Intelligent bicycle speed change method and system based on sensor data

Abstract

The invention relates to the technical field of bicycles, in particular to an intelligent bicycle speed change method and system based on sensor data, and the method comprises the steps: obtaining an initial model set of a bicycle, obtaining a plurality of speed change proportion sets based on the initial model set, obtaining a speed change strategy group set based on the plurality of speed change proportion sets and a speed change strategy construction unit, obtaining a target model and a target riding mode, confirming a target speed change strategy group in the speed change strategy group set based on the target model and the target riding mode, obtaining a driving feature sequence group and a user feature sequence group, and obtaining a user speed change strategy group by using the driving feature sequence group and the user feature sequence group; and searching a target speed change proportion in the target speed change strategy group, and adjusting the adjusted bicycle by using the target speed change proportion to realize intelligent speed change of the bicycle. According to the invention, the accuracy and the intelligent degree of intelligent speed change of the bicycle can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bicycles, and in particular to a bicycle intelligent speed changing method and system based on sensor data. Background Art

[0002] With the gradual improvement of environmental awareness and fitness awareness, cycling has become a popular short-distance travel method, entertainment project and hobby. At the same time, with the development of bicycle technology, variable-speed bicycles have gradually transformed from traditional means of transportation to multi-functional bicycles that integrate sports, fitness, tourism and leisure functions. Correspondingly, how to improve the intelligence of bicycles has become an urgent problem to be solved.

[0003] At present, most of the existing bicycles adopt a speed change system to achieve speed change of the bicycle.

[0004] Although the above method can realize the speed adjustment of the bicycle, the speed adjustment is only based on the speed of the bicycle during riding, and the user's riding intention, the user's physiological characteristics and the characteristics of the riding road cannot be considered during the adjustment. Therefore, accurately and intelligently realizing the speed adjustment of the bicycle has become an urgent problem to be solved. Summary of the invention

[0005] The present invention provides a bicycle intelligent speed change method based on sensor data and a computer-readable storage medium, the main purpose of which is to improve the accuracy and intelligence of the intelligent speed change of the bicycle.

[0006] To achieve the above object, the present invention provides a bicycle intelligent speed shifting method based on sensor data, comprising: Receiving an intelligent speed shift instruction, and confirming an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustment bicycle, and the intelligent speed shift system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit, and a speed shift strategy construction unit; Acquire an initial model set of a bicycle, wherein the initial model set includes a plurality of initial models, and acquire a plurality of speed ratio sets based on the initial model set; Based on the multiple speed ratio sets and the speed strategy building unit, a speed strategy group set is obtained, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A driving feature sequence group and a user feature sequence group are acquired by using a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The driving characteristic sequence group and the user characteristic sequence group are used to retrieve a target speed ratio in a target speed change strategy group, and the bicycle is adjusted using the target speed ratio to achieve intelligent speed change of the bicycle.

[0007] Optionally, acquiring a plurality of speed ratio sets based on the initial model set includes: Extract initial models from the initial model set in sequence, and perform the following operations on the extracted initial models: Based on the initial model, a front disc tooth number set and a rear disc tooth number set are identified, wherein the front disc tooth number set includes a plurality of front disc tooth numbers, and the rear disc tooth number set includes a plurality of rear disc tooth numbers; The front disc tooth numbers are sequentially extracted from the front disc tooth number set, and the following operations are performed on the extracted front disc tooth numbers: In a combined form, a plurality of tooth number combination nodes are obtained using the extracted front disc tooth number and rear disc tooth number sets, wherein the tooth number combination node includes a front disc tooth number and a rear disc tooth number; For each of the multiple tooth number combination nodes, perform the following operations: Calculate the ratio of the number of teeth on the front disc to the number of teeth on the rear disc in the tooth number combination node to obtain a theoretical ratio, summarize the theoretical ratios to obtain a theoretical ratio set, and perform a normalization operation on the theoretical ratios in the theoretical ratio set to obtain a normalized ratio set, wherein the normalized ratio set includes multiple normalized ratios; Obtaining a screening ratio range based on the extracted number of front disc teeth, and using the screening ratio range to identify a screening ratio set in the normalized ratio set, wherein the screening ratio set includes a plurality of screening ratios, and all of the screening ratios are within the screening ratio range; The screening ratio sets are aggregated to obtain a speed ratio set, and the speed ratio sets are aggregated to obtain multiple speed ratio sets.

[0008] Optionally, the acquiring the speed change strategy group set based on the multiple speed change ratio sets and the speed change strategy construction unit includes: confirming receipt of a speed change strategy instruction from a speed change strategy building unit, parsing the speed change strategy instruction, and obtaining a plurality of initial cadence ranges; In a combined form, a plurality of initial cadence ranges and a plurality of speed ratio sets are used to obtain a plurality of test nodes, wherein each test node includes an initial cadence range and a speed ratio; The following operations are performed on each of the multiple test nodes: Acquire a test node timing set based on the test node, a preset test interval time and a preset test period, wherein the test node timing set includes a plurality of test node timings, and the test node timings include: a test heart rate timing, a test speed timing and a test cadence timing; The following operations are performed for each test node timing in the test node timing set: Based on the pre-built sliding window and sliding step, the analysis heart rate time series is extracted in sequence from the test heart rate time series corresponding to the test node, and the following operations are performed on the extracted analysis heart rate time series: Acquire an analyzed heart rate variance based on the analyzed heart rate time series, compare the analyzed heart rate variance with a preset heart rate variance threshold, and after confirming that the analyzed heart rate variance is less than or equal to the heart rate variance threshold, obtain an analyzed heart rate mean using the analyzed heart rate time series, and based on the analyzed heart rate time series, respectively confirm an analyzed speed mean in a test speed time series and confirm an analyzed cadence mean in a test cadence time series; The analyzed heart rate mean, the analyzed speed mean and the analyzed cadence mean are respectively summarized to obtain an analyzed heart rate mean set, an analyzed speed mean set and an analyzed cadence mean set, a target heart rate mean is calculated based on the analyzed heart rate mean set, and a target speed mean and a target cadence mean are obtained based on the analyzed speed mean set and the analyzed cadence mean set; Associating the target heart rate average, the target speed average, the speed ratio and the target cadence average to obtain an analysis association node; The analysis-related nodes are aggregated to obtain an analysis-related node set, and a speed change strategy group set is obtained based on the analysis-related node set.

[0009] Optionally, the calculating the target heart rate mean based on the analyzed heart rate mean set includes: Calculate the mean of the analyzed heart rate means in the analyzed heart rate mean set to obtain the analyzed heart rate mean, and perform the following operations on each analyzed heart rate mean in the analyzed heart rate mean set: Calculate the absolute difference between the analytical heart rate mean and the analytical heart rate mean to obtain the offset heart rate, summarize the offset heart rates to obtain an offset heart rate set, calculate the mean of the offset heart rates in the offset heart rate set to obtain the offset heart rate mean, and calculate the offset evaluation range based on the offset heart rate mean, wherein the offset evaluation range is as follows: in, Indicates the offset evaluation range, are all preset coefficients. Indicates the deviation from the mean heart rate; Using the offset evaluation range, a target offset heart rate set is identified in the offset heart rate set, wherein the target offset heart rate set includes multiple target offset heart rates, and each of the multiple target offset heart rates satisfies the offset evaluation range; For each target offset heart rate in the target offset heart rate set, perform the following operations: The target offset heart rate and the analyzed heart rate mean corresponding to the target offset heart rate are associated to obtain an analytical heart rate node, the analytical heart rate nodes are summarized to obtain an analytical heart rate node set, and the target heart rate mean is calculated based on the analytical heart rate node set. The calculation formula is as follows: in, represents the target heart rate mean, Indicates that the heart rate analysis node has a total of Heart rate analysis nodes, Indicates the first node in the heart rate analysis The target offset heart rate corresponding to the analyzed heart rate node, Respectively represent the first The target offset heart rate and the average analyzed heart rate corresponding to each analyzed heart rate node.

[0010] Optionally, acquiring a speed change strategy group set based on the analysis of the associated node set includes: Obtaining a set of associated range nodes of different riding modes, wherein the associated range node set includes a plurality of associated range nodes, and the associated range nodes correspond to the riding modes one by one, and the associated range nodes include a target heart rate range, a target speed range, and a target cadence range; The following operations are performed on each associated scope node in the associated scope node set: Using the associated range node, searching in the analysis associated node set to obtain a target resolution node set, wherein the target resolution node set includes a plurality of target resolution nodes, and the target heart rate mean, target speed mean, and target cadence mean corresponding to the target resolution nodes are respectively within the target heart rate range, target speed range, and target cadence range corresponding to the associated range node; According to the associated range node, a normalization operation is performed on the target resolution node in the target resolution node set to obtain a normalized resolution node; Summarizing the normalized parsing nodes to obtain a normalized parsing node set, and clustering the normalized parsing node set using a pre-built clustering method to obtain one or more clustered parsing node sets; The following operations are performed on each of the one or more cluster resolution node sets: Using the pre-constructed speed ratio range set, the cluster resolution nodes in the cluster resolution node set are divided to obtain a plurality of target cluster resolution node sets, wherein the speed ratio range set includes three speed ratio ranges; The following operations are performed on each of the multiple target clustering resolution node sets: The speed change application name is obtained by using the speed change ratio range, and the target clustering parsing node set corresponding to the speed change ratio range is identified by using the speed change application name and the riding mode to obtain a speed change strategy group, wherein the speed change application name includes: uphill mode, flat road mode and downhill mode; The speed change strategy groups are summarized to obtain a speed change strategy group set.

[0011] Optionally, the using the driving characteristic sequence group and the user characteristic sequence group to retrieve a target speed change ratio from a target speed change strategy group includes: Based on the sliding window and the sliding step size, an initial slope sequence is sequentially extracted from the riding slope sequence corresponding to the driving feature sequence group, wherein the initial slope sequence includes a plurality of riding slopes; Using the initial slope sequence to identify a target speed change strategy node, wherein the target speed change strategy node is an uphill speed change strategy node, a downhill speed change strategy node or a flat road speed change strategy node, and using the target speed change strategy node to identify a first speed change strategy group in the target speed change strategy group, wherein the first speed change strategy group corresponds one-to-one to the speed change strategy group; The target speed ratio is retrieved from the first speed change strategy group by using the driving characteristic sequence group and the user characteristic sequence group.

[0012] Optionally, the step of using the initial slope sequence to determine the target speed change strategy node includes: Obtain a screening slope range, and use the screening slope range to screen out the classified slope in the initial slope sequence, wherein the classified slope is not within the screening slope range, and after confirming that the classified slope is greater than 0, the classified slope is identified as an uphill slope, and the number of uphill slopes in the initial slope sequence is counted to obtain the uphill number; The uphill number is compared with a preset slope threshold value. If the uphill number is greater than or equal to the slope threshold value, a target uphill slope is identified in the initial slope sequence. The target uphill slope is used to identify an interval uphill slope in the initial slope sequence. An uphill interval time is obtained based on the interval uphill slope and the target uphill slope. The uphill interval time is compared with a preset interval time threshold value. If the uphill interval time is greater than or equal to the interval time threshold value, the interval uphill slope is used as the target uphill slope. The target uphill slope is returned and the initial slope sequence is used. The step of identifying the interval uphill slope in the column, until it is confirmed that the uphill interval time is less than the interval time threshold, using the target uphill slope to identify the target uphill time in the initial slope sequence, and after confirming that the target uphill time is less than the preset uphill time threshold, returning to the step of extracting the initial slope sequence in sequence from the riding slope sequence corresponding to the driving feature sequence group based on the sliding window and the sliding step, until the target uphill time is greater than or equal to the preset uphill time threshold, and then taking the uphill speed change strategy node as the target speed change strategy node; Otherwise, confirming that the target speed change strategy node is a downhill speed change strategy node based on the screening slope range; Otherwise, it is confirmed that the target speed change strategy node is a flat road speed change strategy node.

[0013] Optionally, before retrieving the target speed ratio from the first speed change strategy group using the driving characteristic sequence group and the user characteristic sequence group, the method further includes: After confirming that the target speed change strategy node corresponding to the first speed change strategy group is an uphill speed change strategy node, using a preset evaluation acceleration value, confirming an analysis acceleration sequence in the riding acceleration sequence, wherein the analysis acceleration sequence includes a plurality of analysis accelerations; Extract analytical accelerations in sequence from the analytical acceleration sequence, and perform the following operations on the extracted analytical accelerations: Based on the analytical acceleration, the decomposed acceleration is identified in the analysis acceleration sequence, and the first decomposed acceleration is calculated based on the decomposed acceleration and the detection time interval. The calculation formula is as follows: in, represents the first decomposed acceleration, represents the decomposed acceleration, represents the analytical acceleration, represents the detection time interval; A first decomposed acceleration sequence is obtained based on the first decomposed acceleration, a decomposed acceleration mean is obtained by using the first decomposed acceleration sequence, the decomposed acceleration mean is compared with a preset decomposed acceleration threshold, and if the decomposed acceleration mean is greater than or equal to the decomposed acceleration threshold, a target speed ratio is retrieved from a first speed change strategy group by using a driving feature sequence group and a user feature sequence group.

[0014] Optionally, the using the driving characteristic sequence group and the user characteristic sequence group to retrieve the target speed ratio in the first speed change strategy group includes: The target user heart rate, the target user cadence and the target riding speed are respectively identified in the driving characteristic sequence group and the user characteristic sequence group; Calculate the target user's heart rate, target user's cadence, and target riding speed and the evaluation difference between the analysis-related nodes in the first speed change strategy group. The calculation formula is as follows: in, represents the evaluation difference, are all preset coefficients. Respectively represent the target user heart rate and the target heart rate mean, They represent the target riding speed and the target speed mean, respectively. They represent the target user cadence and the target cadence mean respectively; The evaluation differences are summarized to obtain an evaluation difference set, and a target speed ratio is determined based on the evaluation difference set, wherein the target speed ratio is the speed ratio corresponding to the smallest evaluation difference in the evaluation difference set.

[0015] To achieve the above object, the present invention further provides a bicycle intelligent speed change system based on sensor data, comprising: A speed change environment confirmation module is used to receive an intelligent speed change instruction and confirm an intelligent speed change environment based on the intelligent speed change instruction, wherein the intelligent speed change environment includes: an intelligent speed change system and an adjustment bicycle, and the intelligent speed change system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit and a speed change strategy construction unit; A speed change strategy building module, used to obtain an initial model set of bicycles, wherein the initial model set includes multiple initial models, and to obtain multiple speed change ratio sets based on the initial model set; Based on the multiple speed ratio sets and the speed strategy building unit, a speed strategy group set is obtained, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A riding feature acquisition module, used to respectively use the riding feature acquisition unit, the physiological feature acquisition unit and the preset detection time interval to acquire a riding feature sequence group and a user feature sequence group, wherein the riding feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The speed change strategy confirmation module is used to use the driving characteristic sequence group and the user characteristic sequence group to retrieve a target speed change ratio in the target speed change strategy group, and use the target speed change ratio to adjust the bicycle to achieve intelligent speed change of the bicycle.

[0016] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising: A memory storing at least one instruction; and a processor executing the instruction stored in the memory to implement the above-mentioned bicycle intelligent speed shifting method based on sensor data.

[0017] In order to solve the above problem, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned bicycle intelligent speed shifting method based on sensor data.

[0018] The present invention is to solve the problem described in the background technology. The present invention receives an intelligent speed shift instruction and confirms an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustable bicycle, and the intelligent speed shift system includes: a target model input unit, a driving feature collection unit, a physiological feature collection unit and a speed shift strategy construction unit. It can be seen that when confirming the intelligent speed shift environment, the present invention confirms the driving feature collection unit for collecting driving features and the physiological feature collection unit for collecting physiological features, thereby laying a foundation for the subsequent combination of physiological features and driving features to realize intelligent speed shifting of the bicycle. The combination of features improves the intelligence level of the present invention. The present invention obtains a speed strategy group set based on the multiple speed ratio sets and the speed strategy construction unit, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes. The speed strategy group set is sent to the initiator of the intelligent speed change instruction, and the target model input unit is used to receive the target model and target riding mode confirmed by the user according to the speed strategy group set. Based on the target model and the target riding mode, the target speed strategy group is confirmed in the speed strategy group set. It can be seen that the present invention constructs a speed strategy group suitable for different types of bicycles before confirming the target model and the target riding mode, and before constructing the speed strategy group, it also considers the integration of different riding modes, thereby improving the accuracy of the constructed speed strategy group, and confirms the riding mode required by the user through human-computer interaction, thereby improving the intelligence level of the present invention. The present invention uses a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval to obtain a driving feature sequence group and a user feature sequence group, respectively, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence. The driving feature sequence group and the user feature sequence group are used to retrieve the target speed ratio in the target speed change strategy group, and the target speed ratio is used to adjust the adjustment bicycle to achieve intelligent speed change of the bicycle. It can be seen that before performing the adjustment, the present invention also considers the physiological characteristics and riding characteristics of the user when riding, and can avoid over-adjustment, thereby improving the accuracy and intelligence of the speed change adjustment of the bicycle. Therefore, the present invention can improve the accuracy and intelligence of the intelligent speed change of the bicycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a flow chart of a bicycle intelligent speed change method based on sensor data provided by an embodiment of the present invention; Figure 2 A schematic diagram of a flow chart of a bicycle intelligent speed change method based on sensor data provided by an embodiment of the present invention; Figure 3 Another schematic diagram of a flow chart of a bicycle intelligent speed change method based on sensor data provided by an embodiment of the present invention; Figure 4 A functional module diagram of a bicycle intelligent speed change system based on sensor data provided by an embodiment of the present invention; Figure 5 A schematic diagram of the structure of an electronic device for implementing the bicycle intelligent speed shifting method based on sensor data provided by an embodiment of the present invention.

[0020] Description of reference numerals: 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0021] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0022] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0023] The embodiment of the present application provides a bicycle intelligent speed shifting method based on sensor data. The execution subject of the bicycle intelligent speed shifting method based on sensor data includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the bicycle intelligent speed shifting method based on sensor data can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0024] Reference Figure 1 FIG. 1 is a flow chart of a bicycle intelligent speed change method based on sensor data provided by an embodiment of the present invention. In this embodiment, the bicycle intelligent speed change method based on sensor data includes: S1. Receive an intelligent speed shift instruction, and confirm an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustable bicycle, and the intelligent speed shift system includes: a target model input unit, a driving feature collection unit, a physiological feature collection unit, and a speed shift strategy construction unit.

[0025] It should be explained that the intelligent speed change instruction is an instruction issued to realize the intelligent speed change of the adjustment bicycle, the intelligent speed change environment refers to the necessary environment for realizing the intelligent speed change of the adjustment bicycle, and the intelligent speed change environment includes the intelligent speed change system and the adjustment bicycle, wherein the adjustment bicycle refers to the bicycle to be intelligently shifted, the intelligent speed change system refers to the applet or APP used to realize the intelligent speed change of the adjustment bicycle, and the intelligent speed change system includes: a target model input unit, a driving feature collection unit, a physiological feature collection unit and a speed change strategy construction unit. For the specific application of the units, please refer to the subsequent embodiments. The main purpose of the present invention is to improve the user experience of the rider.

[0026] For example, in order to improve the riding experience, the rider of the adjustment bicycle connects to the intelligent speed change system through a mobile phone and selects the riding mode on the mobile phone before starting to ride. The adjustment bicycle can intelligently adjust the gear of the adjustment bicycle based on the rider's physiological characteristics and characteristics when riding, so as to improve the rider's experience.

[0027] S2. Acquire an initial model set of bicycles, wherein the initial model set includes a plurality of initial models, and acquire a plurality of speed ratio sets based on the initial model set.

[0028] It is understandable that the initial model refers to the model of the bicycle. In the embodiment of the present invention, the initial model obtained refers to the model of the bicycle that can use the intelligent speed change environment to realize intelligent speed change for the bicycle.

[0029] Further, the acquiring a plurality of speed ratio sets based on the initial model set includes: Extract initial models from the initial model set in sequence, and perform the following operations on the extracted initial models: Based on the initial model, a front disc tooth number set and a rear disc tooth number set are identified, wherein the front disc tooth number set includes a plurality of front disc tooth numbers, and the rear disc tooth number set includes a plurality of rear disc tooth numbers; The front disc tooth numbers are sequentially extracted from the front disc tooth number set, and the following operations are performed on the extracted front disc tooth numbers: In a combined form, a plurality of tooth number combination nodes are obtained using the extracted front disc tooth number and rear disc tooth number sets, wherein the tooth number combination node includes a front disc tooth number and a rear disc tooth number; For each of the multiple tooth number combination nodes, perform the following operations: Calculate the ratio of the number of teeth on the front disc to the number of teeth on the rear disc in the tooth number combination node to obtain a theoretical ratio, summarize the theoretical ratios to obtain a theoretical ratio set, and perform a normalization operation on the theoretical ratios in the theoretical ratio set to obtain a normalized ratio set, wherein the normalized ratio set includes multiple normalized ratios; Obtaining a screening ratio range based on the extracted number of front disc teeth, and using the screening ratio range to identify a screening ratio set in the normalized ratio set, wherein the screening ratio set includes a plurality of screening ratios, and all of the screening ratios are within the screening ratio range; The screening ratio sets are aggregated to obtain a speed ratio set, and the speed ratio sets are aggregated to obtain multiple speed ratio sets.

[0030] It should be explained that the number of teeth on the front disc refers to the number of teeth on the bicycle chainring, and the number of teeth on the rear disc refers to the number of teeth on the bicycle flywheel. Generally speaking, the gear ratio of the bicycle can be changed by adjusting the number of teeth on the front disc and the number of teeth on the rear disc, thereby adjusting the torque that the bicycle can output.

[0031] It is understandable that not all theoretical ratios in the theoretical ratio set have corresponding effects. Therefore, in the embodiment of the present invention, the screening ratio range is first obtained according to the number of teeth on the front disc, and then the screening ratio range is used to confirm the form of the screening ratio set in the normalized ratio set to improve the accuracy of the obtained screening ratio. Generally speaking, when riding a bicycle, it is necessary to avoid riding in the form of matching a larger number of teeth on the front disc with a larger number of teeth on the rear disc, that is, avoid matching a larger number of teeth on a toothed disc with a larger number of teeth on a flywheel. Similarly, it is also necessary to avoid riding in the form of matching a smaller number of teeth on the front disc with a smaller number of teeth on the rear disc, so as to improve riding efficiency and reduce mechanical wear. Optionally, different combinations of tooth number combination nodes are evaluated by the hierarchical analysis method and the pre-constructed detection index set to screen out different tooth number combinations in the tooth number combination node, thereby improving the accuracy of obtaining the screening ratio range, wherein the detection index set can be set by experience, and other methods can achieve the same effect, which will not be repeated here.

[0032] It should be explained that the normalization operation refers to an operation of mapping a numerical value between 0 and 1. Optionally, minimum-maximum normalization is used as the normalization operation. Other technologies can achieve the same effect, which will not be repeated here.

[0033] S3. Obtain a speed strategy group set based on the multiple speed ratio sets and the speed strategy construction unit, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes.

[0034] It should be explained that see Figure 2 As shown, the step of acquiring the speed change strategy group set based on the multiple speed change ratio sets and the speed change strategy construction unit includes: S31, confirming receipt of a speed change strategy instruction from a speed change strategy building unit, parsing the speed change strategy instruction, and obtaining a plurality of initial cadence ranges; S32, obtaining a plurality of test nodes by using a plurality of initial cadence ranges and a plurality of speed ratio sets in a combined form, wherein each test node includes an initial cadence range and a speed ratio; S33, performing the following operations on each of the multiple test nodes: Acquire a test node timing set based on the test node, a preset test interval time and a preset test period, wherein the test node timing set includes a plurality of test node timings, and the test node timings include: a test heart rate timing, a test speed timing and a test cadence timing; S34, performing the following operations on each test node timing in the test node timing set: Based on the pre-built sliding window and sliding step, the analysis heart rate time series is extracted in sequence from the test heart rate time series corresponding to the test node, and the following operations are performed on the extracted analysis heart rate time series: Acquire an analyzed heart rate variance based on the analyzed heart rate time series, compare the analyzed heart rate variance with a preset heart rate variance threshold, and after confirming that the analyzed heart rate variance is less than or equal to the heart rate variance threshold, obtain an analyzed heart rate mean using the analyzed heart rate time series, and based on the analyzed heart rate time series, respectively confirm an analyzed speed mean in a test speed time series and confirm an analyzed cadence mean in a test cadence time series; S35, respectively summarizing the analyzed heart rate mean, analyzed speed mean, and analyzed cadence mean to obtain an analyzed heart rate mean set, an analyzed speed mean set, and an analyzed cadence mean set, calculating a target heart rate mean based on the analyzed heart rate mean set, and obtaining a target speed mean and a target cadence mean based on the analyzed speed mean set and the analyzed cadence mean set; S36, associating the target heart rate average, the target speed average, the speed ratio and the target cadence average to obtain an analysis association node; The analysis-related nodes are aggregated to obtain an analysis-related node set, and a speed change strategy group set is obtained based on the analysis-related node set.

[0035] It is understood that the initial cadence range refers to a pre-set cadence range, and optionally, the initial cadence range is 80 to 100 times / minute. Generally, different initial cadence ranges can be suitable for different needs. For example, for the purpose of physical exercise, the initial cadence range should be 80 to 100 times / minute, while for the purpose of leisure sightseeing, the initial cadence range can be 60 to 70 times / minute. Optionally, the initial cadence range is set in combination with experience.

[0036] Further, the test heart rate sequence refers to a sequence obtained by sorting the obtained heart rates in a time-to-time order after performing a heart rate test at every test interval within the test period. The method for obtaining the test speed sequence and the method for obtaining the test cadence sequence are the same as the method for obtaining the test heart rate sequence, and will not be repeated here. For example, a large number of volunteers are recruited, and the test is performed while keeping the cadence within the initial cadence range to obtain a test node sequence set. The test period is 5 minutes, and the test time interval is 5 seconds. Then, in the test period, the heart rate, speed and cadence are measured once every 5 seconds, and the heart rate, speed and cadence are sorted in a time-to-time order corresponding to the heart rate, speed and cadence, respectively, to obtain the test heart rate sequence, the test speed sequence and the test cadence sequence, wherein each volunteer corresponds to a test node sequence set. Optionally, the cadence is measured by a cadence sensor, the speed is measured by a speed sensor, and the heart rate is measured by a sports watch. Obviously, when conducting tests, it is necessary to consider the environments that different gears are adapted to. For example, when testing with a gear that has a smaller theoretical ratio for climbing, the test should be conducted on a road with a certain slope.

[0037] It is understandable that the sliding window refers to a window that can extract a fixed amount of data in the time series. Optionally, a fixed-size window is used as the sliding window, and the sliding step size refers to the step size of each sliding window movement. For example, the test heart rate time series includes 10 test heart rates, and the 10 test heart rates are: 80bpm, 83bpm, 86bpm, 90bpm, 93bpm, 95bpm, 99bpm, 103bpm, 106bpm and 110bpm, the size of the sliding window used is 3, and the sliding step size is 1. Then, using the sliding window and the sliding step size, multiple analysis heart rate time series can be sequentially extracted from the test heart rate time series, wherein the multiple analysis heart rate time series are: (80bpm, 83bpm, 86bpm), (83bpm, 86bpm, 90bpm), (86bpm, 90bpm, 93bpm) and so on. Generally speaking, in the early stage of riding, the rider's heart rate may continue to rise due to the warm-up stage. After the rider warms up, under the conditions of the initial cadence range and the test period, the rider's heart rate should be in a relatively stable state, which means that the analyzed heart rate variance is less than or equal to the heart rate variance threshold. The analyzed heart rate variance refers to the variance of multiple test heart rates in the analyzed heart rate time series. The analyzed heart rate mean refers to the mean of multiple test heart rates in the analyzed heart rate time series.

[0038] It should be explained that in the embodiment of the present invention, the time period corresponding to the analysis heart rate sequence is the same as the time period corresponding to the analysis speed mean and the time period corresponding to the analysis cadence mean. Therefore, the analysis speed sequence and the analysis cadence sequence can be respectively confirmed in the test speed sequence and the test cadence sequence by analyzing the heart rate sequence, and the mean of multiple speeds in the analysis speed sequence is respectively calculated to obtain the analysis speed mean, and the mean of multiple cadences in the analysis cadence sequence is calculated to obtain the analysis cadence mean. In the embodiment of the present invention, the purpose of obtaining the target heart rate mean, the target speed mean and the target cadence mean is to obtain the heart rate, speed and cadence suitable for the rider under the actual test, and then improve the accuracy of the subsequent speed adjustment of the bicycle in the actual riding environment. The method of obtaining the target speed mean and the method of obtaining the target cadence mean are the same as the method of obtaining the target heart rate mean, which will not be repeated here.

[0039] It can be understood that the calculation of the target heart rate mean based on the analyzed heart rate mean set includes: Calculate the mean of the analyzed heart rate means in the analyzed heart rate mean set to obtain the analyzed heart rate mean, and perform the following operations on each analyzed heart rate mean in the analyzed heart rate mean set: Calculate the absolute difference between the analytical heart rate mean and the analytical heart rate mean to obtain the offset heart rate, summarize the offset heart rates to obtain an offset heart rate set, calculate the mean of the offset heart rates in the offset heart rate set to obtain the offset heart rate mean, and calculate the offset evaluation range based on the offset heart rate mean, wherein the offset evaluation range is as follows: in, Indicates the offset evaluation range, are all preset coefficients. Indicates the deviation from the mean heart rate; Using the offset evaluation range, a target offset heart rate set is identified in the offset heart rate set, wherein the target offset heart rate set includes multiple target offset heart rates, and each of the multiple target offset heart rates satisfies the offset evaluation range; For each target offset heart rate in the target offset heart rate set, perform the following operations: The target offset heart rate and the analyzed heart rate mean corresponding to the target offset heart rate are associated to obtain an analytical heart rate node, the analytical heart rate nodes are summarized to obtain an analytical heart rate node set, and the target heart rate mean is calculated based on the analytical heart rate node set. The calculation formula is as follows: in, represents the target heart rate mean, Indicates that the heart rate analysis node has a total of Heart rate analysis nodes, Indicates the first node in the heart rate analysis The target offset heart rate corresponding to the analyzed heart rate node, Respectively represent the first The target offset heart rate and the average analyzed heart rate corresponding to each analyzed heart rate node.

[0040] It should be explained that the average analyzed heart rates obtained by cyclists with different exercise habits and different physical conditions are different. Therefore, in the embodiment of the present invention, an offset evaluation range is formulated by the offset heart rate, and a target offset heart rate set is obtained through the offset evaluation range. This can improve the universality of the obtained target offset heart rate set, that is, the target offset heart rate in the target offset heart rate set can represent the heart rate set of most cyclists in specific riding situations.

[0041] It should be understood that in the embodiment of the present invention, the weight is constructed based on the target offset heart rate in the analytical heart rate node, so that the smaller the target offset heart rate, the larger the analytical heart rate mean corresponding to the target offset heart rate, thereby improving the universality of the obtained target heart rate mean.

[0042] Further, acquiring a speed change strategy group set based on the analysis of the associated node set includes: Obtaining a set of associated range nodes of different riding modes, wherein the associated range node set includes a plurality of associated range nodes, and the associated range nodes correspond to the riding modes one by one, and the associated range nodes include a target heart rate range, a target speed range, and a target cadence range; The following operations are performed for each associated scope node in the associated scope node set: Using the associated range node, searching in the analysis associated node set to obtain a target resolution node set, wherein the target resolution node set includes a plurality of target resolution nodes, and the target heart rate mean, target speed mean, and target cadence mean corresponding to the target resolution nodes are respectively within the target heart rate range, target speed range, and target cadence range corresponding to the associated range node; According to the associated range node, a normalization operation is performed on the target resolution node in the target resolution node set to obtain a normalized resolution node; Summarizing the normalized parsing nodes to obtain a normalized parsing node set, and clustering the normalized parsing node set using a pre-built clustering method to obtain one or more clustered parsing node sets; The following operations are performed on each of the one or more cluster resolution node sets: Using the pre-constructed speed ratio range set, the cluster resolution nodes in the cluster resolution node set are divided to obtain a plurality of target cluster resolution node sets, wherein the speed ratio range set includes three speed ratio ranges; The following operations are performed on each of the multiple target clustering resolution node sets: The speed change application name is obtained by using the speed change ratio range, and the target clustering parsing node set corresponding to the speed change ratio range is identified by using the speed change application name and the riding mode to obtain a speed change strategy group, wherein the speed change application name includes: uphill mode, flat road mode and downhill mode; The speed change strategy groups are summarized to obtain a speed change strategy group set.

[0043] It should be explained that the riding mode refers to the mode that the rider can select before riding. The riding mode can be obtained by artificial setting. Obviously, different riding modes can achieve different effects. Therefore, different associated range nodes can be obtained through different riding modes. The target heart rate range, target speed range and target cadence range in the associated range node can all be set in advance. For ease of understanding, only the target heart rate range is taken as an example. For example, when it is set to the fat burning stage, the heart rate should be maintained in the range of 110bpm to 140bpm. Therefore, the proposed riding mode is the fat burning mode corresponding to the fat burning stage, and the target heart rate range corresponding to the riding mode is set to 110bpm to 140bpm.

[0044] It is understandable that the analysis association node set includes analysis association nodes corresponding to different test nodes, so the target analysis association node set that meets the conditions can be retrieved in the analysis association node set using the association range node. According to the association range node, the target analysis node in the target analysis node set is normalized by normalizing the target heart rate mean corresponding to the target analysis node using the target heart rate range, normalizing the target speed mean corresponding to the target analysis node using the target speed range, and normalizing the target cadence mean corresponding to the target analysis node using the target cadence range, and then obtaining the target analysis node. According to the association range node, the method of normalizing the target analysis node in the target analysis node set is the same as the method of normalizing the theoretical ratio in the theoretical ratio set to obtain the normalized ratio set, and the difference is that before the target analysis node is normalized, the maximum value and the minimum value of the corresponding range need to be extracted in the association range node, and the normalization operation is performed using the maximum value and the minimum value.

[0045] It should be explained that the data in the normalized parsing nodes are all between 0 and 1, and the purpose of normalizing the target parsing nodes is to improve the accuracy of clustering the target parsing nodes, that is, to eliminate the numerical influence of different data, so as to improve the accuracy of the constructed speed change strategy group set. Optionally, the k-means clustering algorithm is used as the clustering method, and other technologies can achieve the same effect, which will not be repeated here. For example, there are 200 normalized parsing nodes in the normalized parsing node set. The k-means clustering algorithm can be used to cluster the normalized parsing nodes in the normalized parsing node set into 10 clusters, and the normalized parsing nodes contained in each cluster constitute a clustered parsing node set.

[0046] It should be understood that the speed ratio range refers to a range of theoretical ratios set for different purposes based on theoretical ratios. For example, when going uphill, because a theoretical ratio of a larger torque is adopted, the range formed by the theoretical ratio of a larger torque is the speed ratio range. The speed application name is the name corresponding to the speed ratio range, and both the speed ratio range and the speed application name can be set manually. For example, when a theoretical ratio of a larger torque is adopted, the theoretical ratio corresponding to this situation is defined as: climbing gear, and here, climbing gear is the speed application name.

[0047] Furthermore, through clustering, the target clustering parsing nodes corresponding to different speed change application names in different riding modes can be obtained. For example, if the riding mode is the fat burning mode, then through clustering, the target clustering parsing nodes corresponding to the fat burning mode, which are applicable to: climbing, downhill, and flat road riding, can be obtained. The purpose of using the speed change application name and the riding mode to identify the target clustering parsing node set is to distinguish the road conditions applicable to different riding modes and different theoretical proportions in different riding modes, and then improve the accuracy of intelligent speed change adjustment of the bicycle. For example: there are three target clustering parsing node sets, and the riding mode corresponding to the three target clustering parsing node sets is the fat burning mode, and the speed change application names are: climbing mode, flat road mode and downhill mode, then using the speed change application name and the riding mode to identify the target clustering parsing node sets respectively can identify the three target clustering parsing node sets as: fat burning mode-climbing mode-target clustering parsing node set, fat burning mode-flat road mode-target clustering parsing node set, fat burning mode-downhill mode-target clustering parsing node set.

[0048] S4. Send the speed shift strategy group set to the initiator of the intelligent speed shift instruction, use the target model input unit to receive the target model and target riding mode confirmed by the user according to the speed shift strategy group set, and based on the target model and target riding mode, confirm the target speed shift strategy group in the speed shift strategy group set.

[0049] It should be explained that the target model refers to the model of the bicycle selected by the user in the intelligent speed-changing system, and the target riding mode refers to the riding mode selected by the user according to the speed-changing strategy group set. According to the target model and the target riding mode, the speed-changing strategy group that is the same as the target model and the target riding mode can be identified in the speed-changing strategy group set. Here, the speed-changing strategy group is the target speed-changing strategy group. For example: if the riding mode selected by the rider is the fat burning mode, then in the speed-changing strategy group set, it can be identified that the corresponding speed ratio set of the fat burning mode-uphill mode, the speed ratio set of the fat burning mode-downhill mode, and the speed ratio set of the fat burning mode-downhill mode correspond to the specific model of bicycle in the fat burning mode.

[0050] S5. Use the driving characteristic acquisition unit, the physiological characteristic acquisition unit and the preset detection time interval to obtain a driving characteristic sequence group and a user characteristic sequence group, wherein the driving characteristic sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user characteristic sequence group includes: a user heart rate sequence and a user cadence sequence.

[0051] It is understandable that the riding speed sequence refers to a sequence composed of riding speeds, and riding speed refers to the speed of a user when riding and adjusting a bicycle. The riding acceleration sequence refers to a sequence composed of riding accelerations, and riding acceleration refers to the acceleration of a user when riding and adjusting a bicycle. The riding slope sequence refers to a sequence composed of riding slopes, and riding slope refers to the slope of a user when riding and adjusting a bicycle. The user heart rate sequence refers to a sequence composed of user heart rates, and user heart rate refers to the heart rate of the user detected when the user is riding and adjusting a bicycle. The user cadence sequence refers to a sequence composed of user cadences, and user cadence refers to the cadence of the user detected when the user is riding and adjusting a bicycle.

[0052] S6. Retrieve a target speed ratio from a target speed change strategy group using the driving characteristic sequence group and the user characteristic sequence group, and adjust the bicycle using the target speed ratio to achieve intelligent speed change of the bicycle.

[0053] It should be explained that the use of the driving characteristic sequence group and the user characteristic sequence group to retrieve the target speed ratio in the target speed change strategy group includes: Based on the sliding window and the sliding step size, an initial slope sequence is sequentially extracted from the riding slope sequence corresponding to the driving feature sequence group, wherein the initial slope sequence includes a plurality of riding slopes; Using the initial slope sequence to identify a target speed change strategy node, wherein the target speed change strategy node is an uphill speed change strategy node, a downhill speed change strategy node or a flat road speed change strategy node, and using the target speed change strategy node to identify a first speed change strategy group in the target speed change strategy group, wherein the first speed change strategy group corresponds one-to-one to the speed change strategy group; The target speed ratio is retrieved from the first speed change strategy group by using the driving characteristic sequence group and the user characteristic sequence group.

[0054] It is understandable that the acquisition method of the initial slope sequence is the same as the acquisition method of analyzing the heart rate time series, and can achieve the same effect, which will not be repeated here. Here, the purpose of setting the uphill speed change strategy node, the downhill speed change strategy node and the flat road speed change strategy node is to select different first speed change strategy groups in different theoretical proportions, so as to combine the driving characteristic sequence group and the user characteristic sequence group to achieve intelligent speed change for adjusting the bicycle.

[0055] It should be understood that the first speed shift strategy group and the speed shift strategy group have a one-to-one correspondence, that is, when the target speed shift strategy node is an uphill speed shift strategy node, the first speed shift strategy group is the speed shift strategy group corresponding to the uphill mode, when the target speed shift strategy node is a downhill speed shift strategy node, the first speed shift strategy group is the speed shift strategy group corresponding to the downhill mode, and when the target speed shift strategy node is a flat road speed shift strategy node, the first speed shift strategy group is the speed shift strategy group corresponding to the flat road mode.

[0056] Understandably, see Figure 3 As shown, the method of using the initial slope sequence to determine the target speed change strategy node includes: S61, obtaining a screening slope range, and using the screening slope range to screen out a classified slope in the initial slope sequence, wherein the classified slope is not within the screening slope range, and after confirming that the classified slope is greater than 0, the classified slope is identified as an uphill slope, and the number of uphill slopes in the initial slope sequence is counted to obtain the uphill number; S62, comparing the number of uphill climbs with a preset slope threshold; if the number of uphill climbs is greater than or equal to the slope threshold, identifying a target uphill slope in the initial slope sequence, using the target uphill slope, identifying an interval uphill slope in the initial slope sequence, obtaining an uphill interval time based on the interval uphill slope and the target uphill slope, comparing the uphill interval time with a preset interval time threshold; if the uphill interval time is greater than or equal to the interval time threshold, taking the interval uphill slope as the target uphill slope, returning to the target uphill slope, and obtaining the interval uphill slope in the initial slope sequence; The step of identifying the interval uphill slope in the riding slope sequence until it is confirmed that the uphill interval time is less than the interval time threshold, using the target uphill slope to identify the target uphill time in the initial slope sequence, and after confirming that the target uphill time is less than the preset uphill time threshold, returning to the step of extracting the initial slope sequence in sequence from the riding slope sequence corresponding to the driving feature sequence group based on the sliding window and the sliding step, until the target uphill time is greater than or equal to the preset uphill time threshold, and then taking the uphill speed change strategy node as the target speed change strategy node; S63: otherwise, confirming that the target speed change strategy node is a downhill speed change strategy node based on the screened slope range; S64: Otherwise, confirm that the target speed change strategy node is a flat road speed change strategy node.

[0057] It should be explained that the screening slope range refers to the range used to determine whether the bicycle is located on the slope when the user is riding the bicycle. Optionally, the screening slope range is -5 degrees to 5 degrees, and here, the positive and negative signs are only used to confirm uphill or downhill. When the slope of the bicycle is greater than 0 degrees when it is traveling, it is determined that the bicycle is on an uphill slope, otherwise, it is determined that the bicycle is on a downhill slope. When the number of uphill slopes is greater than or equal to the slope threshold, it is determined that the user is riding the bicycle and the bicycle is roughly in an uphill stage when riding. Here, the uphill stage may be composed of multiple bumpy sections. Therefore, after confirming that the number of uphill slopes is greater than or equal to the slope threshold, it is also necessary to determine whether the section corresponding to the number of uphill slopes is an uphill section. Obviously, if the road section is not refined and the speed adjustment of the adjustment bicycle is performed, it may lead to excessive adjustment of the adjustment bicycle, thereby reducing the user's experience.

[0058] It is understandable that the definition of the interval uphill slope is the same as the definition of the target uphill slope, and the interval uphill slope is adjacent to the target uphill slope and lags behind the target uphill slope. Obviously, the present invention sets a detection time interval, so the time interval between the interval uphill slope and the target uphill slope can be obtained. When the uphill interval time is greater than or equal to the interval time threshold, it is determined that the section of the road on which the bicycle is traveling is a bumpy section. Therefore, it is necessary to return to the step of determining whether the section is an uphill section, which is: taking the interval uphill slope as the target uphill slope, return to the step of using the target uphill slope to identify the interval uphill slope in the initial slope sequence.

[0059] Furthermore, the target uphill time is the absolute difference between the time corresponding to the first target uphill slope and the time corresponding to the last target uphill slope among the multiple target uphill slopes, and the uphill interval time corresponding to two adjacent target uphill slopes among the multiple target uphill slopes is less than the uphill time threshold. When the target uphill time is greater than or equal to the uphill time threshold, it is determined that the road section traveled by the adjustment bicycle is still an uphill section, so the adjustment bicycle can be adjusted to improve the user experience.

[0060] It should be explained that the confirmation method of the downhill speed change strategy node is the same as the confirmation method of the uphill speed change strategy node, and the difference is that the downhill speed change strategy node refers to confirming that the section of the road on which the bicycle is traveling is a downhill section. The flat road speed change strategy node refers to the complement of the uphill speed change strategy node and the downhill speed change strategy node. It is not difficult to understand that in the embodiment of the present invention, the detection of the user is realized at the detection time interval, so the obtained driving feature sequence group and user feature sequence group will be updated with the test data.

[0061] Furthermore, before retrieving the target speed ratio from the first speed change strategy group using the driving characteristic sequence group and the user characteristic sequence group, the method further includes: After confirming that the target speed change strategy node corresponding to the first speed change strategy group is an uphill speed change strategy node, using a preset evaluation acceleration value, confirming an analysis acceleration sequence in the riding acceleration sequence, wherein the analysis acceleration sequence includes a plurality of analysis accelerations; Extract analytical accelerations in sequence from the analytical acceleration sequence, and perform the following operations on the extracted analytical accelerations: Based on the analytical acceleration, the decomposed acceleration is identified in the analysis acceleration sequence, and the first decomposed acceleration is calculated based on the decomposed acceleration and the detection time interval. The calculation formula is as follows: in, represents the first decomposed acceleration, represents the decomposed acceleration, represents the analytical acceleration, represents the detection time interval; A first decomposed acceleration sequence is obtained based on the first decomposed acceleration, a decomposed acceleration mean is obtained by using the first decomposed acceleration sequence, the decomposed acceleration mean is compared with a preset decomposed acceleration threshold, and if the decomposed acceleration mean is greater than or equal to the decomposed acceleration threshold, a target speed ratio is retrieved from a first speed change strategy group by using a driving feature sequence group and a user feature sequence group.

[0062] It is understandable that the purpose of setting the evaluation acceleration value is to identify whether the user has the intention to accelerate in the current situation. The decomposed acceleration is adjacent to the analytical acceleration and lags behind the analytical acceleration. Generally speaking, the time corresponding to the analytical acceleration in the confirmed analytical acceleration sequence is closest to the current time, so as to characterize the current intention of the rider. The number of the multiple analytical accelerations is the evaluation acceleration value.

[0063] Further, the use of the driving characteristic sequence group and the user characteristic sequence group to retrieve the target speed ratio in the first speed change strategy group includes: The target user heart rate, the target user cadence and the target riding speed are respectively identified in the driving characteristic sequence group and the user characteristic sequence group; Calculate the target user's heart rate, target user's cadence, and target riding speed and the evaluation difference between the analysis-related nodes in the first speed change strategy group. The calculation formula is as follows: in, represents the evaluation difference, are all preset coefficients. Respectively represent the target user heart rate and the target heart rate mean, They represent the target riding speed and the target speed mean, respectively. They represent the target user cadence and the target cadence mean respectively; The evaluation differences are summarized to obtain an evaluation difference set, and a target speed ratio is determined based on the evaluation difference set, wherein the target speed ratio is the speed ratio corresponding to the smallest evaluation difference in the evaluation difference set.

[0064] It is understandable that the target user heart rate is obtained by using the sliding window to obtain the latest user heart rate sequence in the user heart rate sequence, wherein the user heart rate sequence includes multiple user heart rates, and the average of the multiple user heart rates in the user heart rate sequence is calculated to obtain the target user heart rate. The target user cadence and target riding speed are obtained in the same way as the target user heart rate, which will not be described here. Generally speaking, the user's physical condition needs to be considered before adjusting the gear of the bicycle, so as to provide the user with a gear that is more in line with the user's wishes and the user's physical condition, thereby improving the intelligence level of the embodiment of the present invention.

[0065] Further, the adjusting the bicycle by using the target speed ratio includes: The target speed ratio is sent to the initiator of the intelligent speed change instruction, and after confirming the receipt of the confirmation instruction issued by the user according to the target speed ratio, the bicycle is adjusted using the target speed ratio.

[0066] It is understandable that when realizing intelligent speed shifting of the adjustable bicycle, factors such as the physical condition of the rider or user during actual riding and road conditions must also be considered. Therefore, in the embodiment of the present invention, the confirmed target speed ratio needs to be sent to the user. When the user confirms the use of the target speed ratio, the gear used by the adjustable bicycle can be adjusted to the target speed ratio.

[0067] The present invention is to solve the problem described in the background technology. The present invention receives an intelligent speed shift instruction and confirms an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustable bicycle, and the intelligent speed shift system includes: a target model input unit, a driving feature collection unit, a physiological feature collection unit and a speed shift strategy construction unit. It can be seen that when confirming the intelligent speed shift environment, the present invention confirms the driving feature collection unit for collecting driving features and the physiological feature collection unit for collecting physiological features, thereby laying a foundation for the subsequent combination of physiological features and driving features to realize intelligent speed shifting of the bicycle. The combination of features improves the intelligence level of the present invention. The present invention obtains a speed strategy group set based on the multiple speed ratio sets and the speed strategy construction unit, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes. The speed strategy group set is sent to the initiator of the intelligent speed change instruction, and the target model input unit is used to receive the target model and target riding mode confirmed by the user according to the speed strategy group set. Based on the target model and the target riding mode, the target speed strategy group is confirmed in the speed strategy group set. It can be seen that the present invention constructs a speed strategy group suitable for different types of bicycles before confirming the target model and the target riding mode, and before constructing the speed strategy group, it also considers the integration of different riding modes, thereby improving the accuracy of the constructed speed strategy group, and confirms the riding mode required by the user through human-computer interaction, thereby improving the intelligence level of the present invention. The present invention uses a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval to obtain a driving feature sequence group and a user feature sequence group, respectively, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence. The driving feature sequence group and the user feature sequence group are used to retrieve the target speed ratio in the target speed change strategy group, and the target speed ratio is used to adjust the adjustment bicycle to achieve intelligent speed change of the bicycle. It can be seen that before performing the adjustment, the present invention also considers the physiological characteristics and riding characteristics of the user when riding, and can avoid over-adjustment, thereby improving the accuracy and intelligence of the speed change adjustment of the bicycle. Therefore, the present invention can improve the accuracy and intelligence of the intelligent speed change of the bicycle.

[0068] like Figure 4 , which is a functional module diagram of a bicycle intelligent speed change system based on sensor data provided by an embodiment of the present invention.

[0069] The bicycle intelligent speed change system 100 based on sensor data of the present invention can be installed in an electronic device. According to the functions to be implemented, the bicycle intelligent speed change system 100 based on sensor data can include a speed change environment confirmation module 101, a speed change strategy construction module 102, a riding feature acquisition module 103 and a speed change strategy confirmation module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, which are stored in the memory of the electronic device.

[0070] The speed change environment confirmation module 101 is used to receive an intelligent speed change instruction and confirm an intelligent speed change environment based on the intelligent speed change instruction, wherein the intelligent speed change environment includes: an intelligent speed change system and an adjustment bicycle, and the intelligent speed change system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit and a speed change strategy construction unit; The speed change strategy building module 102 is used to obtain an initial model set of bicycles, wherein the initial model set includes multiple initial models, and obtain multiple speed change ratio sets based on the initial model set; Based on the multiple speed ratio sets and the speed strategy building unit, a speed strategy group set is obtained, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; The riding feature acquisition module 103 is used to respectively use the riding feature acquisition unit, the physiological feature acquisition unit and the preset detection time interval to acquire a riding feature sequence group and a user feature sequence group, wherein the riding feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The speed change strategy confirmation module 104 is used to use the driving characteristic sequence group and the user characteristic sequence group to retrieve a target speed change ratio in the target speed change strategy group, and use the target speed change ratio to adjust the bicycle to achieve intelligent speed change of the bicycle.

[0071] In detail, the modules in the bicycle intelligent speed change system 100 based on sensor data in the embodiment of the present invention are used in the same manner as described above. Figure 1The technical means are the same as the bicycle intelligent speed shifting method based on sensor data described in, and can produce the same technical effects, so they will not be repeated here.

[0072] like Figure 5 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a bicycle intelligent speed change method based on sensor data provided by an embodiment of the present invention.

[0073] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a bicycle intelligent speed shifting method program based on sensor data.

[0074] The memory 11 includes at least one type of readable storage medium, including flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the bicycle intelligent speed change method program based on sensor data, but also can be used to temporarily store data that has been output or is to be output.

[0075] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as a bicycle intelligent speed change method program based on sensor data, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0076] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0077] Figure 5 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 5 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0078] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management system, so that the power management system can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0079] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0080] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0081] The bicycle intelligent speed change method program based on sensor data stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve: Receiving an intelligent speed shift instruction, and confirming an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustment bicycle, and the intelligent speed shift system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit, and a speed shift strategy construction unit; Acquire an initial model set of a bicycle, wherein the initial model set includes a plurality of initial models, and acquire a plurality of speed ratio sets based on the initial model set; Based on the multiple speed ratio sets and the speed strategy building unit, a speed strategy group set is obtained, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A driving feature sequence group and a user feature sequence group are acquired by using a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The driving characteristic sequence group and the user characteristic sequence group are used to retrieve a target speed ratio in a target speed change strategy group, and the bicycle is adjusted using the target speed ratio to achieve intelligent speed change of the bicycle.

[0082] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 5 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0083] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or system that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0084] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement: Receiving an intelligent speed shift instruction, and confirming an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustment bicycle, and the intelligent speed shift system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit, and a speed shift strategy construction unit; Acquire an initial model set of a bicycle, wherein the initial model set includes a plurality of initial models, and acquire a plurality of speed ratio sets based on the initial model set; Based on the multiple speed ratio sets and the speed strategy building unit, a speed strategy group set is obtained, wherein the speed strategy group set includes multiple speed strategy groups marked with riding modes, and each speed strategy group includes multiple speed ratios, and different speed strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A driving feature sequence group and a user feature sequence group are acquired by using a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The driving characteristic sequence group and the user characteristic sequence group are used to retrieve a target speed ratio in a target speed change strategy group, and the bicycle is adjusted using the target speed ratio to achieve intelligent speed change of the bicycle.

[0085] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0086] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0088] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A bicycle intelligent speed change method based on sensor data, characterized in that: The method comprises: Receiving an intelligent speed shift instruction, and confirming an intelligent speed shift environment based on the intelligent speed shift instruction, wherein the intelligent speed shift environment includes: an intelligent speed shift system and an adjustment bicycle, and the intelligent speed shift system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit, and a speed shift strategy construction unit; Acquire an initial model set of a bicycle, wherein the initial model set includes a plurality of initial models, and acquire a plurality of speed ratio sets based on the initial model set; Acquire a speed change strategy group set based on the multiple speed change ratio sets and the speed change strategy construction unit, wherein the speed change strategy group set includes multiple speed change strategy groups marked with riding modes, and each speed change strategy group includes multiple speed change ratios, and different speed change strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A driving feature sequence group and a user feature sequence group are acquired by using a driving feature acquisition unit, a physiological feature acquisition unit and a preset detection time interval, wherein the driving feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The driving characteristic sequence group and the user characteristic sequence group are used to retrieve a target speed ratio in a target speed change strategy group, and the bicycle is adjusted using the target speed ratio to achieve intelligent speed change of the bicycle.

2. The bicycle intelligent speed change method based on sensor data according to claim 1, characterized in that: The step of acquiring a plurality of speed ratio sets based on the initial model set comprises: Extract initial models from the initial model set in sequence, and perform the following operations on the extracted initial models: Based on the initial model, a front disc tooth number set and a rear disc tooth number set are identified, wherein the front disc tooth number set includes a plurality of front disc tooth numbers, and the rear disc tooth number set includes a plurality of rear disc tooth numbers; The front disc tooth numbers are sequentially extracted from the front disc tooth number set, and the following operations are performed on the extracted front disc tooth numbers: In a combined form, a plurality of tooth number combination nodes are obtained using the extracted front disc tooth number and rear disc tooth number sets, wherein the tooth number combination node includes a front disc tooth number and a rear disc tooth number; For each of the multiple tooth number combination nodes, perform the following operations: Calculate the ratio of the number of teeth on the front disc to the number of teeth on the rear disc in the tooth number combination node to obtain a theoretical ratio, summarize the theoretical ratios to obtain a theoretical ratio set, and perform a normalization operation on the theoretical ratios in the theoretical ratio set to obtain a normalized ratio set, wherein the normalized ratio set includes multiple normalized ratios; Obtaining a screening ratio range based on the extracted number of front disc teeth, and using the screening ratio range to identify a screening ratio set in the normalized ratio set, wherein the screening ratio set includes a plurality of screening ratios, and all of the screening ratios are within the screening ratio range; The screening ratio sets are aggregated to obtain a speed ratio set, and the speed ratio sets are aggregated to obtain multiple speed ratio sets.

3. The bicycle intelligent speed change method based on sensor data as claimed in claim 2, characterized in that: The step of acquiring a speed change strategy group set based on the plurality of speed change ratio sets and the speed change strategy construction unit comprises: confirming receipt of a speed change strategy instruction from a speed change strategy building unit, parsing the speed change strategy instruction, and obtaining a plurality of initial cadence ranges; In a combined form, a plurality of initial cadence ranges and a plurality of speed ratio sets are used to obtain a plurality of test nodes, wherein each test node includes an initial cadence range and a speed ratio; The following operations are performed on each of the multiple test nodes: Acquire a test node timing set based on the test node, a preset test interval time and a preset test period, wherein the test node timing set includes a plurality of test node timings, and the test node timings include: a test heart rate timing, a test speed timing and a test cadence timing; The following operations are performed for each test node timing in the test node timing set: Based on the pre-built sliding window and sliding step, the analysis heart rate time series is extracted in sequence from the test heart rate time series corresponding to the test node, and the following operations are performed on the extracted analysis heart rate time series: Acquire an analyzed heart rate variance based on the analyzed heart rate time series, compare the analyzed heart rate variance with a preset heart rate variance threshold, and after confirming that the analyzed heart rate variance is less than or equal to the heart rate variance threshold, obtain an analyzed heart rate mean using the analyzed heart rate time series, and based on the analyzed heart rate time series, respectively confirm an analyzed speed mean in a test speed time series and confirm an analyzed cadence mean in a test cadence time series; The analyzed heart rate mean, the analyzed speed mean and the analyzed cadence mean are respectively summarized to obtain an analyzed heart rate mean set, an analyzed speed mean set and an analyzed cadence mean set, a target heart rate mean is calculated based on the analyzed heart rate mean set, and a target speed mean and a target cadence mean are obtained based on the analyzed speed mean set and the analyzed cadence mean set; Associating the target heart rate average, the target speed average, the speed ratio and the target cadence average to obtain an analysis association node; The analysis-related nodes are aggregated to obtain an analysis-related node set, and a speed change strategy group set is obtained based on the analysis-related node set.

4. The bicycle intelligent speed change method based on sensor data as claimed in claim 3, characterized in that: The calculating the target heart rate mean based on the analyzed heart rate mean set includes: Calculate the mean of the analyzed heart rate means in the analyzed heart rate mean set to obtain the analyzed heart rate mean, and perform the following operations on each analyzed heart rate mean in the analyzed heart rate mean set: Calculate the absolute difference between the analytical heart rate mean and the analytical heart rate mean to obtain the offset heart rate, summarize the offset heart rates to obtain an offset heart rate set, calculate the mean of the offset heart rates in the offset heart rate set to obtain the offset heart rate mean, and calculate the offset evaluation range based on the offset heart rate mean, wherein the offset evaluation range is as follows: in, Indicates the offset evaluation range, are all preset coefficients. Indicates the deviation from the mean heart rate; Using the offset evaluation range, a target offset heart rate set is identified in the offset heart rate set, wherein the target offset heart rate set includes multiple target offset heart rates, and each of the multiple target offset heart rates satisfies the offset evaluation range; For each target offset heart rate in the target offset heart rate set, perform the following operations: The target offset heart rate and the analyzed heart rate mean corresponding to the target offset heart rate are associated to obtain an analytical heart rate node, the analytical heart rate nodes are summarized to obtain an analytical heart rate node set, and the target heart rate mean is calculated based on the analytical heart rate node set. The calculation formula is as follows: in, represents the target heart rate mean, Indicates that the heart rate analysis node has a total of Heart rate analysis nodes, Indicates the first node in the heart rate analysis The target offset heart rate corresponding to the analyzed heart rate node, Respectively represent the first The target offset heart rate and the average analyzed heart rate corresponding to each analyzed heart rate node.

5. The bicycle intelligent speed change method based on sensor data as claimed in claim 4, characterized in that: The obtaining of the speed change strategy group set based on the analysis of the associated node set includes: Obtaining a set of associated range nodes of different riding modes, wherein the associated range node set includes a plurality of associated range nodes, and the associated range nodes correspond to the riding modes one by one, and the associated range nodes include a target heart rate range, a target speed range, and a target cadence range; The following operations are performed for each associated scope node in the associated scope node set: Using the associated range node, searching in the analysis associated node set to obtain a target resolution node set, wherein the target resolution node set includes a plurality of target resolution nodes, and the target heart rate mean, target speed mean, and target cadence mean corresponding to the target resolution nodes are respectively within the target heart rate range, target speed range, and target cadence range corresponding to the associated range node; According to the associated range node, a normalization operation is performed on the target resolution node in the target resolution node set to obtain a normalized resolution node; Summarizing the normalized parsing nodes to obtain a normalized parsing node set, and clustering the normalized parsing node set using a pre-built clustering method to obtain one or more clustered parsing node sets; The following operations are performed on each of the one or more cluster resolution node sets: Using the pre-constructed speed ratio range set, the cluster resolution nodes in the cluster resolution node set are divided to obtain a plurality of target cluster resolution node sets, wherein the speed ratio range set includes three speed ratio ranges; The following operations are performed on each of the multiple target clustering resolution node sets: The speed change application name is obtained by using the speed change ratio range, and the target clustering parsing node set corresponding to the speed change ratio range is identified by using the speed change application name and the riding mode to obtain a speed change strategy group, wherein the speed change application name includes: uphill mode, flat road mode and downhill mode; The speed change strategy groups are summarized to obtain a speed change strategy group set.

6. The bicycle intelligent speed change method based on sensor data as claimed in claim 5, characterized in that: The method of using the driving characteristic sequence group and the user characteristic sequence group to retrieve a target speed change ratio from a target speed change strategy group includes: Based on the sliding window and the sliding step size, an initial slope sequence is sequentially extracted from the riding slope sequence corresponding to the driving feature sequence group, wherein the initial slope sequence includes a plurality of riding slopes; Using the initial slope sequence to identify a target speed change strategy node, wherein the target speed change strategy node is an uphill speed change strategy node, a downhill speed change strategy node or a flat road speed change strategy node, and using the target speed change strategy node to identify a first speed change strategy group in the target speed change strategy group, wherein the first speed change strategy group corresponds one-to-one to the speed change strategy group; The target speed ratio is retrieved from the first speed change strategy group by using the driving characteristic sequence group and the user characteristic sequence group.

7. The bicycle intelligent speed change method based on sensor data as claimed in claim 6, characterized in that: The method of using the initial slope sequence to determine the target speed change strategy node includes: Obtain a screening slope range, and use the screening slope range to screen out the classified slope in the initial slope sequence, wherein the classified slope is not within the screening slope range, and after confirming that the classified slope is greater than 0, the classified slope is identified as an uphill slope, and the number of uphill slopes in the initial slope sequence is counted to obtain the uphill number; The uphill number is compared with a preset slope threshold value. If the uphill number is greater than or equal to the slope threshold value, a target uphill slope is identified in the initial slope sequence. The target uphill slope is used to identify an interval uphill slope in the initial slope sequence. An uphill interval time is obtained based on the interval uphill slope and the target uphill slope. The uphill interval time is compared with a preset interval time threshold value. If the uphill interval time is greater than or equal to the interval time threshold value, the interval uphill slope is used as the target uphill slope. The target uphill slope is returned and the initial slope sequence is used. The step of identifying the interval uphill slope in the column, until it is confirmed that the uphill interval time is less than the interval time threshold, using the target uphill slope to identify the target uphill time in the initial slope sequence, and after confirming that the target uphill time is less than the preset uphill time threshold, returning to the step of extracting the initial slope sequence in sequence from the riding slope sequence corresponding to the driving feature sequence group based on the sliding window and the sliding step, until the target uphill time is greater than or equal to the preset uphill time threshold, and then taking the uphill speed change strategy node as the target speed change strategy node; Otherwise, confirming that the target speed change strategy node is a downhill speed change strategy node based on the screening slope range; Otherwise, it is confirmed that the target speed change strategy node is a flat road speed change strategy node.

8. The bicycle intelligent speed change method based on sensor data as claimed in claim 7, characterized in that: Before retrieving the target speed ratio from the first speed change strategy group using the driving characteristic sequence group and the user characteristic sequence group, the method further includes: After confirming that the target speed change strategy node corresponding to the first speed change strategy group is an uphill speed change strategy node, using a preset evaluation acceleration value, confirming an analysis acceleration sequence in the riding acceleration sequence, wherein the analysis acceleration sequence includes a plurality of analysis accelerations; Extract analytical accelerations in sequence from the analytical acceleration sequence, and perform the following operations on the extracted analytical accelerations: Based on the analytical acceleration, the decomposed acceleration is identified in the analysis acceleration sequence, and the first decomposed acceleration is calculated based on the decomposed acceleration and the detection time interval. The calculation formula is as follows: in, represents the first decomposed acceleration, represents the decomposed acceleration, represents the analytical acceleration, represents the detection time interval; A first decomposed acceleration sequence is obtained based on the first decomposed acceleration, a decomposed acceleration mean is obtained by using the first decomposed acceleration sequence, the decomposed acceleration mean is compared with a preset decomposed acceleration threshold, and if the decomposed acceleration mean is greater than or equal to the decomposed acceleration threshold, a target speed ratio is retrieved from a first speed change strategy group by using a driving feature sequence group and a user feature sequence group.

9. The bicycle intelligent speed change method based on sensor data as claimed in claim 8, characterized in that: The method of using the driving characteristic sequence group and the user characteristic sequence group to retrieve the target speed ratio in the first speed change strategy group includes: The target user heart rate, the target user cadence and the target riding speed are respectively identified in the driving characteristic sequence group and the user characteristic sequence group; Calculate the target user's heart rate, target user's cadence, and target riding speed and the evaluation difference between the analysis-related nodes in the first speed change strategy group. The calculation formula is as follows: in, represents the evaluation difference, are all preset coefficients. Respectively represent the target user heart rate and the target heart rate mean, They represent the target riding speed and the target speed mean, respectively. They represent the target user cadence and the target cadence mean respectively; The evaluation differences are summarized to obtain an evaluation difference set, and a target speed ratio is determined based on the evaluation difference set, wherein the target speed ratio is the speed ratio corresponding to the smallest evaluation difference in the evaluation difference set.

10. A bicycle intelligent speed change system based on sensor data, characterized in that: The system comprises: A speed change environment confirmation module is used to receive an intelligent speed change instruction and confirm an intelligent speed change environment based on the intelligent speed change instruction, wherein the intelligent speed change environment includes: an intelligent speed change system and an adjustment bicycle, and the intelligent speed change system includes: a target model input unit, a driving characteristic collection unit, a physiological characteristic collection unit and a speed change strategy construction unit; A speed change strategy building module, used to obtain an initial model set of bicycles, wherein the initial model set includes multiple initial models, and to obtain multiple speed change ratio sets based on the initial model set; Acquire a speed change strategy group set based on the multiple speed change ratio sets and the speed change strategy construction unit, wherein the speed change strategy group set includes multiple speed change strategy groups marked with riding modes, and each speed change strategy group includes multiple speed change ratios, and different speed change strategy groups correspond to different riding modes; The speed shift strategy group set is sent to the initiator of the intelligent speed shift instruction, a target model and a target riding mode confirmed by a user according to the speed shift strategy group set are received by a target model input unit, and a target speed shift strategy group is confirmed in the speed shift strategy group set based on the target model and the target riding mode; A riding feature acquisition module, used to respectively use the riding feature acquisition unit, the physiological feature acquisition unit and the preset detection time interval to acquire a riding feature sequence group and a user feature sequence group, wherein the riding feature sequence group includes: a riding speed sequence, a riding acceleration sequence and a riding slope sequence, and the user feature sequence group includes: a user heart rate sequence and a user cadence sequence; The speed change strategy confirmation module is used to use the driving characteristic sequence group and the user characteristic sequence group to retrieve a target speed change ratio in the target speed change strategy group, and use the target speed change ratio to adjust the bicycle to achieve intelligent speed change of the bicycle.

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