and the human parameter is not within the range of the standard health data after each change, the disease risk coefficient is obtained according to the number of changes of the human parameter.

[0078] In the above implementation mode, according to the number of changes of the human parameter of the driving personnel in the driving process, the fatigue coefficient and the disease risk coefficient can be corresponded.

[0079] The change value is the difference between the maximum value and the minimum value of the human body parameter in the same time interval.

[0080] For example, the human body parameter is collected every 10 seconds when the driving parameter is not within the range of the standard driving data within 1 hour of driving. In the human body parameter, the change value of the body temperature is greater than the first threshold value in one of the interval times, and the change frequency of the body temperature is 2, the change value of the blood pressure is also greater than the corresponding first threshold value, and the change frequency of the blood pressure is 1, and other human body parameters do not change, then the change frequency of the human body parameter is 2+1=3.

[0081] Exemplarily, for the same human body parameter, the first threshold value is less than the second threshold value. Moreover, the first threshold value and the second threshold value of different human body parameters are different, for example, the first threshold value corresponding to the body temperature in the human body parameter can be 0.5℃, and the second threshold value can be 1.5℃. The first threshold value corresponding to the heart rate can be 15 and so on, and the second threshold value can be 20 and so on.

[0082] The first threshold value and the second threshold value can be specifically set according to the type of the human body parameter and the change of the human body parameter in the driving process of the driving personnel in the past.

[0083] Exemplarily, the data analysis module obtains the fatigue coefficient or the disease risk coefficient according to the following formula:

[0084]

[0085] Wherein, y is the fatigue coefficient or the disease risk coefficient; b0<b2<b1<b3, b0, b1, b2, b3 are all constants; n is the change frequency of the human body parameter.

[0086] The fatigue coefficient and the disease risk coefficient of the driving personnel in the driving process can be quickly calculated through formula (5).

[0087] The constant b0 in formula (5) can be 10%, b1 can be 20%, b2 can be 15%, and b3 can be 50%.

[0088] Combined with the human body fatigue index in medicine, when the human body is slightly fatigued, the fatigue index is 10-20%, so b0=10% can be obtained. When the human body is moderately fatigued, the fatigue index is 20-50%, so b1=20% can be obtained; correspondingly, b2 is greater than b0, and can be taken as 15%. When the human body is in severe fatigue, the fatigue index is 50-100%, so b3=50%, and the fatigue coefficient b1 is greater than b2, and can be taken as 20%.

[0089] Of course, the above settings of b0, b1, b2, b3 can also be other data, as long as the corresponding fatigue coefficient and disease risk coefficient can be reasonably obtained through the number of changes in human body parameters.

[0090] Exemplarily, when calculating, if the heart rate of the driver suddenly becomes large, and the blood pressure suddenly rises, accompanied by an increase in heart rate, then n = 3. If the human body parameters before and after the change are all within the corresponding standard health data range, then the fatigue coefficient can be calculated according to formula (5). Conversely, if it is not within the corresponding standard health data range after the change, then the disease risk coefficient is calculated.

[0091] Optionally, the alarm module 103 is configured to: when the health score is lower than a first score threshold, or the fatigue coefficient is not less than a first coefficient threshold, the alarm module 103 is configured to: issue an alarm reminder through the buzzer at intervals, issue a high-frequency vibration reminder through the vibrator at intervals, and continuously issue a red light reminder through the alarm indicator light; and when the health score is lower than a second score threshold, and the disease risk coefficient is greater than a second coefficient threshold, the alarm module 103 is configured to: continuously issue an alarm reminder through the buzzer, continuously issue a high-frequency vibration reminder through the vibrator, and continuously issue a red light reminder through the alarm indicator light. The first score threshold is greater than the second score threshold, and the second coefficient threshold is less than the first coefficient threshold.

[0092] According to the above judgment standard, the alarm module can perform different degrees of alarm reminders according to the different physical conditions of the driver.

[0093] The first score threshold, the second score threshold, the first coefficient threshold, and the second coefficient threshold mentioned above can be set according to actual conditions. In the present embodiment, the first score threshold is 80, the second score threshold is 70, the first coefficient threshold is 5, and the second coefficient threshold is 1.

[0094] In addition, the alarm module 104 can also perform more detailed alarms in the following manner in order to more conveniently remind the driver.

[0095] If the health score is greater than or equal to 90, it indicates that the physical health status of the driver is excellent, and the alarm indicator light is green and constantly on, and the buzzer and the vibrator are not actuated.

[0096] If the health score is in [80, 90), and the fatigue coefficient is 0, the alarm indicator light displays green and constantly on, and the buzzer and the vibrator are not actuated.

[0097] If the health score is in [80, 90), and the fatigue coefficient is greater than 0 and less than the first coefficient threshold in the collection period, it indicates that the body has mild fatigue, the alarm indicator light displays yellow and flashes to remind, the buzzer is not actuated, and the vibrator vibrates at low frequency every 5 seconds to remind.

[0098] If the health score is in [80, 90) and the fatigue coefficient in the collection period is greater than the second threshold value and less than the first threshold value, there is moderate fatigue, the body is displayed to have moderate fatigue, the alarm indicator is yellow and always on, the buzzer sounds every 5s, the vibration motor vibrates every 3s, until the fatigue signal is not monitored.

[0099] If the health score is in [70, 80), or the fatigue coefficient in the collection period is not less than the first threshold value, there is severe fatigue, the body is displayed to have poor health, or there is severe fatigue. The alarm indicator is red and always on, the buzzer sounds every 5s, the vibration motor vibrates every 1s, until the current fatigue signal is continuously eliminated, the alarm ends and each signal resets.

[0100] If the health score is less than 70, the body is displayed to have a serious poor health condition, and the disease risk coefficient is not less than the second threshold value, the alarm indicator is red and always on, the buzzer sounds continuously, and the vibration vibrates continuously. At this time, emergency stop is required to handle, the accident is investigated, and support is requested. Until the accident is investigated, the ship can start working again.

[0101] The alarm module further includes an external interface, which is used to connect with the main controller of the ship. When the health score is less than 70, the external interface transmits an emergency stop signal to the main controller of the ship, and the ship is stopped urgently. The remote system is contacted with the shore-based integrated management system to investigate the accident and request support until the accident is investigated. Higher authority resets the main controller of the ship and the intelligent rudder, and the ship can start working again.

[0102] Optionally, the intelligent rudder further includes a display module 104, which is used to display the driving personnel parameters, the health score, the fatigue coefficient, the disease risk coefficient and the alarm information in real time.

[0103] The display module 104 can be a display screen arranged on the main control device of the ship, which can display the current human parameters such as body temperature, heart rate, blood pressure and blood oxygen of the personnel in real time, and the fatigue coefficient and the disease risk coefficient of the driving personnel are also displayed on the display screen.

[0104] Optionally, the intelligent rudder further includes a rudder adjustment module 105, which is used to adjust at least one of the rudder height, the rudder angle and the rudder temperature in real time according to the driving personnel parameters.

[0105] In the above implementation manner, the rudder adjustment module 105 can adjust the height and angle of the intelligent rudder according to different driving personnel, so that the driving personnel can drive more conveniently and comfortably.

[0106] In this embodiment, the rudder adjustment module 105 includes a universal joint, a lifting device, and a temperature control device. The universal joint is connected with the transmission shaft of the intelligent rudder, and can adjust the inclination angle of the intelligent rudder. The lifting device is connected with the transmission, and is used to adjust the height of the intelligent rudder. The temperature control device is arranged inside the rudder rim, and includes a heating resistance wire, a fan, and an air duct, etc. The heating resistance wire is used to generate heat, and the heat is transmitted to the ship through the air duct to increase the room temperature in the ship. The fan is used to blow air, and the cold air is transmitted to the ship through the air duct to reduce the room temperature in the ship.

[0107] In addition, the data acquisition module 101 is also used to acquire the room temperature in the ship. Correspondingly, the sensor device can also include a temperature sensor, so that the temperature in the ship can be detected in real time through the temperature sensor. In this way, the rudder adjustment module 105 can automatically adjust the appropriate temperature according to the temperature of the ship acquired by the data acquisition module 101, so that the driver is more comfortable.

[0108] The memory in the data analysis module 102 also stores the rudder height and inclination angle of the intelligent rudder corresponding to the driver, the appropriate room temperature in the ship corresponding to the driver, and the real-time data such as body temperature, heart rate, blood pressure, and blood oxygen, as well as the process and results of alarm processing, etc. These data can also be exported periodically, so as to be used to evaluate the health degree of the driver, to be used as one of the bases for the regular physical examination review of the driver, and to track the processing process of the alarm, to correct the improper processing, and to prevent more serious accidents.

[0109] Exemplarily, the data acquisition module 101 is also used to acquire the fingerprint of the driver. That is, the sensor device includes a fingerprint identification sensor.

[0110] Correspondingly, the data analysis module 102 will perform real-time analysis and processing on the acquired fingerprint. First, the fingerprint can be used to identify the information of the driver. According to the information of the driver, the intelligent rudder is initialized in advance, that is, the rudder height and inclination angle corresponding to the driver which are pre-stored in the intelligent rudder are automatically matched. At the same time, the heating or air blowing can be started according to the temperature in the ship room corresponding to the driver, combined with the actual room temperature.

[0111] When the body temperature of the driver changes, such as increasing or decreasing by more than 0.5℃, the heating or air blowing mode can be automatically started. If the driver manually adjusts the rudder height, inclination angle, and heating or air blowing gear, etc., only needs to press the storage button on the intelligent rudder, and the information will be updated to the memory in the data analysis module in real time, for the next call.

[0112] On the other hand, the embodiment of the present disclosure also provides a driver monitoring method of an intelligent rudder, and the driver monitoring method is based on the above-mentioned intelligent rudder:

[0113] S201: Collect the driving personnel parameters corresponding to the driving personnel driving the intelligent rudder, the driving personnel parameters including the human body parameters and the driving parameters.

[0114] The human body parameters are physiological parameters used to represent the physical health state of the driving personnel, and the driving parameters are used to represent the driving state of the driving personnel.

[0115] S201 can be detected by the sensor device in the foregoing.

[0116] S202: Based on the human body parameters of the driving personnel and the standard health data, obtain the human body scores of each human body parameter of the driving personnel, and the standard health data is the human body parameters corresponding to the healthy personnel.

[0117] S202 can be calculated by the foregoing formulas (1) and (2).

[0118] S203: Based on the driving parameters of the driving personnel and the standard driving data, obtain the driving scores of each driving parameter of the driving personnel, and the standard driving data is the driving parameters corresponding to the healthy personnel when driving the intelligent rudder.

[0119] S203 can be calculated by the foregoing formulas (3) and (4).

[0120] S204: Add each human body score and each driving score to obtain a health score.

[0121] S204 can directly obtain the addition of the calculation results of the foregoing formulas (1), (2), (3) and (4).

[0122] S205: Based on the human body parameters and the standard health data, obtain a fatigue coefficient and a disease risk coefficient.

[0123] S205 can be calculated by the foregoing formula (5).

[0124] S206: According to the health score, the fatigue coefficient and the disease risk coefficient, an alarm is sent.

[0125] S206 can alarm by the buzzer, vibrator and alarm indicator light in the foregoing alarm module.

[0126] The above-mentioned intelligent rudder driving personnel monitoring method has the same beneficial effects as the foregoing intelligent rudder, which will not be repeated here.

[0127] The above only describes optional embodiments of the present disclosure, and does not limit the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An intelligent rudder, characterized in that, The intelligent rudder comprises: a data acquisition module, configured to acquire a driver parameter corresponding to a driver driving the intelligent rudder, the driver parameter comprising a human parameter and a driving parameter, the human parameter being a physiological parameter used to represent a physical health state of the driver, and the driving parameter being used to represent a driving state of the driver; a data analysis module, configured to obtain a human score of each of the human parameters of the driver based on the human parameter of the driver and standard health data, the standard health data being a human parameter corresponding to a healthy person; obtain a driving score of each of the driving parameters of the driver based on the driving parameter of the driver and standard driving data, the standard driving data being a driving parameter corresponding to the healthy person when driving the intelligent rudder; add each of the human scores and each of the driving scores to obtain a health score; and obtain a fatigue coefficient and a disease risk coefficient based on the human parameter and the standard health data; an alarm module, configured to issue an alarm reminder according to the health score, the fatigue coefficient and the disease risk coefficient; wherein the data analysis module is configured to determine the human score in the following manner: if the human parameter is within a range of the corresponding standard health data, the human score is a first reference value; if the human parameter is greater than a maximum value of the standard health data, the human score is obtained according to the following formula: y = B1 - A1(x1 - a max ); if the human parameter is less than a minimum value of the standard health data, the human score is obtained according to the following formula: y = B1 - A2(a min - x1); Wherein, y is the human body score, not less than zero, B1 is the first reference value; A1 and A2 are constants; x1 is a human body parameter; a max is the maximum value of the corresponding standard health data;a min is the minimum value of the corresponding standard health data. the data analysis module is configured to obtain the fatigue coefficient or the disease risk coefficient according to the following formula: wherein y is the fatigue coefficient or the disease risk coefficient; b0 2. The intelligent rudder of claim 1, wherein, The data analysis module is configured to determine the driving score in the following manner: if the driving parameter is within a range of the corresponding standard driving data, the driving score is a second reference value, the second reference value being the same as the first reference value; if the driving parameter is greater than a maximum value within the range of the standard driving data, the driving score is obtained according to the following formula: y = B2- A3(x2- b max ); if the human parameter is less than a minimum value of the standard driving data, the driving score is obtained according to the following formula: y = B2 - A4(b min - x2); wherein y is the driving score, not less than zero, B2 is a second reference value; A3 and A4 are constants; x2 is a driving parameter; b max is a maximum value corresponding to the standard driving data; b min is a minimum value corresponding to the standard driving data. The first reference value and the second reference value are both 10, the constant A1 and A2 are calculated according to the limit value corresponding to different types of human parameters and the maximum value and the minimum value in the corresponding standard health data, and the constant A3 and A4 are calculated according to the limit value corresponding to different types of driving parameters and the maximum value and the minimum value in the corresponding standard driving data.

3. The intelligent rudder of claim 1, wherein, The data analysis module is configured to determine the fatigue coefficient and the disease risk coefficient in the following manner: If the driving parameter is not within the range of the standard driving data, the change value of the human body parameter in the same interval time during driving is greater than a first threshold value, and the human body parameter is always within the corresponding standard health data range before and after each change, then the fatigue coefficient is obtained according to the number of changes of the human body parameter; If the driving parameter is not within the range of the standard driving data, the change value of the human body parameter in the same interval time during driving is greater than a second threshold value, and the human body parameter is not within the standard health data range after each change, then the disease risk coefficient is obtained according to the number of changes of the human body parameter.

4. The intelligent rudder according to any one of claims 1 to 3, characterized in that, The alarm module includes a buzzer, a vibrator, and an alarm indicator light; The alarm module is used to: When the health score is lower than a score first threshold value, or the fatigue coefficient is not less than a coefficient first threshold value, the buzzer is used to issue an alarm reminder at intervals, the vibrator is used to issue a high-frequency vibration reminder at intervals, and the alarm indicator light is used to continuously issue a red light reminder; When the health score is lower than a score second threshold value, and the disease risk coefficient is not less than a coefficient second threshold value, the buzzer is used to continuously issue an alarm reminder, the vibrator is used to continuously issue a high-frequency vibration reminder, and the alarm indicator light is used to continuously issue a red light reminder; The score first threshold value is greater than the score second threshold value, and the coefficient second threshold value is less than the coefficient first threshold value.

5. The intelligent rudder according to any one of claims 1 to 3, characterized in that, The human body parameter includes age, body mass index, body temperature, heart rate, blood pressure, blood oxygen, and pulse; The driving parameter includes the navigation time of the driver, the rest time during navigation, and the corresponding time period during navigation.

6. The intelligent rudder according to any one of claims 1 to 3, wherein, The intelligent rudder further includes a display module, which is used to display the driver parameter, the health score, the fatigue coefficient, the disease risk coefficient, and alarm information in real time and online.

7. The intelligent rudder according to any one of claims 1 to 3, wherein, The intelligent rudder further includes a rudder adjustment module, which is used to adjust at least one of the rudder height, the rudder angle, and the rudder temperature in real time according to the driver.

8. A method of monitoring a helmsman of a smart rudder, characterized by, The driver monitoring method: A driver parameter corresponding to a driver driving the intelligent rudder is collected, the driver parameter including a human body parameter and a driving parameter, the human body parameter being a physiological parameter used to represent the physical health status of the driver, and the driving parameter being used to represent the driving state of the driver; Based on the human body parameter of the driver and standard health data, a human body score of each of the human body parameters of the driver is obtained, the standard health data being a human body parameter corresponding to a healthy person; Based on the driving parameter of the driver and standard driving data, a driving score of each of the driving parameters of the driver is obtained, the standard driving data being a driving parameter corresponding to the healthy person when driving the intelligent rudder; The human body scores and the driving scores are added to obtain a health score; Based on the human body parameter and the standard health data, a fatigue coefficient and a disease risk coefficient are obtained; According to the health score, the fatigue coefficient and the disease risk coefficient, an alarm is sent out; If the human body parameter is within the range of the standard health data, the human body score is a first reference value; If the human body parameter is greater than the maximum value of the standard health data, the human body score is obtained according to the following formula: y = B1 - A1(x1 - a max ); If the human body parameter is less than the minimum value of the standard health data, the human body score is obtained according to the following formula: y = B1 - A2(a min - x1); Wherein, y is the human body score, not less than zero, B1 is the first reference value; A1 and A2 are constants; x1 is a human body parameter; a max is the maximum value of the corresponding standard health data; a min is the minimum value of the corresponding standard health data. The fatigue coefficient or the disease risk coefficient is obtained according to the following formula: Wherein, y is the fatigue coefficient or the disease risk coefficient; b0

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