CN114978894B - Code table parameter configuration method and code table - Google Patents
Code table parameter configuration method and code table Download PDFInfo
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- CN114978894B CN114978894B CN202210413415.6A CN202210413415A CN114978894B CN 114978894 B CN114978894 B CN 114978894B CN 202210413415 A CN202210413415 A CN 202210413415A CN 114978894 B CN114978894 B CN 114978894B
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- 238000004458 analytical method Methods 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 5
- 238000007405 data analysis Methods 0.000 claims description 3
- 230000033001 locomotion Effects 0.000 description 8
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
- H04L41/0806—Configuration setting for initial configuration or provisioning, e.g. plug-and-play
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62J—CYCLE SADDLES OR SEATS; AUXILIARY DEVICES OR ACCESSORIES SPECIALLY ADAPTED TO CYCLES AND NOT OTHERWISE PROVIDED FOR, e.g. ARTICLE CARRIERS OR CYCLE PROTECTORS
- B62J50/00—Arrangements specially adapted for use on cycles not provided for in main groups B62J1/00 - B62J45/00
- B62J50/20—Information-providing devices
- B62J50/21—Information-providing devices intended to provide information to rider or passenger
- B62J50/22—Information-providing devices intended to provide information to rider or passenger electronic, e.g. displays
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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- Signal Processing (AREA)
- Mechanical Engineering (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention provides a code table parameter configuration method and a code table, wherein the method comprises the following steps: when a user uses the code table for the first time, judging whether the code table is in an offline state, if the code table is in the offline state, acquiring riding data in real time after entering user basic information, carrying out parameter configuration through a microprocessor on the code table, and if the code table is not in the offline state, logging in a user account, and configuring code table parameters in a background server based on the riding data acquired in real time by the code table; when the user does not use the code table for the first time, the user riding data is collected in real time based on the code table and is uploaded to the background server, and the background server analyzes and configures code table parameters through big data. The code table can be replaced conveniently through the scheme, and the accuracy of the parameter configuration of the code table can be guaranteed.
Description
Technical Field
The invention belongs to the technical field of bicycle code tables, and particularly relates to a code table parameter configuration method and a code table.
Background
The implementation of each item of data in the bicycle code table is calculated according to a plurality of parameters, and the corresponding parameter sources are generally fixed values set by users or large mode values obtained by test evaluation of developers. In practice, the parameter values configured in this way are inaccurate and ambiguous, and the variability is particularly obvious for different user groups, so that the same group of configuration parameters is used for different characteristic groups, so that data which does not accord with the reality can be obtained, and meanwhile, the physical characteristics of the same person in different stages also have great variation, so that the accuracy of code table parameter configuration is greatly reduced.
Disclosure of Invention
In view of this, the embodiment of the invention provides a code table parameter configuration method and a code table, which are used for solving the problem of inaccurate configuration of the existing code table parameters.
In a first aspect of an embodiment of the present invention, there is provided a code table parameter configuration method, including:
when a user uses the code table for the first time, judging whether the code table is in an offline state, if the code table is in the offline state, acquiring riding data in real time after entering user basic information, carrying out parameter configuration through a microprocessor on the code table, and if the code table is not in the offline state, logging in a user account, and configuring code table parameters in a background server based on the riding data acquired in real time by the code table;
when the user does not use the code table for the first time, the user riding data is collected in real time based on the code table and is uploaded to the background server, and the background server analyzes and configures code table parameters through big data.
In a second aspect of an embodiment of the present invention, there is provided a code table including:
the data acquisition module is used for acquiring riding data through the sensor and inputting user basic information;
the data transmission module is used for transmitting the user basic information and the riding data to the background server or receiving the configuration parameters transmitted by the background server;
and the parameter configuration module is used for analyzing riding data based on a microprocessor on the code table, configuring code table parameters or configuring the code table parameters based on configuration parameters sent by a background server.
According to the embodiment of the invention, the code table parameters are configured based on analysis of the riding data of the user, so that the code table of the user is associated with the individual characteristics of the user, the accuracy of the code table parameters can be improved, and the code table can be replaced conveniently.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of a code table parameter configuration method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a code table parameter configuration method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a code table according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the term "comprising" and other similar meaning in the description of the invention or the claims and the above-mentioned figures is intended to cover a non-exclusive inclusion, such as a process, method or system, apparatus comprising a series of steps or elements, without limitation to the listed steps or elements. Furthermore, "first" and "second" are used to distinguish between different objects and are not used to describe a particular order.
Referring to fig. 1, a flow chart of a code table parameter configuration method provided by an embodiment of the present invention includes:
s101, when a user uses a code table for the first time, judging whether the code table is in an offline state, if the code table is in the offline state, acquiring riding data in real time after inputting user basic information, carrying out parameter configuration through a microprocessor on the code table, and if the code table is not in the offline state, logging in a user account, and configuring code table parameters in a background server based on the riding data acquired in real time by the code table;
the basic information of the user includes age, weight, height, region, usage habit and the like. The code table configuration refers to parameter items affected by individual feature differences of users or environments. The general code table configuration depends on user basic information, but along with the increase of the use times, configuration parameters gradually trend data actually obtained by a user in actual use, the information of each parameter item can be calculated through the analysis of an algorithm, and the parameter information also directly determines each function index of the code table. The stopwatch parameters may include, but are not limited to, user heart rate intervals, aerobic rate, aerobic power, training type preferences, font size, body style preferences, warming up, fat burning, extreme exercise intensity intervals, etc., typically requiring multiple stopwatches to be used to derive such configuration parameters.
The offline state refers to a state that the device is not connected to the network (may also be referred to as an offline state), and for the code table in the offline state, the user riding data may be stored in the memory of the code table, and the code table microprocessor may acquire the riding data and analyze the riding data through a predetermined algorithm to obtain parameter configuration conforming to the user characteristics. The predetermined algorithm performs analysis including recursive filtering, mean filtering, weighted filtering, and the like.
When the user is in an offline state or can be connected to a network, taking a user account as a user identifier, storing user basic information, uploading riding data acquired by a code table to an account corresponding to the user on a background server through a WiFi or cellular network, storing the account data in a specified database, carrying out algorithm analysis on the account data by a special processor to obtain parameter configuration which is more in line with the characteristics of the user, and transmitting the parameter configuration back to the code table end through WiFi or the cellular network for the user to use.
And judging whether the user has history use equipment, if so, importing history data, and if not, inputting user basic information, and analyzing the code table by the microprocessor to acquire data in real time for parameter configuration.
As shown in fig. 2, before using the code table, the user needs to determine whether to use for the first time, if so, whether to be in an offline state, and if so, whether to have a history code table device, and generally, the history code table parameters are synchronized to the current code table.
The sensor types corresponding to the code table include, but are not limited to, an acceleration sensor, a speed sensor, a pedal frequency sensor, a power sensor and the like.
S102, when the user does not use the code table for the first time, the user riding data is collected in real time based on the code table and is uploaded to the background server, and the background server analyzes and configures code table parameters through big data.
For users who do not use for the first time, the configuration parameters of the code table before can be imported, the riding data acquired by the current code table is analyzed through an algorithm to optimize the code table parameters so as to better accord with the current physical characteristics and the use style of the users.
The physical characteristics refer to physiological performances reflected by the body of the user under different intensity movements, and the data are comprehensively obtained by basic information of the user and various data acquired by the sensor. The usage style refers to a style of man-machine interaction between a user and a code table, and influence factors are determined by basic information of the user and the usage frequency, for example, the usage frequency of different data items can determine the display sequence of the data items, the user of different ages can display the font size of the code table gradually increases along with the ages, and the like.
The big data analysis is to upload various sensor data collected in a user code table to a background server, calculate related parameter values of the collected data through a specific algorithm, and transmit the parameter values back to the code table for configuration, wherein generally, each parameter has a corresponding specific algorithm.
In this embodiment, by improving the fixed parameter configuration in the code table to the dynamic parameter configuration, deviation from the real data due to individual variability of the user can be avoided; the data on the old equipment is synchronized to the new equipment, so that the loss of user data can be avoided; through background big data analysis configuration, the use of a user can be facilitated, the operation difficulty is reduced, and the accuracy of configuration parameters is ensured. Meanwhile, the pertinence is strong, and the functional compatibility is strong.
In one embodiment, a circular queue buffer is employed on the stopwatch or on the background server to store the collected riding data.
For a stopwatch or a background server, since the amount of riding data generated by a user is infinite, and the storage amount of the device is limited, the infinite data stored in a limited memory needs to be subjected to covering processing, namely, a ring queue buffer technology is adopted. The method is characterized in that data are stored in a queue with fixed length, the head and the tail of the queue are connected, and the situation of a team is tracked by respectively pointing to the positions of the tail and the head of the queue through two pointers. The pointer is moved forward accordingly, based on the increase and decrease of new data in the queue. Without having to dynamically operate on this queue. When the queue is full, new data will cover the data at the tail of the queue, the data at the head of the queue will be fetched when the data is fetched, and so on, the latest data is always stored in the queue, and the data transmission is performed in a FIFO (first in first out) mode.
In one embodiment, recursive filtering, mean filtering and weighted filtering are respectively performed on riding data acquired by the code table.
Because the human body can show intermittent movement trend, if the user rides data and the like, the situation that the theoretical body strength is smaller than the actual body strength when riding for a plurality of days continuously and the theoretical body strength is larger than the actual body strength when stopping riding for a plurality of days can be generated. The realization of algorithms such as recursive filtering, average filtering, weighted filtering and the like is introduced, and the data obtained from background big data is analyzed after passing through the filtering algorithm, so that interference caused by intermittent motion trend can be effectively reduced.
The mean filtering is a linear filtering mode, can well obtain a data average value, smooth special data of a certain riding time and filter random interference.
The recursive filtering is to set a queue with the length of N, put the collected data at the tail of the queue, and discard the data at the head of the queue at the same time, so as to ensure that N data in the queue are all the latest data, and solve the problem that the motion data is affected by real-time performance after the motion data are filtered by the average value.
The weighted filtering is to apply different weights to the data at different moments, and generally, the closer the data at the moment is, the larger the weight acquisition is, the larger the weight coefficient of the new sampled data value is, so as to improve the influence of the real-time property of the data.
Illustratively, the user purchases a new cycle chart, and needs to fill in personal basic information and parameter configuration when using the chart for the first time, but specific data cannot be clearly obtained when filling in the wheel diameter of the bicycle because the user purchases the bicycle for many years. But this code table has the function of exporting the old equipment usage data, the usage data in the old code table is sent to the new code table through Bluetooth, and at this time, the new code table is matched through the original configuration data of the original user to obtain the bicycle wheel diameter which is most suitable for the user.
When the user just uses the stopwatch, the most suitable heart rate warning value is assumed to be 120 times/min, and after continuous riding is performed for a plurality of times, the most suitable heart rate warning value is assumed to be 140 times/min. The average heart rate data obtained from this time movement is 90, 100, 110, 100, 115, 110, 120, 125 (with continuous movement body function gradually increasing), and n is obtained by mean filtering 0 =110.5, and the superimposed recursive filtering (n=5) yields N-th pre-data 1 =103, later data n 2 =118, and the weighted filtering (weighting factor is incremented by "1") is superimposed to obtain the forward data n 3 =99.67, post data n 4 =120. After the user continuously stops riding for a plurality of days, the most suitable heart rate warning value is actually reduced to 120 times/min, 5 groups of new data 95, 105, 100, 105 and 110 are obtained after riding on a certain day, and n is obtained through mean filtering 5 =108, and superimposed recursive filtering (n=5) to obtain N 6 =103, and the weighted filtering (weight coefficient is incremented by "1") is superimposed to obtain n 7 =101. Each filtered value can be used as the current heart rate warning value.
n 0 ＝(90+100+110+100+115+115+110+120+120+125)/10＝110.5
n 1 ＝(90+100+110+100+115)/5＝103
n 2 ＝(115+110+120+120+125)/5＝118
n 3 ＝(90*5+100*4+110*3+100*2+115)/15＝99.67
n 4 ＝(115+110*2+120*3+120*4+125*5)/15＝120
n 5 ＝(90+100+110+100+115+115+110+120+120+125+95+105+100+105+110)/15＝108
n 6 ＝(95+105+100+105+110)/5＝103
n 7 ＝(95*5+105*4+100*3+105*2+110)/15＝101
The following table shows:
| early data | Post-period data | Post-stop motion data | |
| Actual data | 120 | 140 | 120 |
| Mean value filtering | 110.5+20＝130.5 | 110.5+20＝130.5 | 108+20＝128 |
| Superimposed recursive filtering | 103+20＝123 | 118+20＝138 | 103+20＝123 |
| Superposition weighted filtering | 99.67+20＝119.67 | 120+20＝140 | 101+20＝121 |
Therefore, the accuracy of the data can be effectively improved through the superposition filtering algorithm.
It should be understood that the sequence number of each step in the above embodiment does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not be construed as limiting the implementation process of the embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a code table according to an embodiment of the present invention, where the system includes:
the data acquisition module 310 is used for acquiring riding data through a sensor and inputting user basic information;
the data acquisition module comprises a sensor and is used for acquiring riding data of a user based on the sensor, and the code table is associated with terminal equipment for inputting information.
The data transmission module 320 is configured to send the user basic information and the riding data to the background server, or receive the configuration parameters sent by the background server;
the transmission module comprises a wireless communication unit for communicating with a background server, and a Bluetooth unit for transmitting data with old code table equipment.
The parameter configuration module 330 is configured to analyze the riding data based on the microprocessor on the code table, configure the code table parameters, or perform the configuration of the code table parameters based on the configuration parameters sent by the background server.
The parameter configuration module comprises a microprocessor, and the microprocessor performs parameter configuration based on a specific algorithm by acquiring riding data on a memory. Or receiving the data transmitted by the background server, and directly completing parameter configuration.
And judging whether the user has history use equipment, importing history data if the user has the history use equipment, inputting user basic information if the user does not have the history use equipment, and carrying out parameter configuration through a parameter configuration module.
Preferably, the collected riding data is buffered and stored on the code table by adopting a ring queue.
The background server can also adopt ring queue buffer for data storage.
Preferably, the parameter configuration module includes:
the filtering unit is used for respectively carrying out recursive filtering, average filtering and weighted filtering on riding data acquired by the code table.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A code table parameter configuration method, comprising:
when a user uses the code table for the first time, judging whether the code table is in an offline state, if the code table is in the offline state, acquiring riding data in real time after entering user basic information, carrying out parameter configuration through a microprocessor on the code table, and if the code table is not in the offline state, logging in a user account, and configuring code table parameters in a background server based on the riding data acquired in real time by the code table;
when the user does not use the code table for the first time, the user riding data is collected in real time based on the code table and is uploaded to the background server, and the background server analyzes and configures code table parameters through big data.
2. The method of claim 1, wherein entering user base information if the code table is offline comprises:
judging whether a user has history use equipment, importing history data if the user has the history use equipment, inputting user basic information if the user does not have the history use equipment, and acquiring data in real time through a microprocessor analysis code table to perform parameter configuration.
3. The method of claim 1, wherein the collected riding data is buffered using a circular queue on the stopwatch or on the background server.
4. The method of claim 1, wherein the background server comprises, before configuring the code table parameters by big data analysis:
and performing recursive filtering, mean filtering and weighted filtering on riding data acquired by the code table respectively.
5. A code table, comprising:
the data acquisition module is used for acquiring riding data through the sensor and inputting user basic information;
the data transmission module is used for transmitting the user basic information and the riding data to the background server or receiving the configuration parameters transmitted by the background server;
and the parameter configuration module is used for analyzing riding data based on a microprocessor on the code table, configuring code table parameters or configuring the code table parameters based on configuration parameters sent by a background server.
6. The code table of claim 5, wherein the entering user base information comprises:
if the code table is used for the first time by the user and the code table is in an offline state, judging whether the user has history use equipment, if so, importing history data, and if not, inputting user basic information, and carrying out parameter configuration through a parameter configuration module.
7. The code table of claim 5, wherein a circular queue is employed on the code table to buffer the collected riding data.
8. The code table of claim 5, wherein the parameter configuration module comprises:
the filtering unit is used for respectively carrying out recursive filtering, average filtering and weighted filtering on riding data acquired by the code table.
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| CN205320142U (en) * | 2015-12-03 | 2016-06-15 | 昆山研达电脑科技有限公司 | Intelligence code table system |
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Address after: 430000 No. 1-5, floor 3, building 4, creative workshop, phase III, Wuhan creative world, No. 16, yezhihu West Road, Hongshan street, Hongshan District, Wuhan City, Hubei Province Applicant after: WUHAN QIWU TECHNOLOGY Co.,Ltd. Address before: 430000 floor 2, building B, Zhongshi data industrial incubator, No. 10, Wenxiu street, Shucheng Road, Hongshan District, Wuhan City, Hubei Province Applicant before: WUHAN QIWU TECHNOLOGY Co.,Ltd. |
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| GR01 | Patent grant | ||
| GR01 | Patent grant |