Skiing monitoring system and wearable device

Abstract

The invention relates to a skiing monitoring system and wearable equipment. The skiing monitoring system is deployed on a wearable device, and the skiing monitoring system comprises a data acquisition device used for acquiring first original skiing data related to skiing movement and sending the first original skiing data to a data processing device; the data processing device comprises a plurality of data screening units and a data processing unit, for each ski data dimension, the N data screening units use respective data screening rules to screen the first original ski data so as to obtain second original ski data used for calculating target ski parameters of the dimension, and the second original ski data are used for calculating the target ski parameters of the dimension. The data processing unit is used for acquiring second original skiing data and inputting the second original skiing data into the data processing unit, and the data processing unit is used for determining target skiing parameters under the dimension according to the second original skiing data; and the data output device is used for outputting the target skiing parameters of each skiing data dimension. Therefore, the monitoring efficiency and precision of the skiing monitoring system are improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of wearable devices, and in particular to a ski monitoring system and a wearable device. Background Art

[0002] As people's living standards improve, ice and snow sports are becoming more and more popular among the public, and more and more people are engaging in skiing. Whether it is a novice who tries skiing out of curiosity, a skiing enthusiast, or a professional skier, the demand for skiing is increasing.

[0003] At present, most users in the skiing circle use mobile phone applications to record skiing data, but the monitoring efficiency and accuracy of skiing data during skiing are low. In addition, most skiers choose not to bring their mobile phones with them during skiing because the mobile phones are too large and there is a risk of breaking them after falling. Therefore, the development of skiing functions based on wearable devices is particularly important. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a ski monitoring system and a wearable device.

[0005] According to a first aspect of an embodiment of the present disclosure, a ski monitoring system is provided, wherein the ski monitoring system is deployed on a wearable device, and the ski monitoring system includes:

[0006] A data collection device, used for collecting first original skiing data related to skiing, and sending the first original skiing data to a data processing device;

[0007] The data processing device includes a plurality of data screening units and a data processing unit, wherein for each skiing data dimension, N data screening units use respective data screening rules to screen the first original skiing data to obtain second original skiing data for calculating the target skiing parameter of the dimension, and input the second original skiing data into the data processing unit, and the data processing unit is used to determine the target skiing parameter under the dimension according to the second original skiing data; different data screening units have different data screening rules, N is an integer less than or equal to the number of filtering units, and the skiing data dimension includes at least one of the following: speed dimension, distance dimension, altitude dimension, trip number dimension, and slope dimension;

[0008] The data output device is used to output the target skiing parameter of each skiing data dimension.

[0009] Optionally, the multiple data screening units include a filtering unit for acceleration dimension and a filtering unit for altitude dimension; the multiple data screening units also include a filtering unit for distance dimension or speed dimension;

[0010] a filtering unit in a distance dimension, configured to determine a sliding distance according to the position data included in the first original skiing data, and to filter out abnormal first original skiing data according to a change in the sliding distance;

[0011] a filtering unit in a speed dimension, configured to filter out abnormal first original skiing data according to an original skiing speed included in the first original skiing data and a first skiing speed calculated based on position data included in the first original skiing data;

[0012] The filtering unit of the acceleration dimension is used to filter out abnormal first original skiing data according to the acceleration calculated based on the original skiing speed and / or calculated based on the position data included in the first original skiing data;

[0013] The filtering unit of the altitude dimension is used to filter out abnormal first original skiing data according to the first altitude data and the second altitude data included in the first original skiing data;

[0014] The first altitude data refers to altitude data measured by a first sensor, and the second altitude data refers to altitude data measured by a second sensor.

[0015] Optionally, the data processing unit further includes a data fusion unit;

[0016] For the sliding speed dimension, the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension, so as to filter out abnormal first original skiing data in the distance or speed dimension, the acceleration dimension, and the altitude dimension, and obtain second original skiing data for calculating the target sliding speed;

[0017] The data fusion unit is used to obtain the acceleration calculated based on the second original skiing data and the second skiing speed calculated based on the position data included in the second original skiing data, and determine the target skiing speed based on the original skiing speed, the acceleration and the second skiing speed, as well as the historical skiing speed and the historical skiing distance.

[0018] Optionally, the data processing unit further includes a data fusion unit;

[0019] For the sliding distance dimension, the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension and the filtering unit of the acceleration dimension, so as to filter the abnormal first original skiing data in the distance dimension or the speed dimension and the acceleration dimension, and obtain the second original skiing data for calculating the target sliding distance;

[0020] The data fusion unit is used to determine a target skiing distance according to the second original skiing data.

[0021] Optionally, the data processing unit further includes a smoothing filter unit;

[0022] The smoothing filter unit is connected to the data fusion unit and is used for performing smoothing filter processing on the second original skiing data output by the N data screening units and then inputting the data into the data fusion unit.

[0023] Optionally, the data processing unit further includes a post-processing unit;

[0024] For the ski slope dimension, the first original ski data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension and the filtering unit of the altitude dimension, so as to filter out abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension and the altitude dimension, and obtain second original ski data for calculating the target ski slope;

[0025] The post-processing unit is used to determine a ski slope according to the second original ski data, and calibrate a maximum slope among the ski slopes according to a mountain slope to obtain a target ski slope.

[0026] Optionally, the data processing unit further includes a downsampling unit;

[0027] The down-sampling unit is connected to the post-processing unit, and is used for down-sampling the second original skiing data, and inputting the sampled second original skiing data into the post-processing unit.

[0028] Optionally, the data acquisition device includes a global positioning system GPS and a barometer; the data processing unit also includes: a data fusion unit;

[0029] For the dimension of the number of ski trips, the first original ski data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension, so as to filter the abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension, and the altitude dimension, and obtain the second original ski data for calculating the target number of ski trips;

[0030] The data fusion unit is used to determine the target number of skiing trips based on the second original skiing data collected by the GPS when the global positioning system GPS is normal, and to determine the target number of skiing trips based on the second original skiing data collected by the barometer when the global positioning system GPS is abnormal.

[0031] Optionally, the data processing unit further includes a downsampling unit and a smoothing filtering unit;

[0032] The down-sampling unit is used to down-sample the second original skiing data and input the sampled second original skiing data into the smoothing filter unit;

[0033] The smoothing filter unit is used to perform smoothing filter processing on the sampled second original skiing data, and input the filtered second original skiing data into the data fusion unit.

[0034] Optionally, the data acquisition device includes a global positioning system GPS and a barometer; the data processing unit also includes a smoothing filter unit, a data fusion unit and a post-processing unit;

[0035] With respect to the altitude dimension, the first original skiing data is sequentially input into the smoothing filter unit, the data fusion unit and the post-processing unit to obtain a target altitude;

[0036] The data fusion unit is used to determine the fused altitude at the current moment according to the target altitude output at the previous moment, the altitude collected by the global positioning system GPS and the altitude determined based on the first original skiing data collected by the barometer, when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated and is not at the bottom of the slope, and determine the fused altitude as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal and the barometer is calibrated, determine the altitude determined based on the data collected by the barometer as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated and is at the bottom of the slope, determine the altitude collected by the global positioning system GPS as the target altitude at the current moment.

[0037] Optionally, the ski monitoring system further comprises: a calorie calculation device;

[0038] The data collection device is also used to collect the user's heart rate, user information, motion status and sliding speed;

[0039] The calorie calculation device is used to determine the user's heart rate calories based on the user's heart rate and user information, and to determine the consumed calories based on the heart rate calories, user information, exercise status and sliding speed.

[0040] Optionally, the calorie calculation device includes a heart rate calorie prediction unit and a metabolic equivalent correction unit;

[0041] The heart rate calorie prediction unit is used to determine the user's heart rate calories based on the user's heart rate and user information;

[0042] The metabolic equivalent correction unit is used to determine a calorie range according to the motion state, and to determine the optimal metabolic equivalent calories according to the motion state, the gliding speed and the user information. If the heart rate calories are within the calorie range, the heart rate calories are determined as the consumed calories. If the heart rate calories exceed the calorie range, the optimal metabolic equivalent calories are determined as the consumed calories.

[0043] Optionally, the ski monitoring system further comprises: a data preprocessing device;

[0044] The data preprocessing device is used to filter the first original skiing data collected by the data collecting device to obtain the filtered first original skiing data, and send the filtered first original skiing data to the data processing device.

[0045] According to a second aspect of an embodiment of the present disclosure, a wearable device is provided, wherein the wearable device includes the ski monitoring system described in the first aspect of the present disclosure.

[0046] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0047] By adopting the above technical solution, the first original skiing data collected is analyzed in multiple dimensions to remove abnormal first original skiing data. In the process of removing abnormal first original skiing data, the skiing data are mutually penetrated and integrated, thereby improving the monitoring efficiency and accuracy of the skiing monitoring system. In addition, the skiing monitoring device is deployed on the wearable device, which improves the convenience of monitoring during skiing.

[0048] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0050] Figure 1 is a block diagram of a ski monitoring system according to an exemplary embodiment.

[0051] Figure 2 is a block diagram of another ski monitoring system according to an exemplary embodiment.

[0052] Figure 3 The diagram is a schematic diagram showing a method of determining a target taxiing speed according to an exemplary embodiment.

[0053] Figure 4The figure is a schematic diagram showing a method of determining a target number of ski trips according to an exemplary embodiment.

[0054] Figure 5 The diagram is a schematic diagram showing a method of determining a target altitude according to an exemplary embodiment.

[0055] Figure 6 is a schematic diagram showing a method of determining consumed calories according to an exemplary embodiment. DETAILED DESCRIPTION

[0056] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0057] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0058] The present invention provides a ski monitoring system and a wearable device, which performs a multi-dimensional analysis on the collected first original ski data to remove abnormal first original ski data, thereby achieving mutual penetration and integration between ski data, thereby improving the monitoring efficiency and accuracy of the ski monitoring system. In addition, the ski monitoring device is deployed on the wearable device, which improves the convenience of monitoring during skiing.

[0059] Figure 1 FIG. 1 is a block diagram of a ski monitoring system according to an exemplary embodiment. Figure 1 As shown, the ski monitoring system 100 may include: a data acquisition device 101 , a data processing device 102 and a data output device 103 .

[0060] The data acquisition device 101 is used to acquire first original skiing data related to skiing, and send the first original skiing data to the data processing device 102 .

[0061] For example, the data collection device 101 may include a global positioning system (GPS). Accordingly, the first original skiing data includes skiing data collected by GPS, for example, three types of data: altitude, longitude and latitude, and speed. Each time GPS collects data, the first original skiing data including the three types of data can be obtained.

[0062] As another example, the data collection device 101 may include a global positioning system GPS and a barometer. Accordingly, the first original skiing data includes the first original skiing data collected by the GPS and the first original skiing data collected by the barometer. The first original skiing data collected by the barometer includes the current air pressure and the sea level atmospheric pressure.

[0063] As another example, the data collection device 101 may include a global positioning system GPS, a barometer, and an adaptive cruise control ACC (Adaptive Cruise Control). Accordingly, the first original skiing data includes the first original skiing data collected by the GPS, the first original skiing data collected by the barometer, and the first original skiing data collected by the ACC.

[0064] Considering that the first original skiing data is collected only based on the global positioning system GPS, there may be accuracy defects for each dimension data, such as altitude, slope and other dimensional data. If skiing data is collected based on the global positioning system GPS, a barometer and an adaptive cruise control ACC, since the sampling rate of the adaptive cruise control ACC is higher than that of the GPS and the barometer, it will lead to higher power consumption. Therefore, in the present disclosure, the data collection device 101 including the global positioning system GPS and the barometer is used as an example for description.

[0065] The data processing device 102 includes a plurality of data screening units 1021 and a data processing unit 1022. Each data screening unit has its own data screening rule, each data screening rule is different, and each data screening unit is used to screen the first original skiing data, remove abnormal original skiing data, and obtain normal original skiing data.

[0066] For each skiing data dimension, N data filtering units use their own data filtering rules to filter the first original skiing data to obtain second original skiing data for calculating the target skiing parameters of this dimension, where N is an integer less than or equal to the number of data filtering units.

[0067] In the present disclosure, the skiing data dimension includes at least one of the following: speed dimension, distance dimension, altitude dimension, trip dimension, and slope dimension. For different skiing data dimensions, if the selected data screening units are exactly the same, the second original skiing data used to calculate the target skiing parameters of the different dimensions are the same. It should be understood that for different skiing data dimensions, the selected data screening units and the number of selected data screening units may be different in the data screening stage.

[0068] After the N data screening units screen out the second original skiing data for calculating the target skiing parameters of the dimension, the second original skiing data is input into the data processing unit 1022, and the data processing unit 1022 is used to determine the target skiing parameters under the dimension according to the second original skiing data. The data output device 103 is used to output the target skiing parameters of each skiing data dimension.

[0069] By adopting the above technical solution, the first original skiing data collected is analyzed in multiple dimensions to remove abnormal first original skiing data. In the process of removing abnormal first original skiing data, the skiing data are mutually penetrated and integrated, thereby improving the monitoring efficiency and accuracy of the skiing monitoring system. In addition, the skiing monitoring device is deployed on the wearable device, which improves the convenience of monitoring during skiing.

[0070] For ease of description, the following multiple data screening units include a filtering unit of a distance dimension or a speed dimension, a filtering unit of an acceleration dimension, and a filtering unit of an altitude dimension. It should be understood that, since the speed parameter and the distance parameter can be converted to each other when the time is known, the multiple data screenings may include a filtering unit of a distance dimension, a filtering unit of an acceleration dimension, and a filtering unit of an altitude dimension, or the multiple data screenings may include a filtering unit of a speed dimension, a filtering unit of an acceleration dimension, and a filtering unit of an altitude dimension.

[0071] The filtering unit of the distance dimension is used to determine the sliding distance according to the position data included in the first original skiing data, and filter out abnormal first original skiing data according to the change of the sliding distance. For example, the position data can be longitude and latitude data, and the sliding distance is determined according to the longitude and latitude, and when the change of the sliding distance is greater than a first threshold, the first original skiing data corresponding to the longitude and latitude data is filtered out. For example, GPS collects a first original skiing data at each moment, and the first original skiing data includes altitude data, longitude and latitude data, and speed data. If it is determined that the change of the sliding distance determined based on the longitude and latitude data in the first original skiing data collected at time t1 is greater than the first threshold, the first original skiing data collected at time t1 is determined as abnormal first original skiing data and filtered out.

[0072] The filtering unit of the speed dimension is used to filter out abnormal first original skiing data according to the original sliding speed included in the first original skiing data and the first sliding speed calculated based on the position data included in the first original skiing data. For example, the original sliding speed included in the first original skiing data refers to the sliding speed collected by GPS, and the first sliding speed refers to the sliding distance calculated based on the position data included in the first original skiing data, and the sliding distance is first-order derivative to obtain the calculated sliding speed. The abnormal first original skiing data is determined and filtered out according to the collected original sliding speed and the calculated first sliding speed. For example, the original sliding speed with a large difference between the two or the first original skiing data corresponding to the first sliding data is determined as the abnormal first original skiing data. Among them, the first original skiing data corresponding to the first sliding speed refers to the first original skiing data corresponding to the position data used when calculating the first sliding speed.

[0073] The filtering unit of the acceleration dimension is used to filter out abnormal first original skiing data according to the acceleration calculated based on the original skiing speed and / or calculated based on the position data included in the first original skiing data. For example, the first original skiing data with acceleration greater than the second threshold value can be determined as abnormal first original skiing data and filtered out. The acceleration can be obtained by taking the second-order derivative of the distance obtained based on the position data, or by taking the first-order derivative of the original skiing speed.

[0074] The filtering unit of the altitude dimension is used to filter out abnormal first original skiing data according to first altitude data and second altitude data included in the first original skiing data, wherein the first altitude data refers to altitude data measured based on a first sensor, and the second altitude data refers to altitude data measured based on a second sensor. For example, the first sensor may be a GPS, and the second sensor may be a barometer.

[0075] It should be understood that in actual applications, more data screening units with different data screening rules can be set up to further improve the continuity and integration of skiing data, as well as the monitoring efficiency and accuracy of the skiing monitoring system.

[0076] In addition, in the present disclosure, the ski monitoring system may further include a data pre-processing device. Figure 2 FIG. 1 is a block diagram of another ski monitoring system according to an exemplary embodiment. Figure 2 As shown, the ski monitoring system 100 further includes a data preprocessing device 104 , which is connected to the data acquisition device 101 and the data processing device 102 , respectively.

[0077] The data preprocessing device 104 is used for filtering the first original skiing data collected by the data collecting device 101 to obtain filtered first original skiing data, and sending the filtered first original skiing data to the data processing device 102 .

[0078] For example, the data preprocessing device 104 first performs data cleaning on the first raw skiing data, for example, cleaning to remove abnormal values, missing data or erroneous data. Then, the first raw skiing data collected by the sensor is first screened according to the horizontal precision factor and horizontal accuracy of the sensor that collects the first raw skiing data. For example, the first raw skiing data collected by the GPS is first screened according to the horizontal precision factor and horizontal accuracy of the GPS.

[0079] It should be understood that the screening of the first original skiing data by the data pre-processing device 104 can be regarded as the first round of screening. Subsequently, the data processing device 102 can perform a second round of screening on the first original skiing data after the first round of screening, that is, use multiple data screening units to screen out the second original skiing data for calculating the target skiing parameters of each dimension.

[0080] The specific implementation method for obtaining the target skiing parameter of each dimension is described below.

[0081] With respect to the sliding speed dimension, the first original skiing data is input into a filtering unit of a distance dimension or a speed dimension, a filtering unit of an acceleration dimension, and a filtering unit of an altitude dimension, so as to filter out abnormal first original skiing data in the distance or speed dimension, the acceleration dimension, and the altitude dimension, and obtain the second original skiing data for calculating the target sliding speed.

[0082] For example, Figure 2 As shown, the first original skiing data collected by the data acquisition device 101 is first input into the data preprocessing device 104 for a first round of screening to obtain the first original skiing data after the first round of screening. After that, the first original skiing data is input into the filtering unit 10211 of the distance dimension or the speed dimension, the filtering unit 10212 of the acceleration dimension and the filtering unit 10213 of the altitude dimension for filtering processing to obtain the second original skiing data for calculating the target sliding speed.

[0083] First, it should be understood that if the first original skiing data at the current moment is abnormal, the target skiing speed at the previous moment may be determined as the target skiing speed at the current moment.

[0084] Secondly, it should be understood that the order in which the first original skiing data after the first round of screening is input into the three filtering units is not limited, and can be as follows: Figure 2 The input order shown may also be other input orders, and the present disclosure does not make any specific limitation on this.

[0085] In one embodiment, the original skiing speed in the second original skiing data obtained above and used to calculate the target skiing speed may be directly determined as the target skiing data.

[0086] In another embodiment, in order to further improve the accuracy of the determined target sliding speed, a data fusion unit may be used to perform fusion processing to obtain the target sliding speed. For example, the data processing unit 1022 also includes a data fusion unit 10221. The data fusion unit 10221 is used to obtain the acceleration calculated based on the second original data and the second sliding speed calculated based on the position data included in the second original skiing data, and determine the target sliding speed according to the original sliding speed, the acceleration and the second sliding speed, as well as the historical sliding speed and the historical sliding distance.

[0087] The acceleration calculated based on the second original data refers to the acceleration obtained by calculating the sliding distance according to the position data included in the second original data and taking the second-order derivative of the sliding distance. The second sliding speed calculated based on the position data included in the second original skiing data refers to the speed obtained by calculating the sliding distance according to the position data included in the second original data and taking the first-order derivative of the sliding distance. The original sliding speed refers to the speed included in the second original skiing data.

[0088] Figure 3 FIG. 1 is a schematic diagram showing a method of determining a target taxiing speed according to an exemplary embodiment. Figure 3 As shown, first, the original sliding speed collected by GPS, the second sliding speed calculated based on the position data included in the second original skiing data, and the acceleration calculated based on the second original skiing data are fused to obtain the fused speed, and then the fused speed, the historical sliding speed, and the historical sliding distance are tracked to obtain the target sliding speed. The target sliding speed may include the real-time sliding speed and / or the maximum sliding speed.

[0089] In this way, the first original skiing data is screened using a filtering unit for distance dimension or speed dimension, a filtering unit for acceleration dimension, and a filtering unit for altitude dimension to obtain the second original skiing data for calculating the target sliding speed, thereby achieving mutual penetration and fusion between the original skiing data and improving the accuracy of the determined sliding speed.

[0090] With respect to the sliding distance dimension, the first original skiing data is input into a filtering unit of a distance dimension or a speed dimension and a filtering unit of an acceleration dimension to filter the abnormal first original skiing data in the distance dimension or the speed dimension and the acceleration dimension to obtain the second original skiing data for calculating the target sliding distance.

[0091] For example, Figure 2 As shown, the first original skiing data collected by the data acquisition device 101 is first input into the data preprocessing device 104 for a first round of screening to obtain the first original skiing data after the first round of screening. Then, the first original skiing data after the first round of screening is input into the filtering unit 10211 of the distance dimension or the speed dimension and the filtering unit 10212 of the acceleration dimension to filter the abnormal first original skiing data in the distance dimension or the speed dimension and the acceleration dimension to obtain the second original skiing data for calculating the target sliding distance.

[0092] Similarly, there is no limitation on the order in which the first original skiing data is input into the filtering unit 10211 of the distance dimension or the speed dimension and the filtering unit 10212 of the acceleration dimension.

[0093] In one embodiment, the target skiing distance may be calculated based on the position data in the second original skiing data.

[0094] In another embodiment, in order to further improve the accuracy of the determined target sliding distance, a data fusion unit may be used to perform fusion processing to obtain the target sliding distance. For example, the data fusion unit 10221 is used to determine the target sliding distance based on the second original skiing data. For example, the data fusion unit 10221 determines the target sliding distance based on the second original skiing data using a Kalman fusion algorithm.

[0095] The target gliding distance may include at least one of the following: real-time gliding distance, total gliding distance, and total distance including cable car ride and gliding.

[0096] In this way, the first original skiing data is analyzed by using a filter unit of a distance dimension or a speed dimension, and a filter unit of an acceleration dimension, so that the skiing data can be interpenetrated and integrated with each other, thereby improving the accuracy of the determined sliding distance.

[0097] In addition, the data processing unit 1022 may also include a smoothing filter unit 10222. The smoothing filter unit 10222 is connected to the data fusion unit 10221, and is used to perform smoothing filter processing on the second original skiing data output by the N data screening units and then input the data into the data fusion unit 10222. The smoothing filter unit 10222 may use Butterworth filtering, and for different data, analyze the spectrum characteristics to filter the original data and the filter output data of the above dimensions.

[0098] For the sliding speed dimension, the smoothing filter unit 10222 Figure 2 The second original skiing data output by the three filtering units are smoothed and filtered, and the filtered second original skiing data are input into the data fusion unit 10221, so that the data fusion unit 10221 can generate the second original skiing data according to the filtering process. Figure 3 The target taxiing speed is obtained in the manner shown.

[0099] For the sliding distance dimension, the smoothing filter unit 10222 Figure 2 The second original skiing data output by the filtering unit of the distance dimension or speed dimension and the filtering unit of the acceleration dimension are smoothed and filtered, and the filtered second original skiing data are input into the data fusion unit 10221, so that the data fusion unit 10221 obtains the target sliding distance according to the Kalman fusion algorithm.

[0100] It is worth noting that, with respect to the sliding speed dimension and the sliding distance dimension, the first original skiing data mentioned above may refer to the first original skiing data collected by using GPS.

[0101] For the ski slope dimension, the first original ski data is input into a filter unit of a distance dimension or a speed dimension, a filter unit of an acceleration dimension, and a filter unit of an altitude dimension, so as to filter out abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension, and the altitude dimension, and obtain second original ski data for calculating a target ski slope. The ski slope may include a real-time ski slope and / or a maximum ski slope. In addition, the first original ski data may include first original ski data collected by a GPS and first original ski data collected by a barometer.

[0102] Similarly, there is no limitation on the order in which the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension.

[0103] In one embodiment, in order to further improve the accuracy of the determined target ski slope, the second original ski data may be post-processed. Figure 2 As shown, the data processing unit 1022 includes a post-processing unit 10223. Accordingly, the second original skiing data is input into the post-processing unit 10223 to obtain a target skiing slope.

[0104] For example, the post-processing unit 10223 determines the ski slope according to the second original ski data, and calibrates the maximum slope of the ski slope according to the mountain slope to obtain the target ski slope, wherein the maximum slope of the target ski slope cannot exceed a preset multiple of the mountain slope.

[0105] For example, the post-processing unit 10223 may determine the ski slope by the following formula: slope=actan(Δh / Δs), where Δh represents the altitude change within a period of time Δt, and Δs represents the accumulated distance within a period of time Δt.

[0106] In addition, the mountain slope refers to the slope of the mountain where the current skiing activity is located. The slope may be the mountain slope calculated based on historically monitored slope data, or the mountain slope measured by the user.

[0107] Furthermore, in the present disclosure, before the second original skiing data is post-processed to obtain the target ski slope, the second original skiing data may be downsampled to further improve the accuracy of the determined target ski slope.

[0108] For example, Figure 2 As shown, the data processing device 102 further includes a downsampling unit 10224. The downsampling unit 10224 is configured to downsample the second original skiing data and input the sampled second original skiing data into the post-processing unit 10223. In this way, the accuracy of the determined target ski slope is further improved.

[0109] With respect to the dimension of the number of ski trips, the first original ski data is input into a filtering unit of a distance dimension or a speed dimension, a filtering unit of an acceleration dimension, and a filtering unit of an altitude dimension, so as to filter abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension, and the altitude dimension, and obtain the second original ski data for calculating the target number of ski trips.

[0110] Similarly, there is no limitation on the order in which the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension.

[0111] In one embodiment, the number of skiing trips determined based on the second original skiing data collected by GPS may be directly determined as the target number of skiing trips.

[0112] However, considering that the accuracy of the second original skiing data collected when the GPS is abnormal is not high, in the present disclosure, after obtaining the second original skiing data used to calculate the target number of ski trips, the data fusion unit 10221 determines the target number of skiing trips based on the second original skiing data collected by the GPS when the global positioning system GPS is normal, and determines the target number of skiing trips based on the second original skiing data collected by the barometer when the global positioning system GPS is abnormal.

[0113] Figure 4 FIG. 1 is a schematic diagram showing a method for determining a target number of ski trips according to an exemplary embodiment. Figure 4As shown, when starting skiing, first, determine whether the GPS is abnormal at the beginning, for example, determine whether the GPS is lost. If not, determine whether the GPS loss duration during the exercise exceeds a preset duration, for example, the preset duration is 60s. If it does not exceed the preset duration, the number of trips determined based on the second original skiing data collected by the GPS is used as the target number of skiing trips, or when the loss period does not exceed the preset duration, the number of trips most recently determined based on the second original skiing data collected by the GPS is determined as the target number of skiing trips. If the GPS loss duration during the exercise exceeds the preset duration, the number of trips determined based on the second original skiing data collected by the barometer is determined as the target number of skiing trips, and after the GPS is restored by itself, the number of trips determined based on the second original skiing data collected by the GPS is determined as the target number of skiing trips. If the GPS is lost at the beginning, it is determined whether the barometer is lost. If the barometer is lost, the number of ski trips will not be monitored. If the barometer is not lost, the number of ski trips determined based on the second original ski data collected by the barometer will be determined as the target number of ski trips. After the GPS recovers itself, the number of ski trips determined based on the second original ski data collected by the GPS will be determined as the target number of ski trips.

[0114] In order to further improve the accuracy of the determined target number of ski trips, the second original ski data may be subjected to downsampling and smoothing filtering. Figure 2 As shown, the second original skiing data is sequentially input into the down-sampling unit 10224 and the smoothing filter unit 10222.

[0115] For example, the downsampling unit 10224 is used to downsample the second original skiing data, and input the sampled second original skiing data into the smoothing filter unit 10222; the smoothing filter unit 10222 is used to smooth filter the second original skiing data, and input the filtered second original skiing data into the data fusion unit 10221.

[0116] Considering that the ski slope is determined according to the altitude in the second original ski data, in order to avoid identifying a trip as soon as the altitude drops, thereby causing erroneous monitoring of the number of ski trips, in the present disclosure, the second original ski data is first downsampled to avoid erroneous identification and improve the accuracy of the target number of ski trips finally determined. Afterwards, the adopted second original ski data is smoothed and filtered to obtain relatively smooth second original ski data, and then when the data fusion unit 10221 obtains the target number of ski trips based on the second original ski data after the smoothing and filtering, it can ensure that the target number of ski trips curve finally obtained is relatively smooth.

[0117] For the altitude dimension, the first original skiing data is sequentially input into the smoothing filter unit 10222, the data fusion unit 10221 and the post-processing unit 10223 to obtain the target altitude. In the present disclosure, the target altitude may include at least one of the following: real-time absolute altitude, minimum altitude and maximum altitude.

[0118] The smoothing filter unit 10222 performs smoothing filtering based on the original altitude collected by the GPS and the altitude determined based on the first original skiing data collected by the barometer.

[0119] The data fusion unit 10221 is used to determine the fused altitude at the current moment according to the target altitude output at the previous moment, the altitude collected by the global positioning system GPS, and the altitude determined based on the first original skiing data collected by the barometer when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated, and the skier is not at the bottom of the slope, and determine the fused altitude as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal and the barometer is calibrated, determine the altitude determined based on the data collected by the barometer as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated, and the skier is at the bottom of the slope, determine the altitude collected by the global positioning system GPS as the target altitude. In the data fusion unit 10221, the altitude collected by the GPS refers to the altitude obtained after smoothing and filtering the original altitude collected by the GPS.

[0120] For example, Figure 5 FIG. 1 is a schematic diagram showing a method of determining a target altitude according to an exemplary embodiment. Figure 5 As shown, when skiing begins, first, determine whether the GPS is abnormal, for example, determine whether the GPS is lost. If the GPS is lost and the barometer is also lost, or if the GPS is not lost and the barometer is lost, the target altitude output at the previous moment is determined as the target altitude at the current moment. If the GPS is lost and the barometer is not lost, the altitude determined based on the first original skiing data collected by the barometer is determined as the target altitude. If the GPS is not lost and the barometer is not lost, the fused altitude increment at the current moment is determined based on the altitude collected by the GPS and the altitude determined based on the first original skiing data collected by the barometer, and the sum of the target altitude output at the previous moment and the fused altitude increment at the current moment is determined as the fused altitude at the current moment.

[0121] Considering that temperature drift and environmental influences may cause errors in the barometer, and the errors will be accumulated, it is also necessary to determine whether the barometer is calibrated. For example, if the barometer is calibrated, the altitude determined based on the first original skiing data collected by the barometer is determined as the target altitude regardless of whether it is currently at the bottom of the slope or not. If it is at the bottom of the slope and the barometer is not calibrated, the altitude collected by the GPS is obtained, and the altitude collected by the GPS is determined as the target altitude. If it is not currently at the bottom of the slope and the barometer is not calibrated, the fused altitude is determined as the target altitude. For example, if the altitude is 0, it is considered to have reached the bottom of the slope, otherwise it is considered not to have reached the bottom of the slope.

[0122] It should be understood that in Figure 5 In the step, when it is determined that the bottom of the slope has not been reached and the barometer has not been calibrated, the fused altitude increment at the current moment is determined according to the altitude collected by the GPS and the altitude determined based on the first original skiing data collected by the barometer, and the sum of the target altitude output at the previous moment and the fused altitude increment at the current moment is determined. The present disclosure does not make specific limitations on this.

[0123] In addition, the collected skiing data can be sequentially input into the smoothing filter unit 10222, the data fusion unit 10221 and the post-processing unit 10223 to obtain the descent height, that is, the accumulated descent height.

[0124] In the present disclosure, in addition to being able to calculate external motion-related parameters during skiing, the skier's internal body functional state can also be informed. For example, the ski monitoring system provided by the present disclosure can also monitor the calories consumed by the skier.

[0125] For example, the ski monitoring system also includes: a calorie calculation device. The data acquisition device can also collect the user's heart rate, user information, motion state and sliding speed. Among them, the user information includes but is not limited to height, weight, age, gender, etc. The motion state may include a cable car state, a walking state and a skiing state. The calorie calculation device is used to determine the user's heart rate calories based on the user's heart rate and user information, and determine the consumed calories based on the heart rate calories, user information, motion state and sliding speed. Among them, the consumed calories may include the calories consumed by skiing and / or the total calories consumed. The total calories consumed may refer to the calories consumed by cable car riding, walking and skiing as a whole. In addition, heart rate calories refer to calories determined based on heart rate.

[0126] For example, the calorie calculation device includes a heart rate calorie prediction unit and a metabolic equivalent correction unit. The heart rate calorie prediction unit is used to determine the user's heart rate calories according to the user's heart rate and user information. For example, the heart rate calorie prediction unit can be a calorie prediction model based on heart rate, which can be pre-trained according to a conventional training method. Therefore, the user's heart rate and user information are input into the heart rate calorie prediction unit, and the heart rate calorie prediction unit outputs the heart rate calories.

[0127] The metabolic equivalent correction unit determines a calorie range according to the motion state, and determines the optimal metabolic equivalent calories according to the motion state, the gliding speed and the user information. If the heart rate calories are within the calorie range, the heart rate calories are determined as the actual calories. If the heart rate calories exceed the calorie range, the optimal metabolic equivalent calories are determined as the consumed calories.

[0128] Figure 6 FIG. 1 is a schematic diagram showing a method of determining calories consumed according to an exemplary embodiment. Figure 6 As shown, first, the maximum metabolic equivalent value and the minimum metabolic equivalent value are determined according to the motion state, and the maximum calorie value and the minimum calorie value are obtained based on the maximum metabolic equivalent value and the minimum metabolic equivalent value, respectively, and then the calorie range is obtained. At the same time, the optimal metabolic equivalent is determined according to the motion state, the sliding speed and the user information, and the optimal metabolic equivalent calories are obtained based on the optimal metabolic equivalent. Among them, the maximum metabolic equivalent value, the minimum metabolic equivalent value, and the optimal metabolic equivalent calories can be determined by conventional technical means. Next. Determine whether the heart rate calories are within the calorie range. If the heart rate calories are within the calorie range, the heart rate calories are determined as the actual calories. If the heart rate calories exceed the calorie range, the optimal metabolic equivalent calories are determined as the actual calories.

[0129] In this way, the ski monitoring system provided by the present invention can output relatively accurate ski data. For newcomers with weak skiing foundation, the data such as the maximum altitude and maximum slope provided by the ski monitoring system can help users know whether the level of the current ski slope is suitable for them, so that they can choose a ski slope that suits them, ensure the user's skiing safety, and enhance the user's skiing experience.

[0130] For skiing enthusiasts who have a certain skiing foundation, the ski monitoring system provides data such as maximum speed and sliding distance to help users know whether their sliding ability has improved. For professional skiers, the ski monitoring system provides data such as maximum speed, average speed, sliding distance, and sliding time in each trip, which helps professional skiers carefully analyze and compare their own sliding status. It is a very useful and intuitive data display for athletes.

[0131] Therefore, the ski monitoring system provided by the present invention has reference value for skiers of any level. Multi-dimensional analysis of ski data can help skiers of different levels recognize the standards of the ski slopes, identify their own skiing abilities, and customize the analysis of each skiing detail, thereby improving the user experience.

[0132] In addition, the update strategy of skiing data can also be customized. For example, Table 1 is a customized update strategy of each skiing data. Among them, strategy update means not real-time update but update according to preset strategy.

[0133] Table 1

[0134] Skiing data Update strategy Activity Calories Real-time updates Total Calories Real-time updates Real-time sliding distance Real-time updates Real-time total distance Real-time updates Real-time speed Real-time updates Real-time maximum speed Policy Update Real-time absolute altitude Real-time updates Real-time maximum altitude Real-time updates Real-time minimum altitude Real-time updates Real-time downhill Real-time updates Real-time slope Real-time updates Maximum slope Policy Update Real-time trip count Real-time updates Total trips Real-time updates

[0135] Based on the same inventive concept, the present disclosure also provides a wearable device, which includes the ski monitoring system provided by the present disclosure.

[0136] For example, the wearable device may be a smart ski helmet.

[0137] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0138] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A ski monitoring system, characterized in that: The ski monitoring system is deployed on a wearable device, and the ski monitoring system includes: A data collection device, used for collecting first original skiing data related to skiing, and sending the first original skiing data to a data processing device; The data processing device includes a plurality of data screening units and a data processing unit, wherein for each skiing data dimension, N data screening units use respective data screening rules to screen the first original skiing data to obtain second original skiing data for calculating the target skiing parameter of the dimension, and input the second original skiing data into the data processing unit, and the data processing unit is used to determine the target skiing parameter under the dimension according to the second original skiing data; different data screening units have different data screening rules, N is an integer less than or equal to the number of filtering units, and the skiing data dimension includes at least one of the following: speed dimension, distance dimension, altitude dimension, trip number dimension, and slope dimension; The data output device is used to output the target skiing parameter of each skiing data dimension.

2. The ski monitoring system according to claim 1, characterized in that: The multiple data screening units include a filtering unit for acceleration dimension and a filtering unit for altitude dimension; the multiple data screening units also include a filtering unit for distance dimension or speed dimension; a filtering unit in a distance dimension, configured to determine a sliding distance according to the position data included in the first original skiing data, and to filter out abnormal first original skiing data according to a change in the sliding distance; a filtering unit in a speed dimension, configured to filter out abnormal first original skiing data according to an original skiing speed included in the first original skiing data and a first skiing speed calculated based on position data included in the first original skiing data; The filtering unit of the acceleration dimension is used to filter out abnormal first original skiing data according to the acceleration calculated based on the original skiing speed and / or calculated based on the position data included in the first original skiing data; The filtering unit of the altitude dimension is used to filter out abnormal first original skiing data according to the first altitude data and the second altitude data included in the first original skiing data; The first altitude data refers to altitude data measured by a first sensor, and the second altitude data refers to altitude data measured by a second sensor.

3. The ski monitoring system according to claim 2, characterized in that: The data processing unit also includes a data fusion unit; For the sliding speed dimension, the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension, so as to filter out abnormal first original skiing data in the distance or speed dimension, the acceleration dimension, and the altitude dimension, and obtain second original skiing data for calculating the target sliding speed; The data fusion unit is used to obtain the acceleration calculated based on the second original skiing data and the second skiing speed calculated based on the position data included in the second original skiing data, and determine the target skiing speed based on the original skiing speed, the acceleration and the second skiing speed, as well as the historical skiing speed and the historical skiing distance.

4. The ski monitoring system according to claim 2, characterized in that: The data processing unit also includes a data fusion unit; For the sliding distance dimension, the first original skiing data is input into the filtering unit of the distance dimension or the speed dimension and the filtering unit of the acceleration dimension, so as to filter the abnormal first original skiing data in the distance dimension or the speed dimension and the acceleration dimension, and obtain the second original skiing data for calculating the target sliding distance; The data fusion unit is used to determine a target skiing distance according to the second original skiing data.

5. The ski monitoring system according to claim 3 or 4, characterized in that: The data processing unit also includes a smoothing filter unit; The smoothing filter unit is connected to the data fusion unit, and is used for performing smoothing filter processing on the second original skiing data output by the N data screening units and then inputting the data into the data fusion unit.

6. The ski monitoring system according to claim 2, characterized in that: The data processing unit also includes a post-processing unit; For the ski slope dimension, the first original ski data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension and the filtering unit of the altitude dimension, so as to filter out abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension and the altitude dimension, and obtain second original ski data for calculating the target ski slope; The post-processing unit is used to determine a ski slope according to the second original ski data, and calibrate a maximum slope among the ski slopes according to a mountain slope to obtain a target ski slope.

7. The ski monitoring system according to claim 6, characterized in that The data processing unit also includes a downsampling unit; The down-sampling unit is used to down-sample the second original skiing data and input the sampled second original skiing data into the post-processing unit.

8. The ski monitoring system according to claim 2, characterized in that: The data acquisition device includes a global positioning system GPS and a barometer; the data processing unit also includes: a data fusion unit; For the dimension of the number of ski trips, the first original ski data is input into the filtering unit of the distance dimension or the speed dimension, the filtering unit of the acceleration dimension, and the filtering unit of the altitude dimension, so as to filter the abnormal first original ski data in the distance dimension or the speed dimension, the acceleration dimension, and the altitude dimension, and obtain the second original ski data for calculating the target number of ski trips; The data fusion unit is used to determine the target number of ski trips based on the second original ski data collected by the GPS when the global positioning system GPS is normal, and to determine the target number of ski trips based on the second original ski data collected by the barometer when the global positioning system GPS is abnormal.

9. The ski monitoring system according to claim 8, characterized in that The data processing unit also includes a downsampling unit and a smoothing filter unit; The down-sampling unit is used to down-sample the second original skiing data and input the sampled second original skiing data into the smoothing filter unit; The smoothing filter unit is used to perform smoothing filter processing on the sampled second original skiing data, and input the filtered second original skiing data into the data fusion unit.

10. The ski monitoring system according to claim 2, characterized in that: The data acquisition device includes a global positioning system GPS and a barometer; the data processing unit also includes a smoothing filter unit, a data fusion unit and a post-processing unit; With respect to the altitude dimension, the first original skiing data is sequentially input into the smoothing filter unit, the data fusion unit and the post-processing unit to obtain a target altitude; The data fusion unit is used to determine the fused altitude at the current moment according to the target altitude output at the previous moment, the altitude collected by the global positioning system GPS and the altitude determined based on the first original skiing data collected by the barometer, when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated and is not at the bottom of the slope, and determine the fused altitude as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal and the barometer is calibrated, determine the altitude determined based on the data collected by the barometer as the target altitude at the current moment; when both the global positioning system GPS and the barometer are normal, the barometer is not calibrated and is at the bottom of the slope, determine the altitude collected by the global positioning system GPS as the target altitude at the current moment.

11. The ski monitoring system according to claim 1, characterized in that: The ski monitoring system also includes: a calorie calculation device; The data collection device is also used to collect the user's heart rate, user information, motion status and sliding speed; The calorie calculation device is used to determine the user's heart rate calories based on the user's heart rate and user information, and to determine the consumed calories based on the heart rate calories, user information, exercise status and sliding speed.

12. The ski monitoring system according to claim 11, characterized in that The calorie calculation device includes a heart rate calorie prediction unit and a metabolic equivalent correction unit; The heart rate calorie prediction unit is used to determine the user's heart rate calories based on the user's heart rate and user information; The metabolic equivalent correction unit is used to determine a calorie range according to the motion state, and to determine the optimal metabolic equivalent calories according to the motion state, the gliding speed and the user information. If the heart rate calories are within the calorie range, the heart rate calories are determined as the consumed calories. If the heart rate calories exceed the calorie range, the optimal metabolic equivalent calories are determined as the consumed calories.

13. The ski monitoring system according to claim 1, characterized in that: The ski monitoring system further comprises: a data preprocessing device; The data preprocessing device is used to filter the first original skiing data collected by the data collecting device to obtain the filtered first original skiing data, and send the filtered first original skiing data to the data processing device.

14. A wearable device, characterized in that: The wearable device comprises a ski monitoring system as claimed in any one of claims 1-13.

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