Two-wheel motor vehicle virtual interactive racing system based on internet of things and vehicle

Abstract

This application discloses a virtual interactive racing system and vehicle for two-wheeled vehicles based on the Internet of Things (IoT). The system includes a user mobile app, a smart two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform. After the user selects one of three racing modes—single-player competition, team battle, or multiplayer free-for-all—through the app's built-in interactive control module, the smart two-wheeled vehicle terminal collects the user's riding data and ELO score in real time. The edge computing node preprocesses the raw riding data to obtain valid data. The cloud matching module combines the racing mode, valid data, and ELO score to match the user with a suitable opponent or team, and the rendering module generates the corresponding virtual racing scene accordingly. The virtual world engine, based on the real GPS trajectories of all participants, synchronously maps and updates the vehicle's posture, track position, and racing interaction results within the virtual scene, reflecting the racing status. This application enables real-time virtual riding competition across geographical regions.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to a virtual interactive racing system and vehicle for two-wheeled vehicles based on the Internet of Things. Background Technology

[0002] With the increasing popularity of two-wheeled electric vehicles (such as electric bicycles and electric scooters), coupled with the continuous upgrading of IoT technology, two-wheeled travel is no longer just a simple means of transportation. User needs have shifted from basic riding and data recording to pursuing more fun, social, and competitive experiences. Current mainstream sports apps only support data recording, leaderboards, and simple online challenges, making it difficult to adapt to the new user demands. These platforms generally suffer from three major problems: First, the interactive mode is mainly based on asynchronous challenges, preventing users from competing with other riders in real time and lacking an immediacy of competition; second, the competition format is limited to data comparisons such as speed and mileage, lacking gamified creative design and resulting in a dull and monotonous riding experience; third, events are constrained by geographical conditions, relying on fixed routes and areas, and failing to achieve cross-regional interactive linkage.

[0003] Therefore, current cycling-related applications still have significant shortcomings in user experience, making it difficult to meet users' needs for immersive, real-time interactive cycling experiences. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a virtual interactive racing system and vehicle for two-wheeled vehicles based on the Internet of Things (IoT), which enables real-time virtual riding competitions across regions, creating a gamified and immersive battle experience and breaking through the limitations of traditional riding applications.

[0005] The embodiments of this application disclose the following technical solutions: A virtual interactive racing system for two-wheeled vehicles based on the Internet of Things (IoT) includes a user mobile app, an intelligent two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform. The user mobile app includes an interactive control module, and the cloud processing platform includes a matching module, a rendering module, and a virtual world engine. The interactive control module is used to receive the competition mode selected by the target user; the competition mode includes single-player competition, team battle, or multiplayer free-for-all. The intelligent two-wheeled vehicle terminal, in response to the competition mode selected by the target user, is used to collect the target user's riding data and ELO score in real time; the riding data includes vehicle motion parameters and vehicle geographical location information. The edge computing node is used to preprocess the cycling data to obtain valid cycling data; The matching module is used to match the target user with competition participants based on the competition mode, the valid cycling data, and the ELO score; the competition participants include suitable opponents or opposing teams. The rendering module is used to construct a virtual competition scene adapted to the competition mode based on the competition mode, the valid cycling data, and the virtual avatar configuration information of the target user and the matching competition participants. The intelligent two-wheeled vehicle terminal is also used to acquire the real GPS trajectories of the target user and the matching competition participants; The virtual world engine is used to synchronously map, dynamically update, and infer the virtual competition status of all participating users in the virtual competition scene based on the real GPS trajectories of the target user and the matched competition participants; the virtual competition status includes virtual vehicle posture, virtual track position, and competition interaction results.

[0006] In one possible implementation, the virtual world engine includes a coordinate transformation module and a scene state inference module; The coordinate transformation module is used to convert the real GPS trajectories of the target user and the matching competition participants into virtual track coordinates; The scenario state deduction module is used to perform scenario data synchronization mapping, dynamic updating and real-time deduction based on the virtual track coordinates of the target user and the matched competition participants, and update the virtual competition state.

[0007] In one possible implementation, the coordinate transformation module is specifically used for: The affine transformation is used to perform a coarse linear coordinate transformation on the real GPS trajectory to obtain coarsely matched track coordinates; The B-spline free deformation algorithm is used to perform nonlinear fine correction on the point transformation residuals of the coarse matching track coordinates to obtain the virtual track coordinates.

[0008] In one possible implementation, the system further includes an anti-cheating engine, which is used to: Multi-dimensional anomaly detection is performed on user cycling data, operating environment, and account association to obtain anomaly detection results; Based on the anomaly type of the anomaly detection result, perform corresponding review, data cleaning, illegal data interception, or account management operations.

[0009] In one possible implementation, the anti-cheating engine is specifically used for: When the deviation between physical speed and virtual speed exceeds the deviation threshold, the account is flagged and manual review is triggered. When the position difference between the current real GPS coordinates and the previous real GPS coordinates is greater than the sudden change threshold, the current real GPS coordinates are discarded. When it is detected that a user's terminal is running in an emulator environment, the user's eligibility to participate in the competition will be revoked, and the user's account will be banned. When the HMAC-SHA256 signature verification of a data frame fails, the data is rejected and discarded. When the user's cycling behavior pattern is analyzed by the LSTM neural network and abnormal features that deviate from the normal behavior distribution are identified, the anti-cheating detection threshold corresponding to that user is dynamically adjusted. When a score-boosting account is identified based on device fingerprint and IP address, a batch ban is performed on the score-boosting account and its associated accounts.

[0010] In one possible implementation, the user mobile app further includes a screen display module, which is used for: The virtual competition scene, real-time event data, and interface display elements are presented to the target user using a partitioned interface approach. The display module is also used to respond to perspective switching commands and switch between first-person and third-person perspectives in the virtual competition scene.

[0011] In one possible implementation, the real-time race data includes real-time rankings, remaining distance, and estimated completion time; the interface display elements include a speed dashboard, an energy bar, and an item bar.

[0012] In one possible implementation, the user mobile app further includes a comprehensive service module, which is used for: It enables functions such as checking match results, watching live matches, AI coaching, and virtual asset trading.

[0013] In one possible implementation, the user mobile app further includes a social module, which is used for: Enables real-time team formation, voice interaction, and friend management functions.

[0014] One vehicle includes the Internet of Things-based virtual interactive racing system for two-wheeled vehicles as described above.

[0015] Compared with the prior art, this application has the following beneficial effects: This application provides an IoT-based virtual interactive racing system and vehicle for two-wheeled vehicles. The system includes a user mobile app, an intelligent two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform. The user mobile app serves as the interaction entry point, providing users with options for three racing modes: single-player competition, team battles, and multiplayer free-for-all, via a built-in interactive control module. The intelligent two-wheeled vehicle terminal acts as the data acquisition end, simultaneously collecting the user's ELO score and full riding data after the user confirms participation, covering core dimensions such as vehicle motion parameters and geographical location information. The edge computing node performs pre-processing of the data, cleaning and filtering the raw riding data before outputting valid riding data. The cloud processing platform, as the core scheduling hub, intelligently matches opponents or teams using a matching module that combines the racing mode, valid riding data, and ELO score. A rendering module then generates corresponding virtual racing scenes based on racing rules, riding data, and user avatar configurations. Finally, a virtual world engine maps the virtual and real worlds based on the real GPS tracks of all participating users, synchronously updating and real-time simulating the vehicle posture, track position, and competitive interaction status of all users within the virtual scene, providing users with a complete real-time virtual riding racing service. This application enables real-time, simultaneous competition among cyclists, solving the problem of asynchronous interaction in traditional cycling software. Simultaneously, it constructs virtual cycling competition scenarios, enriching the forms of cycling competition and enhancing the enjoyment of cycling. Furthermore, relying on GPS trajectory linkage and analysis, this application breaks through geographical and route limitations, enabling immersive cross-regional cycling competition. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic diagram of the structure of a virtual interactive racing system for two-wheeled vehicles based on the Internet of Things provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of a control unit provided in an embodiment of this application; Figure 3 This is a schematic diagram of another control unit provided in an embodiment of this application. Detailed Implementation

[0018] To facilitate understanding of the technical solutions provided in the embodiments of this application, the background technology involved in the embodiments of this application will be described below.

[0019] With the continuous increase in the number of electric bicycles, electric scooters, and other two-wheeled electric vehicles, and the continuous iteration and evolution of IoT sensing and data interconnection technologies, the positioning of two-wheeled transportation has broken through the traditional scope of a means of transportation. Correspondingly, users' needs for two-wheeled riding have gradually extended from simply recording the riding process and storing exercise data to a comprehensive interactive experience that combines fun, social connectivity, and a sense of real-time competition.

[0020] Currently, mainstream sports applications on the market can only provide basic sports data storage, static leaderboard display, and lightweight asynchronous online challenge functions, which cannot meet the diversified experience needs of users after upgrades. Existing similar products have obvious limitations: First, the interaction mechanism mostly adopts an asynchronous challenge mode, which cannot support multiple cyclists to conduct real-time virtual competitions simultaneously, making it difficult to create an instant competitive atmosphere; Second, the competition evaluation dimensions are limited to the comparison of basic data such as cycling speed and mileage, lacking the support of gamified interaction design, resulting in a monotonous overall cycling interaction experience; Third, both offline and online events are limited by actual geographical space, mostly relying on designated physical routes and limited activity areas, and do not support simultaneous participation of users in different regions.

[0021] In summary, existing cycling sports applications have significant shortcomings in user experience and cannot effectively meet users' needs for immersive, real-time interconnected two-wheeled cycling interactive competition.

[0022] To address this issue, this application provides an IoT-based virtual interactive racing system for two-wheeled vehicles. This system comprises a user mobile app, a smart two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform working together. Users can select competition modes such as single-player competition, team battles, or multiplayer free-for-all through the app's interactive control module. After confirming participation, the smart two-wheeled vehicle terminal collects the user's riding data and ELO score in real time. The raw riding data is first transmitted to the edge computing node for preprocessing to obtain valid riding data. The cloud matching module combines the competition mode, valid riding data, and ELO score to match the user with other participants. Subsequently, the cloud rendering module builds a dedicated virtual racing scene for the corresponding mode based on the competition mode, valid riding data, and the virtual avatar configuration of all participating users. Simultaneously, the smart two-wheeled vehicle terminal collects the real GPS tracks of all participating users and sends them to the cloud virtual world engine for virtual-real mapping. This synchronously converts the real riding tracks into corresponding states within the virtual scene, dynamically updating and real-time predicting the virtual vehicle posture, virtual track position, and competitive interaction results of all participating users, ultimately achieving a complete cross-regional virtual riding racing experience. This application relies on an edge-cloud collaborative architecture to enable real-time virtual cycling competitions among users of similar skill levels across different regions. It transforms real cycling behavior into multi-dimensional virtual interactive content, breaking the limitations of traditional cycling software such as asynchronous competition, single data dimension, and geographical constraints, and providing users with an immersive, gamified, same-field battle experience.

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0024] See Figure 1 , Figure 1 This is a structural diagram of a virtual interactive racing system for two-wheeled vehicles based on the Internet of Things, provided as an embodiment of this application.

[0025] like Figure 1The system shown comprises four core components working together: a user mobile application (APP), an intelligent two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform. Each module has a clearly defined function and interconnected data links, enabling complete support for the entire process from user-initiated competition to real-time synchronization of competition status. The interactive control module is connected to both the intelligent two-wheeled vehicle terminal and the rendering module; the intelligent two-wheeled vehicle terminal is connected to both the edge computing nodes and the matching module; the edge computing nodes are connected to both the matching module and the rendering module; the matching module is also connected to the rendering module; the rendering module is also connected to the virtual world engine; and the virtual world engine is also connected to the intelligent two-wheeled vehicle terminal.

[0026] As the core entry point for user interaction with the system, the user's mobile app has a built-in interactive control module. Users can use this module to choose the competition mode they want to participate in. The system currently supports three different competition formats: 1v1 single-player competition, team battles (such as 3v3 team battles), and multiplayer free-for-all. This can adapt to the social and competitive needs of different users. Whether they want to challenge their scores alone, team up with friends, or participate in large-scale multiplayer competitions, they can complete the mode selection and participation confirmation through this module.

[0027] Once the user confirms the selected competition mode, the intelligent two-wheeled vehicle terminal used by the user will immediately respond to the competition command. The terminal is equipped with a main control MCU, a six-axis IMU, a Beidou / Global Positioning System (GPS) dual-mode positioning module, a 4G communication module, a Hall speed sensor, and a battery management system. Relying on the complete hardware configuration, it starts high-frequency data acquisition: on the one hand, it will collect full riding data that reflects the user's riding status in real time, covering vehicle motion parameters such as vehicle speed, acceleration, and heading angle, as well as vehicle geographical location information obtained based on Beidou / GPS dual-mode positioning; on the other hand, it will also simultaneously retrieve the corresponding user's Elo Rating System (ELO) competition score, which can objectively reflect the user's riding competition level and provide a core basis for subsequent fair matching.

[0028] To reduce the computational load on the cloud, minimize data transmission latency, and improve data validity, the raw riding data collected by the intelligent two-wheeled vehicle terminal is not directly uploaded to the cloud. Instead, it is first transmitted to edge computing nodes for preprocessing. The edge computing nodes perform a series of processes on the raw riding data, including outlier removal, noise filtering, and data compression. This removes invalid data caused by signal fluctuations and sensor errors, ultimately outputting accurate and usable riding data. The preprocessed data is then encrypted and transmitted to the cloud processing platform, providing a high-quality data foundation for subsequent cloud processing.

[0029] The cloud processing platform is the core scheduling hub of the entire system. Its matching module receives three core pieces of information: the user's selected competition mode, pre-processed valid riding data, and the user's ELO rating. Based on a multi-dimensional matching algorithm, it matches the user with the most suitable competition participants. In single-player competition mode, it matches the user with opponents of similar skill levels. In team battle mode, it forms teams of comparable strength based on the principle of balanced ratings. In multiplayer free-for-all mode, it completes the grouping and matching of multiple users, ensuring the fairness and competitiveness of the competition from the root.

[0030] After matching participating users, the cloud-based rendering module initiates the construction of the virtual scene. This module combines the current competition mode rules, all participating users' valid riding data, and each user's pre-set virtual avatar configuration information to generate a customized virtual competition scene highly adapted to the competition mode. Different competition modes correspond to different track designs, scene atmospheres, and interaction rules, providing users with a differentiated visual and competitive experience. During the competition, all participating users' smart two-wheeled vehicle terminals continuously collect their real GPS tracks and simultaneously upload them to the cloud-based virtual world engine.

[0031] The virtual world engine is the core carrier for achieving virtual-real interaction. Based on the real GPS tracks of all participating users, it completes high-precision virtual-real coordinate mapping, synchronously translating users' real-world cycling behavior into corresponding actions within the virtual competition scene. Simultaneously, it dynamically updates and simulates the virtual competition status of all participating users in real time, including the virtual vehicle's driving posture, its real-time position on the virtual track, and the results of competitive interactions such as item interactions and position changes between users. This allows users in different geographical locations to obtain an immersive experience completely consistent with offline competition within the same virtual scene.

[0032] In one possible implementation, the virtual world engine used to achieve virtual-real interaction in the entire system adopts a layered and modular design architecture. The virtual world engine has two core units: a coordinate transformation module and a scene state inference module. The two work together to complete the transformation and synchronization from real riding behavior to virtual competitive state. The coordinate transformation module is connected to both the intelligent two-wheeled vehicle terminal and the scene state inference module; the scene state inference module is also connected to the rendering module.

[0033] The coordinate transformation module is the core component for enabling cross-regional competition. It receives the real GPS tracks of the target user and all matched participants, and through standardized coordinate mapping logic, converts the latitude and longitude coordinates of users in different geographical locations in the real physical world into virtual track coordinates within the same virtual competition scene. This breaks down the limitations of real geographical space, allowing users scattered across different locations to synchronously map their cycling positions onto the same virtual track, providing a unified location benchmark for cross-regional competition. After completing the virtual-real coordinate transformation, the scene state simulation module synchronizes the competition data across the entire scene based on the virtual track coordinates of all participating users. It dynamically updates the corresponding data within the scene based on the users' real-time cycling changes and simulates various state changes throughout the competition process. Ultimately, it synchronously updates the virtual competition status of all users within the virtual scene, allowing all participants to perceive the positional changes and competitive dynamics of their opponents in real time, achieving an immersive experience completely consistent with offline real-world competition.

[0034] In one possible implementation, in the specific implementation of this system, such as Figure 2 As shown, the coordinate transformation module adopts a two-step high-precision mapping scheme of linear coarse matching + nonlinear fine correction to ensure the transformation accuracy from real GPS trajectory to virtual track coordinates. The specific implementation logic is as follows: First, the coordinate transformation module performs a coarse linear coordinate transformation on the collected real GPS track using an affine transformation algorithm. Relying on four basic linear transformations—scaling, translation, rotation, and shearing—it quickly aligns the latitude and longitude track in the real geographic coordinate system to the overall coordinate system of the virtual track, obtaining coarsely matched track coordinates. This step can quickly complete the overall coordinate alignment over a large area, ensuring basic conversion efficiency.

[0035] Building upon this foundation, the module further utilizes the B-spline Free-Form Deformation (FFD) algorithm to perform nonlinear fine-tuning of the point transformation residuals in the coarse-matched track coordinates. For local deformations and point offset errors that linear transformations cannot accommodate, the free-form deformation capability of B-splines is used for refined point adjustments, eliminating local mapping deviations and ultimately obtaining high-precision virtual track coordinates. This approach balances transformation efficiency and mapping accuracy, achieving centimeter-level alignment between virtual and real coordinates, providing a precise positional basis for subsequent real-time synchronous simulations of the competitive state.

[0036] In one possible implementation, to ensure the fairness of virtual cycling competitions and prevent cheating from disrupting the competition order and user experience, this system also includes an independent anti-cheating engine as a core guarantee module for competition fairness. The coordinate transformation module is connected to both the intelligent two-wheeled vehicle terminal and the scene state inference module; the scene state inference module is also connected to the rendering module.

[0037] This anti-cheating engine performs multi-dimensional anomaly detection and verification: it logically verifies the user-uploaded cycling data, identifying abrupt data changes, abnormal trajectories, and motion parameters that do not conform to the logic of real cycling. Simultaneously, it detects the user's terminal operating environment, investigating abnormal operating environments such as emulators and data tampering tools. Furthermore, it investigates account associations, identifying illegal account behaviors such as multi-account collaborative cheating and proxy account activities, outputting complete anomaly detection results through multi-dimensional cross-detection.

[0038] After outputting the anomaly detection results, the anti-cheating engine will take corresponding actions according to the type and severity of the anomaly: for suspected minor anomalies, a second review will be initiated for confirmation; for non-malicious anomalies such as data noise, data cleaning and correction will be performed; for confirmed cheating and violation data, it will be directly blocked and not included in the competition settlement; and for accounts with serious or malicious violations, corresponding account control measures will be implemented to ensure the fairness and impartiality of virtual cycling competitions throughout the entire process.

[0039] In one possible implementation, the anti-cheating engine of this system sets up multi-dimensional and hierarchical precise detection and handling rules for various cheating risks in cycling competition scenarios, covering the entire chain of cheating prevention and control, including data, trajectory, environment, signature, behavior, and account: The engine first performs a consistency check on riding data, comparing the user's actual physical riding speed with the virtual speed synchronized with the virtual scene in real time. When the deviation exceeds a threshold (e.g., 15%), it indicates a risk of data tampering. The engine will automatically flag the corresponding account and trigger manual review, balancing detection accuracy and user experience. Simultaneously, it performs a continuity check on the GPS track, comparing the difference between the actual GPS coordinates at adjacent moments. When the instantaneous speed corresponding to a change in location exceeds a sudden change threshold (e.g., 50 m / s), it determines that the GPS data at that moment has a jump or is falsified, and directly removes the abnormal coordinates to prevent abnormal data from interfering with the race settlement.

[0040] To combat environment-related cheating, the engine identifies the user's terminal's operating environment. If the engine detects that the terminal is running in a simulator environment, it will immediately disqualify the user from the competition and ban their account, thus preventing cheating using simulated data. At the same time, all uploaded cycling data frames will undergo keyed-hash message authentication code (HMAC-SHA256) signature verification. If the signature verification fails, it means that the data transmission has been tampered with, and the engine will directly refuse to receive and discard the corresponding data, ensuring the integrity and authenticity of the uploaded data.

[0041] Furthermore, the engine is equipped with intelligent behavior risk control and batch cheating prevention capabilities: it learns and analyzes users' riding behavior patterns through a Long Short-Term Memory (LSTM) neural network. When it identifies abnormal features that deviate from the normal distribution of user behavior, it dynamically raises the detection threshold for that user, improving the sensitivity of detecting high-risk users. At the same time, it performs account association analysis based on device fingerprints and Internet Protocol Addresses (IP addresses). After identifying groups of cheating accounts that are accumulating points in bulk, it performs batch bans on the accounts that are accumulating points and all associated accounts, comprehensively combating all kinds of cheating behaviors and ensuring a fair and just competitive environment.

[0042] In one possible implementation, the user's mobile app also includes a built-in screen display module, which is connected to the rendering module, such as... Figure 3 As shown, this module adopts a partitioned layout interface design, presenting various information about virtual competitions to the user in different areas, while also supporting perspective switching: The display module divides the content into three categories: virtual racing scenes, real-time race data, and interface elements. The real-time race data includes real-time rankings, remaining distance, and estimated completion time. The interface elements include a speed dashboard, energy bar, and item inventory, all clearly presented through this partitioned layout. The virtual racing scene corresponds to the core main area of ​​the interface. This area is used to render the 3D virtual racing environment, presenting the user's virtual riding vehicle, track scene and overall racing atmosphere. It is the core visual area for users to view the racing process. The real-time race data interface displays information in the following sections: The top left real-time ranking panel displays the rankings and position differences of all participating users; the top right area displays core race progress data such as remaining mileage and estimated completion time; and the bottom left speed and energy dashboard displays the user's current riding speed and vehicle's remaining energy status. All race-related dynamic data are updated synchronously in the corresponding sections. The interface elements correspond to the interactive item area on the right. This area contains interactive function buttons such as accelerators and shields, which are user-triggerable interface interactive elements that allow users to initiate item interactions during the competition.

[0043] Viewpoint switching function: There is a viewpoint switching entry at the top of the interface. The screen display module can respond to the user's viewpoint switching command, allowing users to freely switch between first-person riding view and third-person global view in the virtual competition scene to adapt to different visual experience preferences.

[0044] In one possible implementation, in addition to the core virtual competition interaction functions, the user's mobile app also has a built-in comprehensive service module. This comprehensive service module is connected to the cloud processing platform to provide users with supporting extended services throughout the entire competition process, covering various usage needs before and after the competition. This module supports a battle record query function, which allows users to view their historical competition records, battle results, ranking changes, and ability growth data, clearly understanding their own cycling competition level changes and battle performance. It also provides a live viewing function, allowing users to watch real-time competitions of high-level users and watch official events, learning competitive skills while also satisfying their viewing needs.

[0045] Meanwhile, the integrated service module also features an artificial intelligence (AI) coaching function, which is suitable for users to practice alone when there is no matched opponent. Users can choose AI opponents of different difficulty levels for competitive training and gradually improve their cycling competition ability.

[0046] In addition, the integrated service module also supports virtual asset trading. Users can exchange and trade virtual assets such as virtual cycling avatars, racing props, and personalized track skins within this module to meet users' needs for personalized racing outfits and experiences.

[0047] In a possible implementation, in order to strengthen the social attribute of cycling competitions and enhance the interactive experience of users, the user mobile APP also has a built-in social module. The social module is connected to the cloud processing platform to provide users with the social interaction ability throughout the entire process of the competition: This module supports the real-time team formation function. Users can directly invite friends on the platform to form a competition team and jointly participate in the competition in the team confrontation mode. They can also initiate a temporary team recruitment in the matching interface and quickly form a team with unfamiliar users with the same needs to participate in the competition.

[0048] At the same time, the user mobile APP also has a voice interaction function. During the competition, users in the same team can start real-time voice communication to communicate battle tactics and synchronize the cycling status, greatly enhancing the cooperation degree and on-site interaction sense of the team battle.

[0049] In addition, the user mobile APP also provides a friend management function, supporting users to add cycling enthusiasts as friends on the platform. Users can view the competition status and historical records of their friends and can also initiate a competition invitation to their friends at any time to help users build a dedicated cycling competition social circle.

[0050] In addition, the embodiment of the present application also provides a vehicle, which includes the above-mentioned Internet of Things-based two-wheeled electric vehicle virtual interaction competition system.

[0051] This application relies on the collaborative architecture of the terminal, edge node and cloud to achieve the global linkage processing of cycling data. By real-time matching users with the same level of participation, it breaks the interaction limit of asynchronous comparison of traditional cycling software and creates an on-site competition atmosphere of real-time head-to-head battles. At the same time, this application relies on the cloud rendering module to build an independent virtual competition scene, transforming cycling behaviors into multi-dimensional competition interaction content such as virtual vehicle postures and track positions, getting rid of the limitation of single speed and mileage data comparison, and enriching the gamification experience of cycling competitions. In addition, this application completes cross-regional data synchronization deduction based on the real GPS trajectories of users, without relying on physical fixed cycling routes, breaking the geographical space constraints of offline competitions, and meeting the cross-regional immersive real-time cycling competition interaction needs of users.

[0052] The above has introduced in detail a kind of Internet of Things-based two-wheeled electric vehicle virtual interaction competition system provided by this application. Each embodiment in the specification is described in a progressive manner, and the key points of each embodiment are the differences from other embodiments. The same and similar parts among the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0053] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A virtual interactive racing system for two-wheeled vehicles based on the Internet of Things, characterized in that, The system includes a user mobile app, an intelligent two-wheeled vehicle terminal, edge computing nodes, and a cloud processing platform. The user mobile app includes an interactive control module. The cloud processing platform includes a matching module, a rendering module, and a virtual world engine. The interactive control module is connected to both the intelligent two-wheeled vehicle terminal and the rendering module. The intelligent two-wheeled vehicle terminal is connected to both the edge computing nodes and the matching module. The edge computing nodes are connected to both the matching module and the rendering module. The matching module is also connected to the rendering module. The rendering module is also connected to the virtual world engine. The virtual world engine is also connected to the intelligent two-wheeled vehicle terminal. The interactive control module is used to receive the competition mode selected by the target user; the competition mode includes single-player competition, team battle, or multiplayer free-for-all. The intelligent two-wheeled vehicle terminal, in response to the competition mode selected by the target user, is used to collect the target user's riding data and ELO score in real time; the riding data includes vehicle motion parameters and vehicle geographical location information. The edge computing node is used to preprocess the cycling data to obtain valid cycling data; The matching module is used to match the target user with competition participants based on the competition mode, the valid cycling data, and the ELO score; the competition participants include suitable opponents or opposing teams. The rendering module is used to construct a virtual competition scene adapted to the competition mode based on the competition mode, the valid cycling data, and the virtual avatar configuration information of the target user and the matching competition participants. The intelligent two-wheeled vehicle terminal is also used to acquire the real GPS trajectories of the target user and the matching competition participants; The virtual world engine is used to synchronously map, dynamically update, and infer the virtual competition status of all participating users in the virtual competition scene based on the real GPS trajectories of the target user and the matched competition participants; the virtual competition status includes virtual vehicle posture, virtual track position, and competition interaction results.

2. The system according to claim 1, characterized in that, The virtual world engine includes a coordinate transformation module and a scene state inference module; the coordinate transformation module is connected to the intelligent two-wheeled vehicle terminal and the scene state inference module respectively; the scene state inference module is also connected to the rendering module; The coordinate transformation module is used to convert the real GPS trajectories of the target user and the matching competition participants into virtual track coordinates; The scenario state deduction module is used to perform scenario data synchronization mapping, dynamic updating and real-time deduction based on the virtual track coordinates of the target user and the matched competition participants, and update the virtual competition state.

3. The system according to claim 2, characterized in that, The coordinate transformation module is specifically used for: The affine transformation is used to perform a coarse linear coordinate transformation on the real GPS trajectory to obtain coarsely matched track coordinates; The B-spline free deformation algorithm is used to perform nonlinear fine correction on the point transformation residuals of the coarse matching track coordinates to obtain the virtual track coordinates.

4. The system according to claim 1, characterized in that, The system also includes an anti-cheating engine, which is connected to the intelligent two-wheeled vehicle terminal. The anti-cheating engine is used for: Multi-dimensional anomaly detection is performed on user cycling data, operating environment, and account association to obtain anomaly detection results; Based on the anomaly type of the anomaly detection result, perform corresponding review, data cleaning, illegal data interception, or account management operations.

5. The system according to claim 4, characterized in that, The anti-cheating engine is specifically used for: When the deviation between physical speed and virtual speed exceeds the deviation threshold, the account is flagged and manual review is triggered. When the position difference between the current real GPS coordinates and the previous real GPS coordinates is greater than the sudden change threshold, the current real GPS coordinates are discarded. When it is detected that a user's terminal is running in an emulator environment, the user's eligibility to participate in the competition will be revoked, and the user's account will be banned. When the HMAC-SHA256 signature verification of a data frame fails, the data is rejected and discarded. When the user's cycling behavior pattern is analyzed by the LSTM neural network and abnormal features that deviate from the normal behavior distribution are identified, the anti-cheating detection threshold corresponding to that user is dynamically adjusted. When a score-boosting account is identified based on device fingerprint and IP address, a batch ban is performed on the score-boosting account and its associated accounts.

6. The system according to claim 1, characterized in that, The user mobile app also includes a screen display module, which is connected to the rendering module. The screen display module is used for: The virtual competition scene, real-time event data, and interface display elements are presented to the target user using a partitioned interface approach. The display module is also used to respond to perspective switching commands and switch between first-person and third-person perspectives in the virtual competition scene.

7. The system according to claim 6, characterized in that, The real-time race data includes real-time rankings, remaining distance, and estimated completion time; the interface display elements include a speed dashboard, energy bar, and item bar.

8. The system according to claim 1, characterized in that, The user mobile app also includes a comprehensive service module, which is connected to the cloud processing platform. The comprehensive service module is used for: It enables functions such as checking match results, watching live matches, AI coaching, and virtual asset trading.

9. The system according to claim 1, characterized in that, The user mobile app also includes a social module, which is connected to the cloud processing platform. The social module is used for: Enables real-time team formation, voice interaction, and friend management functions.

10. A vehicle, characterized in that, The vehicle includes the Internet of Things-based virtual interactive racing system for two-wheeled vehicles as described in any one of claims 1-9.

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