An intervention regulation method and system for electric scooters based on AI analysis of riding trajectories

Abstract

The present invention relates to the technical field of electric energy calculation, and an intervention control method and system for an electric scooter based on AI analysis of riding trajectories, including: receiving an intervention control instruction, starting an intervention control unit, detecting the current air pressure value, detecting the current temperature value, detecting the current humidity value, collecting scooter position data, calculating the transmission busyness degree. If the transmission busyness degree is greater than the busyness degree threshold, a processed data set is obtained through preprocessing, and the current height difference is calculated according to the processed temperature value and the processed air pressure value. If the transmission busyness degree is not greater than the busyness degree threshold, the processed temperature value, the processed humidity value, the processed air pressure value and the processed position data are obtained by using a data control unit, the current height difference is calculated, the current rotation degree is calculated, the adjusted electric energy output value is calculated, and the intervention control of the electric scooter is completed based on the adjusted electric energy output value. The present invention can improve the stability of the electric scooter during driving.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy calculation, and particularly relates to a method and system for intervening and regulating an electric scooter based on AI analysis of a riding trajectory. Background Art

[0002] With the rapid development of intelligent transportation tools, the electric scooter, as a convenient short-distance travel mode, has been widely used in urban commuting. The electric scooter can complete urban movement in a short time, greatly facilitating the daily life of urban residents. In order to improve the stability of the electric scooter during driving, regulating the electric energy output of the electric scooter has become an important research direction.

[0003] Most of the existing electric energy output regulations of electric scooters adopt simple battery power monitoring and power output limitation, and regulate the electric scooter based on preset fixed rules. However, during the actual driving process of the electric scooter, it is affected by the current temperature value, current humidity value, and current air pressure value. It is difficult to make the best adjustment to the electric scooter according to environmental changes only based on preset fixed rules. Therefore, how to improve the stability of the electric scooter during driving is an important problem that needs to be solved urgently at present. Summary of the Invention

[0004] The present invention provides a method and system for intervening and regulating an electric scooter based on AI analysis of a riding trajectory, and its main purpose is to improve the stability of the electric scooter during driving.

[0005] To achieve the above purpose, a method for intervening and regulating an electric scooter based on AI analysis of a riding trajectory provided by the present invention includes:

[0006] Receiving an intervention regulation instruction, and starting a pre-confirmed intervention regulation unit based on the intervention regulation instruction, where the intervention regulation unit includes: an air pressure detection unit, a temperature detection unit, a humidity detection unit, a position point acquisition unit, a data transmission unit, and a data regulation unit;

[0007] Using the air pressure detection unit to detect the air pressure to obtain the current air pressure value, using the temperature detection unit to detect the temperature to obtain the current temperature value, and based on the humidity detection unit to detect the humidity to obtain the current humidity value;

[0008] Using the position point acquisition unit to collect the electric scooter position point data and calculate the transmission busy degree of the data transmission unit;

[0009] Comparing the transmission busy degree with a preset busy degree threshold;

[0010] If the transmission busyness is greater than the busyness threshold, the current temperature value, the current humidity value, the current air pressure value, and the scooter position data are transmitted to a pre-constructed scooter processing terminal, and the scooter processing terminal performs data preprocessing operations on the current temperature value, the current humidity value, the current air pressure value, and the scooter position data to obtain a processed data set. Among them, the processed data set includes: a processed temperature value, a processed humidity value, a processed air pressure value, and processed position data. The processed temperature value, the processed humidity value, the processed air pressure value, and the processed position data are transmitted to the data regulation unit, and the current high-level difference is calculated according to the processed temperature value and the processed air pressure value;

[0011] If the transmission busyness is not greater than the busyness threshold, the current humidity value, the current temperature value, the current air pressure value, and the scooter position data are transmitted to the data regulation unit by using the data transmission unit, and the data regulation unit is used to obtain the processed temperature value, the processed humidity value, the processed air pressure value, and the processed position data, and calculate the current high-level difference according to the processed temperature value and the processed air pressure value;

[0012] Calculate the current rotation degree according to the processed position data, calculate the adjusted power output value based on the processed humidity value, the current rotation degree, and the current high-level difference, and complete the intervention regulation of the electric scooter based on the adjusted power output value.

[0013] Optionally, calculating the transmission busyness of the calculation data transmission unit includes:

[0014] Set a calculation period, obtain transmission data based on the calculation period, and perform an aggregation operation on the obtained transmission data to obtain a transmission data set;

[0015] Perform a data classification operation on the transmission data set to obtain multiple classification data sets, and count the total number of classification data sets of the multiple classification data sets;

[0016] Obtain the transmission rate of each classification data set in the multiple classification data sets, and identify the total amount of data of each classification data set, where the transmission rates of the classification data in the classification data sets are the same;

[0017] Calculate the transmission busyness according to the calculation period, the total number of classification data sets, the transmission rate, and the total amount of data:

[0018]

[0019] Among them, refers to the transmission busyness, refers to a preset traversal parameter, refers to the total number of classification data sets, refers to the weight parameter when the preset traversal parameter is , refers to when the traversal parameter is the transmission rate, Refers to the total amount of data when the traversal parameter is , Refers to the maximum bandwidth amount to be pre-acquired, Refers to the calculation period.

[0020] Optionally, performing a data classification operation on the transmission data set to obtain multiple classification data sets, including:

[0021] Sequentially extracting transmission data from the transmission data set, and performing the following operations on the extracted transmission data:

[0022] Performing a type recognition operation on the extracted transmission data using a preset data type to obtain a recognized type, inputting the transmission data into a pre-constructed data type set corresponding to the recognized type based on the recognized type, removing the extracted transmission data from the transmission data set to obtain an updated data set, updating the transmission data set with the updated data set, using the updated transmission data set as the transmission data set, and returning the above step of sequentially extracting transmission data from the transmission data set until the transmission data set is an empty set, where the data type set is an empty set in the initial state;

[0023] Summarizing the data type set to obtain multiple classification data sets.

[0024] Optionally, performing a data preprocessing operation on the current temperature value, current humidity value, current air pressure value, and scooter location data using the scooter processing end to obtain a processed data set, including:

[0025] Collecting the current temperature value, current humidity value, current air pressure value, and scooter location data to obtain a current data set;

[0026] Setting a conventional temperature range, conventional humidity range, conventional air pressure range, and conventional location range;

[0027] Performing data determination on the current data set using the conventional temperature range, conventional humidity range, conventional air pressure range, and conventional location range to obtain violation identification data, and performing type identification based on the violation identification data to obtain a data identification type;

[0028] Starting a pre-constructed standby detection unit according to the data identification type, and using the standby detection unit to detect standby detection data;

[0029] Removing the violation identification data from the current data set to obtain a removed data set, and inputting the standby detection data into the removed data set to obtain a processed data set.

[0030] Optionally, calculating the current high-level difference according to the processed temperature value and processed air pressure value, including:

[0031] Set the standard temperature, standard altitude, and standard air pressure values, where the standard temperature is the standard temperature at sea level, the standard altitude is the sea level altitude, and the standard air pressure value is the sea level air pressure;

[0032] Calculate the current height difference based on the processed temperature value, processed air pressure value, standard temperature, standard altitude, and standard air pressure value:

[0033]

[0034] Among them, refers to the current height difference, refers to the standard temperature, refers to the preset gas constant, refers to the preset acceleration due to gravity, refers to the natural logarithm, refers to the standard air pressure value, refers to the processed air pressure value, refers to the standard altitude, refers to the processed temperature value.

[0035] Optionally, the calculating the current rotation degree according to the processed position data includes:

[0036] Obtain the previous position data, calculate the scooter direction vector based on the processed position data and the previous position data, obtain the standard direction vector, and calculate the scooter vector modulus based on the scooter direction vector;

[0037] Calculate the standard vector modulus according to the standard direction vector, and calculate the first rotation degree based on the scooter direction vector, standard direction vector, scooter vector modulus, and standard vector modulus:

[0038]

[0039] Among them, refers to the first rotation degree, refers to the scooter direction vector, refers to the dot product symbol, refers to the standard direction vector, refers to the scooter vector modulus, refers to the inverse cosine function, refers to the standard vector modulus;

[0040] Calculate the current rotation degree using the first rotation degree.

[0041] Optionally, the calculating the current rotation degree using the first rotation degree includes:

[0042] Obtain the current speed and current acceleration of the electric scooter, collect road images based on a pre-built vision sensor, and perform curvature analysis on the road images to obtain the road curvature;

[0043] Calculate the current rotation degree based on the current speed, current acceleration, first rotation degree, and road curvature:

[0044]

[0045] Wherein, refers to the current rotation degree, refers to the road curvature, refers to the preset maximum curvature, refers to the preset angle parameter, refers to the current acceleration, refers to the current speed.

[0046] Optionally, the calculating the adjusted power output value based on the processed humidity value, current rotation degree, and current height difference includes:

[0047] Obtain the power supply standard humidity value, power supply maximum humidity value, and power supply minimum humidity value, and calculate the power supply humidity deviation value based on the processed humidity value, power supply standard humidity value, power supply maximum humidity value, and power supply minimum humidity value:

[0048]

[0049] Wherein, refers to the power supply humidity deviation value, refers to the processed humidity value, refers to the power supply standard humidity value, refers to the power supply maximum humidity value, refers to the power supply minimum humidity value;

[0050] Calculate the adjusted power output value based on the current rotation degree, power supply humidity deviation value, and current height difference.

[0051] Optionally, the calculating the adjusted power output value based on the current rotation degree, power supply humidity deviation value, and current height difference includes:

[0052] Obtain the maximum height difference and the initial power output, and calculate the adjusted power output value based on the current rotation degree, power supply humidity deviation value, current height difference, maximum height difference, and initial power output:

[0053]

[0054] Wherein, refers to the adjusted power output value, refers to the preset humidity adjustment parameter, refers to the preset rotation adjustment parameter, refers to the preset height adjustment parameter, refers to the maximum height difference, refers to the initial power output.

[0055] To achieve the above object, the present invention further provides an electric scooter intervention regulation system based on AI analysis of riding trajectories, including:

[0056] A data detection module, configured to receive an intervention regulation instruction, and start a pre - confirmed intervention regulation unit based on the intervention regulation instruction. The intervention regulation unit includes: a pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit, and a data regulation unit;

[0057] Use the pressure detection unit to detect the air pressure to obtain the current air pressure value, use the temperature detection unit to detect the temperature to obtain the current temperature value, and perform humidity detection based on the humidity detection unit to obtain the current humidity value;

[0058] Use the site acquisition unit to collect the scooter site data and calculate the transmission busy degree of the data transmission unit;

[0059] A data processing module, configured to compare the transmission busy degree with a preset busy degree threshold;

[0060] If the transmission busy degree is greater than the busy degree threshold, then transmit the current temperature value, the current humidity value, the current air pressure value, and the scooter site data to a pre - constructed scooter processing end, and use the scooter processing end to perform data pre - processing operations on the current temperature value, the current humidity value, the current air pressure value, and the scooter site data to obtain a processed data set. The processed data set includes: a processed temperature value, a processed humidity value, a processed air pressure value, and processed site data. Transmit the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data to the data regulation unit, and calculate the current high - level difference according to the processed temperature value and the processed air pressure value;

[0061] A data regulation module, configured to, if the transmission busy degree is not greater than the busy degree threshold, use the data transmission unit to transmit the current humidity value, the current temperature value, the current air pressure value, and the scooter site data to the data regulation unit, and use the data regulation unit to obtain the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data, and calculate the current high - level difference according to the processed temperature value and the processed air pressure value;

[0062] An electric energy calculation module, configured to calculate the current rotation degree according to the processed site data, calculate an adjusted electric energy output value based on the processed humidity value, the current rotation degree, and the current high - level difference, and complete the intervention regulation of the electric scooter based on the adjusted electric energy output value.

[0063] To solve the above problems, the present invention further provides an electronic device, and the electronic device includes:

[0064] A memory, storing at least one instruction;

[0065] A processor that executes instructions stored in the memory to implement the above-mentioned electric scooter intervention control method based on AI analysis of riding trajectories.

[0066] To solve the above problems, the present invention also provides a computer-readable storage medium storing at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned electric scooter intervention control method based on AI analysis of riding trajectories.

[0067] To solve the problems described in the background art, first, an intervention control instruction is received, and the intervention control unit is started based on the intervention control instruction. By receiving the intervention control instruction to start the intervention control unit, the intervention control unit can respond in a timely manner, improving the intelligence level of the electric scooter. Secondly, the intervention control unit integrates a pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit, and a data regulation unit, improving the detection ability of the intervention control unit to changes in the surrounding environment and providing a data basis for calculating subsequent adjustments to the electric energy output value. Then, the transmission busy degree of the data transmission unit is calculated, and the transmission busy degree is compared with the busy degree threshold. When the transmission busy degree is greater than the busy degree threshold, the current temperature value, the current humidity value, the current pressure value, and the scooter site data are transmitted to the scooter processing end. Calculating the transmission busy degree of the data transmission unit can understand the current network load situation, thereby dynamically adjusting the output transmission strategy. When the transmission busy degree is greater than the busy degree threshold, first transmit the current temperature value, the current humidity value, the current pressure value, and the scooter site data to the scooter processing end, avoiding network congestion and ensuring that the intervention control unit can still operate stably under high network load, improving the stability of the intervention control unit. Then, the current high altitude difference is calculated based on the processed temperature value and the processed pressure value. By calculating the current high altitude difference, the height change of the electric scooter can be analyzed more accurately. Based on the current high altitude difference, the intervention control unit can adjust the electric energy output of the electric scooter more precisely, improving the driving stability of the electric scooter. Finally, the adjusted electric energy output value is calculated based on the processed humidity value, the current rotation degree, and the current high altitude difference. According to the adjusted electric energy output value, the electric scooter can respond more intelligently to different processed humidity values, the current rotation degree, and the current high altitude difference, improving the driving stability of the electric scooter. Therefore, the present invention can improve the driving stability of the electric scooter. Description of the Drawings

[0068] Figure 1 It is a schematic flowchart of the electric scooter intervention control method based on AI analysis of riding trajectories provided by an embodiment of the present invention;

[0069] Figure 2Functional module diagram of the electric scooter intervention control system based on AI analysis of riding trajectories provided by an embodiment of the present invention;

[0070] Figure 3 Schematic structural diagram of an electronic device for implementing the electric scooter intervention control method based on AI analysis of riding trajectories provided by an embodiment of the present invention.

[0071] Description of reference numerals:

[0072] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0073] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0074] 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.

[0075] An embodiment of the present application provides an electric scooter intervention control method based on AI analysis of riding trajectories. The execution subject of the electric scooter intervention control method based on AI analysis of riding trajectories includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the electric scooter intervention control method based on AI analysis of riding trajectories can be executed by software or hardware installed on 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.

[0076] Refer to Figure 1 As shown, it is a flowchart of an electric scooter intervention control method based on AI analysis of riding trajectories provided by an embodiment of the present invention. In this embodiment, the electric scooter intervention control method based on AI analysis of riding trajectories includes:

[0077] S1. Receive an intervention control instruction, and start a pre - confirmed intervention control unit based on the intervention control instruction. Among them, the intervention control unit includes: a pressure detection unit, a temperature detection unit, a humidity detection unit, a site collection unit, a data transmission unit, and a data regulation unit.

[0078] An interpretable intervention control instruction refers to an instruction manually issued for intervening and controlling an electric scooter. For example, Xiao Zhang is a tester for an electric scooter. One day, Xiao Zhang needs to test the intervention control of the electric scooter, so Xiao Zhang issues an intervention control instruction. The intervention control unit refers to the unit for controlling the electric scooter. The intervention control unit is activated by the intervention control instruction, and the intervention control unit includes: a barometric pressure detection unit, a temperature detection unit, a humidity detection unit, a site collection unit, and a data regulation unit. The barometric pressure detection unit refers to the unit for detecting barometric pressure, and the barometric pressure detection unit is waterproofed to ensure that the barometric pressure detection unit can work in rainy or humid environments. Optionally, the barometric pressure detection unit is a digital barometric pressure sensor. The temperature detection unit refers to the unit for detecting air temperature. Optionally, the temperature detection unit is a digital temperature sensor, and the temperature detection unit is waterproofed. The humidity detection unit refers to the unit for detecting air humidity. Optionally, the humidity detection unit is an SHT30. The site collection unit refers to the unit for collecting scooter site data. Scooter site data refers to the position data of the electric scooter. After the site collection unit collects the site data, it stores the collected site data in the site database. Optionally, the site database is a NoSQL database. The scooter site data includes: scooter longitude and scooter latitude. Scooter longitude refers to the longitude of the location where the scooter is located, and scooter latitude refers to the latitude of the location where the scooter is located. For example, the site data of the electric scooter is: (30.2973, -97.8321), where 30.2973 is the scooter latitude and -97.8321 is the scooter longitude. The data transmission unit refers to the unit for transmitting the current humidity value, the current temperature value, the current barometric pressure value, and the scooter site data to the data regulation unit. The data regulation unit refers to the unit for preprocessing the current temperature value, the current humidity value, the current barometric pressure value, and the scooter site data, and for calculating the current height difference, the current rotation degree, and adjusting the electric energy output value.

[0079] S2. Use the barometric pressure detection unit to detect barometric pressure to obtain the current barometric pressure value, use the temperature detection unit to detect temperature to obtain the current temperature value, and perform humidity detection based on the humidity detection unit to obtain the current humidity value.

[0080] An interpretable current barometric pressure value refers to the value of the barometric pressure obtained after detecting the barometric pressure using the barometric pressure detection unit. The current temperature value refers to the temperature of the air obtained after detecting the temperature using the temperature detection unit. The current humidity value refers to the value of the relative humidity obtained after detecting the humidity using the humidity detection unit. The detection frequencies of the barometric pressure detection unit, the temperature detection unit, and the humidity detection unit are all preset detection frequencies. Optionally, the detection frequency is 1 s / time. For example, during the driving of the electric scooter, use the humidity detection unit to detect humidity, and the current humidity value obtained is 62.21%.

[0081] S3. Use the site acquisition unit to collect skateboard parking space data and calculate the transmission busy degree of the data transmission unit.

[0082] Interpretably, the transmission busy degree refers to the occupancy ratio of the load of the data transmission unit per unit time. The transmission busy degree is a percentage between 0% and 100%. When the transmission busy degree is 100%, it means that the data transmission unit is in a full-load state.

[0083] Specifically, calculating the transmission busy degree of the data transmission unit includes:

[0084] Set a calculation period, obtain transmission data based on the calculation period, and perform an aggregation operation on the obtained transmission data to obtain a transmission data set;

[0085] Perform a data classification operation on the transmission data set to obtain multiple classification data sets, and count the total number of classification data sets of the multiple classification data sets;

[0086] Obtain the transmission rate of each classification data set in the multiple classification data sets, and identify the total amount of data of each classification data set. Among them, the transmission rates of the classification data in the classification data sets are the same;

[0087] Calculate the transmission busy degree according to the calculation period, the total number of classification data sets, the transmission rate, and the total amount of data:

[0088]

[0089] Among them, refers to the transmission busy degree, refers to the preset traversal parameter, refers to the total number of classification data sets, refers to the weight parameter when the preset traversal parameter is ; refers to the transmission rate when the traversal parameter is ; refers to the total amount of data when the traversal parameter is ; refers to the pre-acquired maximum bandwidth amount, refers to the calculation period.

[0090] Interpretable. The calculation period refers to the time period selected for calculating the transmission busyness. The calculation period is a fixed value. Optionally, the calculation period is 1 second. The transmitted data refers to the data transmitted using the data transmission unit. Obtaining the transmitted data based on the calculation period means obtaining the transmitted data within the calculation period. The transmission data set refers to the set composed of the transmitted data. Performing a data classification operation on the transmission data set to obtain multiple classified data sets means classifying the transmission data set according to the types of the transmitted data in the transmission data set. The multiple classified data sets refer to the sets composed of multiple transmitted data obtained after performing the data classification operation on the transmission data set. Each classified data set contains all the transmitted data of the same type. Calculating the total number of classified data sets of the multiple classified data sets means counting the number of all classified data sets. The total number of classified data sets refers to the total number of classified data sets. The transmission rate refers to the rate at which the classified data set transmits data. The unit of the transmission rate is bits per second. The total data volume refers to the total volume of the transmitted data in the classified data set. The unit of the total data volume is bits. The transmission rates of the classified data in the classified data set are the same, which means that the transmission rates of all the classified data in a classified data set are the same. For example, there is a classified data set A, and the transmission rates of all the classified data in the classified data set A are the same. The traversal parameter refers to the parameter set for traversing the classified data set. The range of the traversal parameter is from 1 to the total number of classified data sets. The weight parameter refers to the parameter set artificially to adjust the influence degree of the rate parameter on the transmission busyness. The rate parameter refers to the product of the rates of the classified data sets corresponding to the traversal parameter. The rate product refers to the product of the transmission rate and the total data volume. The maximum bandwidth amount refers to the theoretically maximum bandwidth of the data transmission unit. The unit of the maximum bandwidth amount is bits per second.

[0091] Specifically, performing a data classification operation on the transmission data set to obtain multiple classified data sets includes:

[0092] Sequentially extracting the transmitted data from the transmission data set, and performing the following operations on the extracted transmitted data:

[0093] Performing a type recognition operation on the extracted transmitted data using a preset data type to obtain a recognized type. Based on the recognized type, inputting the transmitted data into the pre-constructed data type set corresponding to the recognized type, removing the extracted transmitted data from the transmission data set to obtain an updated data set, using the updated data set to update the transmission data set, taking the updated transmission data set as the transmission data set, and returning to the above step of sequentially extracting the transmitted data from the transmission data set until the transmission data set is an empty set, where the data type set is an empty set in the initial state;

[0094] Summarizing the data type set to obtain multiple classified data sets.

[0095] Interpretable. The data type refers to the type of transmitted data, which includes: temperature data, humidity data, air pressure data, and site data. Temperature data refers to the data detected by the temperature detection unit, humidity data refers to the data detected by the humidity detection unit, air pressure data refers to the data detected by the air pressure detection unit, and site data refers to the data detected by the site collection unit. The identification type refers to the data type of the transmitted data obtained after identifying the transmitted data through the data type. For example, when identifying the type of transmitted data A, if the data type of transmitted data A is obtained as temperature data, then the identification type of transmitted data A is temperature data. The data type set refers to a pre-constructed set for storing transmitted data of each data type, which includes: temperature data set, humidity data set, air pressure data set, and site data set. The temperature data set refers to the set for storing transmitted data with the data type of temperature data, the humidity data set refers to the set for storing transmitted data with the data type of humidity data, the air pressure data set refers to the set for storing transmitted data with the data type of air pressure data, and the site data set refers to the set for storing transmitted data with the data type of site data. The updated data set refers to the set composed of the remaining transmitted data in the transmitted data set after removing the extracted transmitted data from the transmitted data set. For example, the transmitted data in the transmitted data set are: 1, 2, 3, 4. Transmitted data 1 is extracted from the transmitted data set, and transmitted data 1 is removed from the transmitted data set to obtain the updated data set, and the transmitted data in the updated data set are: 2, 3, 4. Obtaining multiple classification data sets based on the data type set means that when the transmitted data set is an empty set, the transmitted data in the transmitted data set are input into the corresponding data type set according to their data types, so multiple classification data sets can be obtained according to the data type set.

[0096] S4. Compare the transmission busyness with a preset busyness threshold.

[0097] Interpretable. The busyness threshold refers to the threshold of the transmission busyness set by humans.

[0098] If the transmission busyness is greater than the busyness threshold, then execute S5. Transmit the current temperature value, current humidity value, current air pressure value, and scooter site data to a pre-constructed scooter processing end, and use the scooter processing end to perform data preprocessing operations on the current temperature value, current humidity value, current air pressure value, and scooter site data to obtain a processed data set. Among them, the processed data set includes: processed temperature value, processed humidity value, processed air pressure value, and processed site data. Transmit the processed temperature value, processed humidity value, processed air pressure value, and processed site data to the data regulation unit, and calculate the current high-level difference according to the processed temperature value and processed air pressure value.

[0099] Interpretable. The scooter processing end refers to the edge computing node equipped on the electric scooter, which is used to receive the current temperature value, current humidity value, current air pressure value and scooter location data when the transmission busy degree of the data transmission unit is greater than the busy degree threshold, and perform data preprocessing operations on the received current temperature value, current humidity value, current air pressure value and scooter location data. The processed temperature value refers to the data obtained after data preprocessing of the current temperature value, the processed humidity value refers to the data obtained after data preprocessing of the current humidity value, the processed air pressure value refers to the data obtained after data preprocessing of the current air pressure value, the processed location data refers to the data obtained after data preprocessing of the scooter location data, and the processed location data will replace the scooter location data in the location database.

[0100] Specifically, the data preprocessing operations performed on the current temperature value, current humidity value, current air pressure value and scooter location data by the scooter processing end to obtain a processed data set include:

[0101] Collect the current temperature value, current humidity value, current air pressure value and scooter location data to obtain a current data set;

[0102] Set a conventional temperature range, conventional humidity range, conventional air pressure range and conventional location range;

[0103] Use the conventional temperature range, conventional humidity range, conventional air pressure range and conventional location range to perform data determination on the current data set to obtain violation identification data, and perform category identification according to the violation identification data to obtain data identification categories;

[0104] Start a pre-constructed standby detection unit according to the data identification category, and use the standby detection unit to detect standby detection data;

[0105] Remove the violation identification data from the current data set to obtain a removed data set, and input the standby detection data into the removed data set to obtain a processed data set.

[0106] Explainably, the current data set refers to a set consisting of the current temperature value, the current humidity value, the current air pressure value and the scooter location data, the conventional temperature range refers to a range manually set for determining whether the current temperature value has a detection error, optionally, the conventional temperature range is 0°C to 50°C, the conventional humidity range refers to a range manually set for determining whether the current humidity value has a detection error, optionally, the conventional humidity range is 20% to 90% relative humidity, the conventional air pressure range refers to a range manually set for determining whether the current air pressure value has a detection error, and the conventional location range refers to a range manually set for determining whether the scooter location data has a detection error. Using the conventional temperature range, conventional humidity range, conventional air pressure range and conventional site range to judge the current data set, and obtaining the violation identification data means judging the current temperature value, current humidity value, current air pressure value and scooter site data in the current data set with the conventional temperature range, conventional humidity range, conventional air pressure range and conventional site range respectively, obtaining the judgment data, and collecting the judgment data to obtain the judgment data set. For example, if the current temperature value is not within the conventional temperature range, and the current humidity value is not within the conventional humidity range, then the current temperature value and the current humidity value are confirmed to be violation identification data. The data identification type refers to the data type of the violation identification data obtained after the violation identification data is identified. For example, the current temperature value is the violation identification data, and the current temperature value is identified to obtain the data type of temperature data. Starting a pre-built spare detection unit according to the data identification type refers to starting the corresponding spare detection unit according to the data identification type. The spare detection unit includes: a spare temperature unit, a spare humidity unit, a spare air pressure unit and a spare location unit. The spare temperature unit refers to a unit started when the current temperature value is not within the conventional temperature range for re-acquiring the current temperature value. The spare humidity unit refers to a unit started when the current humidity value is not within the conventional humidity range for re-acquiring the current humidity value. The spare air pressure unit refers to a unit started when the current air pressure value is not within the conventional air pressure range for re-acquiring the current air pressure value. The spare location unit refers to a unit started when the scooter location data is not within the conventional location range for re-acquiring the scooter location data. Spare detection data refers to data detected by using the spare detection unit. For example, if the data identification type is temperature data, the spare temperature unit is started according to the data identification type, and the temperature data is detected by using the spare temperature unit. The temperature data is the spare detection data. The elimination data set refers to the set obtained after the illegal identification data is eliminated from the current data set. The processing data set refers to the set obtained after the spare detection data is input into the elimination data set.

[0107] In detail, the current high position difference is calculated according to the processing temperature value and the processing air pressure value, including:

[0108] Set the standard temperature, standard altitude, and standard air pressure values, where the standard temperature is the standard temperature at sea level, the standard altitude is the sea level altitude, and the standard air pressure value is the sea level air pressure;

[0109] Calculate the current height difference based on the processed temperature value, processed air pressure value, standard temperature, standard altitude, and standard air pressure value:

[0110]

[0111] Where, refers to the current height difference, refers to the standard temperature, refers to the preset gas constant, refers to the preset acceleration due to gravity, refers to the natural logarithm, refers to the standard air pressure value, refers to the processed air pressure value, refers to the standard altitude, refers to the processed temperature value.

[0112] Interpretably, the current height difference refers to the height difference between the electric scooter and the ground. For example, if the electric scooter is 10 cm above the ground, the current height difference is 10 cm. The standard temperature refers to the standard temperature at sea level, which is 15 °C. The standard altitude refers to the sea level altitude, the standard air pressure value refers to the sea level air pressure, the gas constant is 8.314 J / (mol·K), and the acceleration due to gravity is 9.81 m / s 2 , where the standard temperature at sea level, sea level altitude, sea level air pressure, gas constant, and acceleration due to gravity are all prior arts and will not be elaborated here.

[0113] If the transmission busyness is not greater than the busyness threshold, then execute S6. Use the data transmission unit to transmit the current humidity value, current temperature value, current air pressure value, and scooter location data to the data regulation unit, and use the data regulation unit to obtain the processed temperature value, processed humidity value, processed air pressure value, and processed location data, and calculate the current height difference based on the processed temperature value and processed air pressure value.

[0114] Interpretably, obtaining the processed temperature value, processed humidity value, processed air pressure value, and processed location data using the data regulation unit is the same as the above method of performing data preprocessing operations on the current temperature value, current humidity value, current air pressure value, and scooter location data using the scooter processing end, and will not be elaborated here.

[0115] S7. Calculate the current rotation degree based on the processed location data, calculate the adjusted power output value based on the processed humidity value, current rotation degree, and current height difference, and complete the intervention regulation of the electric scooter based on the adjusted power output value.

[0116] Specifically, calculating the current rotation degree according to the processing site data includes:

[0117] Obtain the previous site data, calculate the scooter direction vector based on the processing site data and the previous site data, obtain the standard direction vector, and calculate the scooter vector modulus based on the scooter direction vector;

[0118] Calculate the standard vector modulus according to the standard direction vector, and calculate the first rotation degree based on the scooter direction vector, the standard direction vector, the scooter vector modulus, and the standard vector modulus:

[0119]

[0120] Wherein, represents the first rotation degree, represents the scooter direction vector, represents the dot product symbol, represents the standard direction vector, represents the scooter vector modulus, represents the arccosine function, represents the standard vector modulus;

[0121] Calculate the current rotation degree using the first rotation degree.

[0122] It can be explained that the current rotation degree refers to the angle between the current driving direction and the standard direction, the range of the angle is 0° to 90°, the current driving direction refers to the direction of the trajectory along which the electric scooter travels, which is described by the scooter direction vector, the standard direction refers to the direction set for the electric scooter without external interference, and this direction is the horizontal direction. External interference refers to factors that affect the forward direction of the electric scooter. For example, the external interference is a bend. The previous site data refers to the site data adjacent to the processing site data in the site database. The scooter direction vector refers to the vector from the previous site data to the processing site data. The standard direction vector refers to the direction vector of the standard direction. The scooter vector modulus refers to the modulus of the scooter direction vector. The standard vector modulus refers to the modulus of the standard direction vector. The first rotation degree refers to the angle between the current driving direction and the standard direction of the electric scooter calculated through the scooter direction vector, the standard direction vector, the scooter vector modulus, and the standard vector modulus without introducing the current acceleration and road curvature.

[0123] Specifically, calculating the current rotation degree using the first rotation degree includes:

[0124] Obtain the current speed and current acceleration of the electric scooter, analyze the curvature of the road image collected by the pre-built vision sensor based on the road image, and obtain the road curvature;

[0125] Calculate the current rotation degree according to the current speed, the current acceleration, the first rotation degree, and the road curvature:

[0126]

[0127] Among them, refers to the current rotation degree, refers to the road curvature, refers to the preset maximum curvature, refers to the preset angle parameter, refers to the current acceleration, refers to the current speed.

[0128] Interpretably, the current speed refers to the current speed of the electric scooter, the current acceleration refers to the current acceleration of the electric scooter, the vision sensor refers to the device for collecting road images. Optionally, the vision sensor is an RGB camera. Curvature analysis is performed on the road image to obtain the road curvature, which means using the Hough transform to process the road image to obtain the road curvature. This is an existing technology and will not be elaborated here. The road curvature refers to the degree of bending of the road. The greater the road curvature, the greater the degree of bending of the road. The maximum curvature refers to the maximum value of the road curvature set by humans, and the angle parameter refers to the parameter set by humans for adjusting the influence degree on the current rotation degree. The larger the angle parameter, the greater the influence degree on the current rotation degree, the larger it is, indicating the greater the influence degree on the current rotation degree. Therefore, setting the angle parameter to a larger value can more accurately reflect the influence on the current rotation degree.

[0129] Specifically, calculating the adjusted power output value based on the processed humidity value, the current rotation degree, and the current height difference includes:

[0130] Obtain the power standard humidity value, the power maximum humidity value, and the power minimum humidity value, and calculate the power humidity deviation value based on the processed humidity value, the power standard humidity value, the power maximum humidity value, and the power minimum humidity value:

[0131]

[0132] Among them, refers to the power humidity deviation value, refers to the processed humidity value, refers to the power standard humidity value, refers to the power maximum humidity value, refers to the power minimum humidity value;

[0133] Calculate the adjusted power output value based on the current rotation degree, the power humidity deviation value, and the current height difference.

[0134] Interpretably, the power supply standard humidity value refers to the humidity value set artificially for comparison with the processed humidity value. Optionally, the power supply standard humidity value is 50%. The maximum power supply humidity value refers to the maximum humidity value that the power supply of the electric scooter can withstand under normal working conditions. Optionally, the maximum power supply humidity value is 90%. The minimum power supply humidity value refers to the minimum humidity value that the power supply of the electric scooter can withstand under normal working conditions. Optionally, the minimum power supply humidity value is 20%. The power supply humidity deviation value refers to the deviation value of the processed humidity value relative to the power supply standard humidity value calculated based on the processed humidity value, the power supply standard humidity value, the maximum power supply humidity value, and the minimum power supply humidity value. This deviation value reflects the degree of deviation of the processed humidity value relative to the power supply standard humidity value.

[0135] Specifically, calculating the adjusted power output value based on the current rotation degree, the power supply humidity deviation value, and the current height difference includes:

[0136] Obtain the maximum height difference and the initial power output, and calculate the adjusted power output value based on the current rotation degree, the power supply humidity deviation value, the current height difference, the maximum height difference, and the initial power output:

[0137]

[0138] Among them, refers to the adjusted power output value, refers to the preset humidity adjustment parameter, refers to the preset rotation adjustment parameter, refers to the preset height adjustment parameter, refers to the maximum height difference, refers to the initial power output.

[0139] Interpretability, the maximum height difference refers to the maximum height difference that an electric scooter can withstand, which is determined by the manufacturing materials of the electric scooter and the structural design of the electric scooter. The initial power output refers to the electric energy currently output by the power source of the electric scooter. The adjusted power output value refers to the output value of the electric energy obtained after adjusting the initial power output according to the current rotation degree, the power source humidity deviation value, the current height difference, and the maximum height difference. The humidity adjustment parameter refers to a parameter set by humans to adjust the influence degree of the power source humidity deviation value on the adjusted power output value. The larger the humidity adjustment parameter, the greater the influence degree of the power source humidity deviation value on the adjusted power output value. The rotation adjustment parameter refers to a parameter set by humans to adjust the influence degree of the current rotation degree on the adjusted power output value. The larger the rotation adjustment parameter, the greater the influence degree of the current rotation degree on the adjusted power output value. The height adjustment parameter refers to a parameter set by humans to adjust the influence degree of the current height difference on the adjusted power output value. The larger the height adjustment parameter, the greater the influence degree of the current height difference on the adjusted power output value. For example, the larger the power source humidity deviation value, the greater the influence degree of the power source humidity deviation value on the adjusted power output value. Therefore, the humidity adjustment parameter is set to be relatively large. For example, when the current rotation degree is large and the electric scooter is performing a turning operation, the adjusted power output value is calculated according to the current rotation degree, and the current power output is adjusted according to the adjusted power output value, which can better maintain the balance of the electric scooter and overcome the centrifugal force generated during turning, improving the stability of the electric scooter during driving.

[0140] To solve the problems described in the background art, first, the present invention receives an intervention regulation instruction, activates the intervention regulation unit based on the intervention regulation instruction. By receiving the intervention regulation instruction to activate the intervention regulation unit, the intervention regulation unit can respond in a timely manner, improving the intelligence level of the electric scooter. Secondly, the intervention regulation unit integrates a pressure detection unit, a temperature detection unit, a humidity detection unit, a site collection unit, a data transmission unit, and a data regulation unit, improving the detection ability of the intervention regulation unit to changes in the surrounding environment and providing a data basis for calculating subsequent adjustments to the electric energy output value. Then, calculate the transmission busy degree of the data transmission unit, and compare the transmission busy degree with the busy degree threshold. When the transmission busy degree is greater than the busy degree threshold, transmit the current temperature value, the current humidity value, the current pressure value, and the scooter site data to the scooter processing end. Calculating the transmission busy degree of the data transmission unit can understand the current network load situation, thereby dynamically adjusting the output transmission strategy. When the transmission busy degree is greater than the busy degree threshold, first transmit the current temperature value, the current humidity value, the current pressure value, and the scooter site data to the scooter processing end, avoiding network congestion and ensuring that the intervention regulation unit can still operate stably under high network load, improving the stability of the intervention regulation unit. Then, calculate the current height difference based on the processed temperature value and the processed pressure value. By calculating the current height difference, the height change of the electric scooter can be analyzed more accurately. Based on the current height difference, the intervention regulation unit can adjust the electric energy output of the electric scooter more precisely, improving the driving stability of the electric scooter. Finally, calculate the adjusted electric energy output value based on the processed humidity value, the current rotation degree, and the current height difference. According to the adjusted electric energy output value, the electric scooter can respond more intelligently to different processed humidity values, the current rotation degree, and the current height difference, improving the driving stability of the electric scooter. Therefore, the present invention can improve the driving stability of the electric scooter.

[0141] As Figure 2 shown, it is a functional module diagram of an electric scooter intervention regulation system based on AI analysis of riding trajectories provided by an embodiment of the present invention.

[0142] The electric scooter intervention regulation system 100 based on AI analysis of riding trajectories described in the present invention can be installed in an electronic device. According to the implemented functions, the electric scooter intervention regulation system 100 based on AI analysis of riding trajectories can include a data detection module 101, a data processing module 102, a data regulation module 103, and an electric energy calculation module 104. The modules described in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, and are stored in the memory of the electronic device.

[0143] The data detection module 101 is configured to receive an intervention regulation instruction and start a pre - confirmed intervention regulation unit based on the intervention regulation instruction. The intervention regulation unit includes: a barometric pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit, and a data regulation unit;

[0144] Use the barometric pressure detection unit to detect the barometric pressure to obtain the current barometric pressure value, use the temperature detection unit to detect the temperature to obtain the current temperature value, and perform humidity detection based on the humidity detection unit to obtain the current humidity value;

[0145] Use the site acquisition unit to collect skateboard parking site data and calculate the transmission busy degree of the data transmission unit;

[0146] The data processing module 102 is configured to compare the transmission busy degree with a preset busy degree threshold;

[0147] If the transmission busy degree is greater than the busy degree threshold, then transmit the current temperature value, the current humidity value, the current barometric pressure value, and the skateboard parking site data to a pre - constructed skateboard processing end, and use the skateboard processing end to perform data pre - processing operations on the current temperature value, the current humidity value, the current barometric pressure value, and the skateboard parking site data to obtain a processed data set. The processed data set includes: a processed temperature value, a processed humidity value, a processed barometric pressure value, and processed site data. Transmit the processed temperature value, the processed humidity value, the processed barometric pressure value, and the processed site data to the data regulation unit, and calculate the current high - level difference based on the processed temperature value and the processed barometric pressure value;

[0148] The data regulation module 103 is configured to, if the transmission busy degree is not greater than the busy degree threshold, use the data transmission unit to transmit the current humidity value, the current temperature value, the current barometric pressure value, and the skateboard parking site data to the data regulation unit, and use the data regulation unit to obtain the processed temperature value, the processed humidity value, the processed barometric pressure value, and the processed site data, and calculate the current high - level difference based on the processed temperature value and the processed barometric pressure value;

[0149] The electric energy calculation module 104 is configured to calculate the current rotation degree according to the processed site data, calculate an adjusted electric energy output value based on the processed humidity value, the current rotation degree, and the current high - level difference, and complete the intervention regulation of the electric skateboard based on the adjusted electric energy output value.

[0150] Specifically, each module in the electric skateboard intervention regulation system 100 based on AI analysis of the riding trajectory in the embodiment of the present invention adopts the same technical means as those in the above - mentioned Figure 1 The electric skateboard intervention regulation method based on AI analysis of the riding trajectory described therein, and can produce the same technical effects, which will not be elaborated here.

[0151] Such as Figure 3As shown, it is a schematic structural diagram of an electronic device for implementing an electric scooter intervention control method based on AI analysis of riding trajectories provided by an embodiment of the present invention.

[0152] The electronic device 1 may include a processor 10, a memory 11, and a bus 12, and may further include a computer program stored in the memory 11 and executable on the processor 10, such as an electric scooter intervention control method program based on AI analysis of riding trajectories.

[0153] Among them, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, magnetic disks, optical disks, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as the mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 1. Further, the memory 11 also includes the internal storage unit of the electronic device 1 and also includes external storage devices. The memory 11 can be used not only to store application software installed on the electronic device 1 and various types of data, such as the code of the electric scooter intervention control method program based on AI analysis of riding trajectories, etc., but also to temporarily store data that has been output or will be output.

[0154] In some embodiments, the processor 10 may be composed of integrated circuits. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same or different functions, including a combination of one or more Central Processing Units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, connecting various components of the entire electronic device through various interfaces and lines, and by running or executing programs or modules stored in the memory 11 (such as the electric scooter intervention control method program based on AI analysis of riding trajectories, etc.), and calling data stored in the memory 11, to execute various functions of the electronic device 1 and process data.

[0155] The bus 12 can be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to implement the connection and communication between the memory 11 and at least one processor 10, etc.

[0156] Figure 3 Only an electronic device with components is shown. Those skilled in the art can understand that Figure 3 The shown structure does not constitute a limitation on the electronic device 1, and it may include fewer or more components than shown, or combine certain components, or have a different component layout.

[0157] For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for powering each component. Preferably, the power source can be logically connected to the at least one processor 10 through a power management device, so as to implement functions such as charging management, discharging management, and power consumption management through the power management device. The power source may also include any components such as one or more DC or AC power sources, a recharge device, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device 1 may also include a variety of sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0158] Furthermore, the electronic device 1 may further 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.

[0159] Optionally, the electronic device 1 may further include a user interface. The user interface can be a display, an input unit (such as a keyboard), and optionally, the user interface can also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display can also be appropriately referred to as a display screen or a display unit, which is used to display the information processed in the electronic device 1 and to display a visual user interface.

[0160] The program of the electric scooter intervention control method based on AI analysis of the riding trajectory stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0161] Receive an intervention control instruction, and start a pre - confirmed intervention control unit based on the intervention control instruction. Among them, the intervention control unit includes: a pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit, and a data regulation unit;

[0162] Use the pressure detection unit to detect the air pressure to obtain the current air pressure value, use the temperature detection unit to detect the temperature to obtain the current temperature value, and perform humidity detection based on the humidity detection unit to obtain the current humidity value;

[0163] Use the site acquisition unit to collect scooter site data and calculate the transmission busy degree of the data transmission unit;

[0164] Compare the transmission busy degree with a preset busy degree threshold;

[0165] If the transmission busy degree is greater than the busy degree threshold, then transmit the current temperature value, the current humidity value, the current air pressure value, and the scooter site data to a pre - constructed scooter processing end, and use the scooter processing end to perform data pre - processing operations on the current temperature value, the current humidity value, the current air pressure value, and the scooter site data to obtain a processed data set. Among them, the processed data set includes: a processed temperature value, a processed humidity value, a processed air pressure value, and processed site data. Transmit the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data to the data regulation unit, and calculate the current height difference based on the processed temperature value and the processed air pressure value;

[0166] If the transmission busy degree is not greater than the busy degree threshold, then use the data transmission unit to transmit the current humidity value, the current temperature value, the current air pressure value, and the scooter site data to the data regulation unit, and use the data regulation unit to obtain the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data, and calculate the current height difference based on the processed temperature value and the processed air pressure value;

[0167] Calculate the current rotation degree according to the processed site data, calculate the adjusted electric energy output value based on the processed humidity value, the current rotation degree, and the current height difference, and complete the intervention control of the electric scooter based on the adjusted electric energy output value.

[0168] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 the description of the relevant steps in the corresponding embodiment, which will not be elaborated here.

[0169] Furthermore, if the modules / units integrated in the electronic device 1 are implemented in the form of software functional units and sold or used as independent products, they 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 device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM, Read-Only Memory).

[0170] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can implement:

[0171] Receiving an intervention regulation instruction, and starting a pre-confirmed intervention regulation unit based on the intervention regulation instruction, where the intervention regulation unit includes: a pressure detection unit, a temperature detection unit, a humidity detection unit, a site collection unit, a data transmission unit, and a data regulation unit;

[0172] Using the pressure detection unit to detect the air pressure to obtain the current air pressure value, using the temperature detection unit to detect the temperature to obtain the current temperature value, and based on the humidity detection unit to detect the humidity to obtain the current humidity value;

[0173] Using the site collection unit to collect skateboard parking site data and calculate the transmission busy degree of the data transmission unit;

[0174] Comparing the transmission busy degree with a preset busy degree threshold;

[0175] If the transmission busy degree is greater than the busy degree threshold, then transmit the current temperature value, the current humidity value, the current air pressure value, and the skateboard parking site data to a pre-constructed skateboard processing end, and use the skateboard processing end to perform data preprocessing operations on the current temperature value, the current humidity value, the current air pressure value, and the skateboard parking site data to obtain a processed data set, where the processed data set includes: a processed temperature value, a processed humidity value, a processed air pressure value, and processed site data, transmit the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data to the data regulation unit, and calculate the current high-level difference according to the processed temperature value and the processed air pressure value;

[0176] If the transmission busy degree is not greater than the busy degree threshold, then use the data transmission unit to transmit the current humidity value, the current temperature value, the current air pressure value, and the skateboard parking site data to the data regulation unit, and use the data regulation unit to obtain the processed temperature value, the processed humidity value, the processed air pressure value, and the processed site data, and calculate the current high-level difference according to the processed temperature value and the processed air pressure value;

[0177] Calculate the current rotation degree according to the processing site data, calculate the adjusted power output value based on the processing humidity value, the current rotation degree, and the current high-level difference, and complete the intervention regulation of the electric scooter based on the adjusted power output value.

[0178] In 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 merely illustrative, and there may be other partitioning methods in actual implementation.

[0179] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, in each embodiment of the present invention, the functional modules can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a hardware plus software functional module.

[0181] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An electric scooter intervention control method based on riding trajectory AI analysis, characterized in that: The method comprises: Receiving an intervention control instruction, and starting a pre-confirmed intervention control unit based on the intervention control instruction, wherein the intervention control unit includes: an air pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit and a data control unit; The air pressure detection unit is used to detect the air pressure to obtain the current air pressure value, the temperature detection unit is used to detect the temperature to obtain the current temperature value, and the humidity detection unit is used to detect the humidity to obtain the current humidity value; The location data of the scooter is collected by using the location collection unit, and the transmission busyness of the data transmission unit is calculated; Comparing the transmission busyness with a preset busyness threshold; If the transmission busyness is greater than the busyness threshold, the current temperature value, the current humidity value, the current air pressure value and the scooter location data are transmitted to the pre-built scooter processing end, and the scooter processing end is used to perform data preprocessing operations on the current temperature value, the current humidity value, the current air pressure value and the scooter location data to obtain a processing data set, wherein the processing data set includes: a processing temperature value, a processing humidity value, a processing air pressure value and a processing location data, the processing temperature value, the processing humidity value, the processing air pressure value and the processing location data are transmitted to the data control unit, and the current high position difference is calculated according to the processing temperature value and the processing air pressure value; If the transmission busyness is not greater than the busyness threshold, the data transmission unit is used to transmit the current humidity value, the current temperature value, the current air pressure value and the scooter location data to the data control unit, and the data control unit is used to obtain the processing temperature value, the processing humidity value, the processing air pressure value and the processing location data, and the current high position difference is calculated according to the processing temperature value and the processing air pressure value; The current rotation degree is calculated according to the processed position data, the adjusted electric energy output value is calculated based on the processed humidity value, the current rotation degree and the current high position difference, and the intervention control of the electric scooter is completed based on the adjusted electric energy output value.

2. The electric scooter intervention control method based on riding trajectory AI analysis according to claim 1, characterized in that: The calculating the transmission busyness of the data transmission unit includes: Setting a calculation cycle, acquiring transmission data based on the calculation cycle, and performing a collection operation on the acquired transmission data to obtain a transmission data set; Performing a data classification operation on the transmission data set to obtain multiple classified data sets, and counting the total number of classified data sets of the multiple classified data sets; Obtaining a transmission rate of each of the plurality of classification data sets, and identifying a total amount of data in each classification data set, wherein the transmission rates of the classification data in the classification data sets are all the same; The transmission busyness is calculated based on the calculation cycle, the total number of classified data sets, the transmission rate and the total amount of data: in, Refers to the transmission busyness, Refers to the preset traversal parameters, Refers to the total number of classification data sets, The preset traversal parameters are The weight parameter is Refers to the traversal parameters as The conveying rate at Refers to the traversal parameters as The total amount of data at Refers to the maximum amount of pre-acquired bandwidth. Refers to the calculation cycle.

3. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 2, characterized in that: The data classification operation is performed on the transmission data set to obtain multiple classified data sets, including: Extracting transmission data from the transmission data set in sequence, and performing the following operations on the extracted transmission data: Performing a type identification operation on the extracted transmission data using a preset data type to obtain an identification type, inputting the transmission data into a pre-constructed data type set corresponding to the identification type based on the identification type, removing the extracted transmission data from the transmission data set to obtain an updated data set, updating the transmission data set using the updated data set, so that the updated transmission data set is the transmission data set, and returning to the above step of sequentially extracting transmission data from the transmission data set until the transmission data set is an empty set, wherein the data type set is an empty set in an initial state; The data category sets are aggregated to obtain multiple classification data sets.

4. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 3 is characterized in that: The scooter processing terminal performs data preprocessing operations on the current temperature value, the current humidity value, the current air pressure value and the scooter location data to obtain a processed data set, including: Gather the current temperature value, current humidity value, current air pressure value and scooter location data to obtain the current data set; Set the normal temperature range, normal humidity range, normal air pressure range and normal position range; Using the conventional temperature range, conventional humidity range, conventional air pressure range and conventional location range to perform data judgment on the current data set, obtain violation identification data, perform category identification based on the violation identification data, and obtain data identification category; Starting a pre-built backup detection unit according to the data identification type, and using the backup detection unit to detect the backup detection data; The illegal identification data is removed from the current data set to obtain a removed data set, and the spare detection data is input into the removed data set to obtain a processed data set.

5. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 4 is characterized in that: The calculating the current high position difference according to the processing temperature value and the processing air pressure value includes: Set the standard temperature, standard altitude and standard air pressure values, where the standard temperature is the standard temperature at sea level, the standard altitude is the altitude at sea level, and the standard air pressure is the pressure at sea level; The current altitude difference is calculated based on the processing temperature value, processing air pressure value, standard temperature, standard altitude and standard air pressure value: in, Refers to the current high difference, Refers to standard temperature, refers to the preset gas constant, Refers to the preset gravity acceleration, refers to the natural logarithm, Refers to the standard atmospheric pressure value. Refers to the processing air pressure value, Refers to the standard height, Refers to the processing temperature value.

6. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 5, characterized in that: The step of calculating the current rotation degree according to the processing position data comprises: Acquire the pre-position data, calculate the scooter direction vector based on the processed position data and the pre-position data, acquire the standard direction vector, and calculate the scooter vector modulus based on the scooter direction vector; The standard vector modulus is calculated according to the standard direction vector, and the first rotation degree is calculated based on the scooter direction vector, the standard direction vector, the scooter vector modulus and the standard vector modulus: in, refers to the first degree of rotation, is the scooter direction vector, Point to the multiplication symbol, refers to the standard direction vector, refers to the vector modulus of the scooter, refers to the inverse cosine function, Refers to the standard vector modulus; The current rotation degree is calculated using the first rotation degree.

7. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 6, characterized in that: The calculating the current rotation degree by using the first rotation degree comprises: Obtain the current speed and acceleration of the electric scooter, collect road images based on the pre-built visual sensor, perform curvature analysis on the road images, and obtain the road curvature; Calculate the current rotation degree based on the current speed, current acceleration, first rotation degree and road curvature: in, Refers to the current rotation degree, Refers to the curvature of the road. Refers to the preset maximum curvature, Refers to the preset angle parameters, refers to the current acceleration, Indicates the current speed.

8. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 7, characterized in that: The step of calculating and adjusting the electric energy output value based on the processed humidity value, the current rotation degree and the current high position difference comprises: Obtain a power supply standard humidity value, a power supply maximum humidity value, and a power supply minimum humidity value, and calculate a power supply humidity deviation value based on the processing humidity value, the power supply standard humidity value, the power supply maximum humidity value, and the power supply minimum humidity value: in, Refers to the power supply humidity deviation value, Refers to the processing humidity value, Refers to the standard humidity value of the power supply, Refers to the maximum humidity value of the power supply, Refers to the minimum humidity value of the power supply; The power output value is adjusted based on the current rotation degree, the power supply humidity deviation value and the current high voltage difference.

9. The electric scooter intervention control method based on riding trajectory AI analysis as claimed in claim 8, characterized in that: The adjusting the electric energy output value based on the current rotation degree, the power supply humidity deviation value and the current high position difference calculation includes: The maximum high position difference and the initial power output are obtained, and the power output value is adjusted based on the current rotation degree, the power supply humidity deviation value, the current high position difference, the maximum high position difference and the initial power output: in, Refers to adjusting the power output value, Refers to the preset humidity adjustment parameters, Refers to the preset rotation adjustment parameters, Refers to the preset high-level adjustment parameters, Refers to the maximum height difference, Refers to the initial power output.

10. An electric scooter intervention control system based on riding trajectory AI analysis, characterized in that: The system comprises: A data detection module, used to receive an intervention control instruction, and start a pre-confirmed intervention control unit based on the intervention control instruction, wherein the intervention control unit includes: an air pressure detection unit, a temperature detection unit, a humidity detection unit, a site acquisition unit, a data transmission unit and a data control unit; The air pressure detection unit is used to detect the air pressure to obtain the current air pressure value, the temperature detection unit is used to detect the temperature to obtain the current temperature value, and the humidity detection unit is used to detect the humidity to obtain the current humidity value; The location data of the scooter is collected by using the location collection unit, and the transmission busyness of the data transmission unit is calculated; A data processing module, used for comparing the transmission busyness with a preset busyness threshold; If the transmission busyness is greater than the busyness threshold, the current temperature value, the current humidity value, the current air pressure value and the scooter location data are transmitted to the pre-built scooter processing end, and the scooter processing end is used to perform data preprocessing operations on the current temperature value, the current humidity value, the current air pressure value and the scooter location data to obtain a processing data set, wherein the processing data set includes: a processing temperature value, a processing humidity value, a processing air pressure value and a processing location data, the processing temperature value, the processing humidity value, the processing air pressure value and the processing location data are transmitted to the data control unit, and the current high position difference is calculated according to the processing temperature value and the processing air pressure value; A data control module is used for transmitting the current humidity value, the current temperature value, the current air pressure value and the scooter location data to the data control unit by using the data transmission unit if the transmission busyness is not greater than the busyness threshold, and obtaining the processing temperature value, the processing humidity value, the processing air pressure value and the processing location data by using the data control unit, and calculating the current high position difference according to the processing temperature value and the processing air pressure value; The electric energy calculation module is used to calculate the current rotation degree according to the processing position data, calculate the adjusted electric energy output value based on the processed humidity value, the current rotation degree and the current high position difference, and complete the intervention control of the electric scooter based on the adjusted electric energy output value.

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