Automatic notification method and system for beidou alarm of visual recognition based non-api docking truck

Abstract

The application discloses a visual recognition-based API non-connection truck Beidou alarm automatic notification method and system, belongs to the technical field of Beidou alarm, and aims at solving the problems of difficult API connection and high cost of a Beidou platform, and comprises the following steps: collecting real-time images of the interface of a Beidou monitoring platform by using a visual recognition technology, recognizing and extracting vehicle license plates, alarm types, specific speed limit violation values and fatigue driving time lengths; taking the extracted vehicle license plate as a unique search identifier, matching a corresponding driver mobile phone number in a pre-established database; generating a standardized early warning instruction based on an effective alarm, and calling an arbitrary available third-party cloud communication service interface; and according to the early warning instruction, automatically sending an SMS early warning containing alarm information to the relevant driver, so that the automation degree and real-time performance of truck Beidou alarm notification are improved.

Description

Technical Field

[0001] This invention relates to the field of Beidou alarm technology, specifically to a method and system for automatic notification of Beidou alarms for trucks without API integration based on visual recognition. Background Technology

[0002] In recent years, the nationwide mandatory installation of Beidou vehicle-mounted terminals on freight vehicles has enabled them to connect to Beidou vehicle dynamic monitoring platforms at all levels, achieving real-time monitoring and alarms for risky behaviors such as speeding, fatigued driving, offline driving, and crossing boundaries. In accordance with road transport safety supervision requirements, alarm information generated by the platform must be promptly detected by monitoring personnel and manually notified to the driver, thereby eliminating safety hazards in a timely manner. Existing mainstream alarm notification methods all rely on API integration, port opening, protocol parsing, or direct database connection with the Beidou monitoring platform to obtain raw alarm data.

[0003] However, in actual promotion and use, the following obvious defects exist: Strict platform access permissions and extremely high API integration difficulty; Due to data security, management compliance, and platform control requirements, official BeiDou monitoring platforms generally do not open API interfaces, communication ports, and data interaction permissions to third-party systems, making it difficult for most transportation companies and third-party security service providers to legally obtain alarm data and achieve automated notifications; High integration costs, poor compatibility, and complex maintenance; BeiDou platform protocols vary across different regions and operators, requiring customized development and on-site debugging for integration. Later platform version upgrades can easily lead to integration failures, requiring companies to continuously invest manpower and resources for maintenance; Low efficiency and high risk of missed or delayed reports; Relying on dedicated monitoring personnel to manually check, dial, or send SMS messages is prone to omissions and delays when there are many vehicles and dense alarms, failing to meet the requirements for 24 / 7 real-time early warning; Complete inability to automate in scenarios without interfaces; In scenarios where data integration is impossible, such as outdated platforms, closed platforms, or platforms without permissions, companies can only rely on manual monitoring, unable to achieve automated and intelligent alarm reminders, severely impacting the efficiency of transportation safety management.

[0004] To address the above issues, a method and system for automatic notification of BeiDou alarms for trucks without API integration based on visual recognition is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a visual recognition-based automatic notification method and system for BeiDou alarms on trucks without API integration. By using this device, the problems of difficult API integration, poor compatibility, and high cost of the BeiDou platform mentioned above are solved.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for automatic notification of BeiDou alarms for trucks without API integration based on visual recognition, the method comprising: Without API integration, data interaction, port connection, or any form of data exchange with the Beidou vehicle dynamic monitoring platform, visual recognition technology is used to acquire real-time images of the Beidou monitoring platform's interface, identify and extract vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving duration; the visual recognition technology covers all visual, image processing, and pattern recognition methods that can acquire alarm information from the platform interface. Using the extracted vehicle license plate number as a unique retrieval identifier, the corresponding driver's mobile phone number is matched in a pre-established database; The system verifies the validity and completeness of the acquired alarm information, filters out duplicate alarms and missing data, generates standardized early warning instructions based on valid alarms, and calls any available third-party cloud communication service interface; the third-party cloud communication service interface includes all cloud service platforms that can realize SMS sending and voice call functions; Based on the warning instruction, an SMS warning containing alarm information is automatically sent to the relevant driver, and an automatic voice call reminder is initiated simultaneously; at the same time, the license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result are stored both locally and in the cloud.

[0007] Furthermore, visual recognition technology is used to acquire real-time images of the Beidou monitoring platform interface, identify and extract vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving durations, including: Using computer vision and image processing algorithms, screenshots and video streams were analyzed from the real-time early warning interface and alarm record page of the Beidou monitoring platform. The system extracts key information such as vehicle license plate number, alarm type, specific speeding value, and duration of fatigue driving. This process does not involve data interaction with the BeiDou platform; it only relies on visual recognition technology to parse the content displayed on the interface.

[0008] Furthermore, using the extracted vehicle license plate number as a unique retrieval identifier, the corresponding driver's mobile phone number is matched within a pre-established database, including: The extracted license plate number is used as a unique retrieval identifier to search for the corresponding driver's mobile phone number in a pre-established local and cloud database; Through an efficient indexing mechanism and a precise data matching algorithm, we ensure that driver information corresponding to the alarm vehicle is obtained quickly and accurately.

[0009] Furthermore, the acquired alarm information is validated for validity and completeness, duplicate alarms and missing data are filtered out, standardized warning instructions are generated based on valid alarms, and any available third-party cloud communication service interface is invoked, including: The communication module is highly compatible and scalable, and can seamlessly connect to various third-party cloud communication service interfaces, including but not limited to SMS sending platforms and voice call services; Upon receiving the alarm information and the corresponding driver's contact information, a standardized warning instruction is generated, and a notification is prepared to be sent to the driver via a cloud communication service interface.

[0010] Furthermore, it automatically sends SMS alerts containing alarm information to relevant drivers and simultaneously initiates automatic voice call reminders, including: Automatically send SMS alerts containing detailed alarm information to relevant drivers via cloud communication service interface; Simultaneously initiate automatic voice call reminders to ensure that drivers can receive alarm notifications in a timely manner.

[0011] Furthermore, before automatically sending a text message containing alarm information to the relevant driver based on the aforementioned warning instruction, the method also includes: Monitor the operational status of dedicated monitoring personnel; When dedicated monitoring personnel do not intervene manually, an automatic notification process will be executed; this method is only an auxiliary tool for dedicated monitoring personnel and does not replace their legally mandated manual monitoring responsibilities.

[0012] Furthermore, before using visual recognition technology to acquire real-time images of the interface of the Beidou monitoring platform, the following steps are also included: Adaptive learning is performed on the interface layout and display style of the Beidou monitoring platform; By using intelligent image processing and pattern recognition algorithms, the recognition parameters are adjusted to accurately extract alarm information from different platform versions.

[0013] Furthermore, after generating standardized early warning instructions, it also includes: Listen for the availability status of third-party cloud communication service interfaces; When a specific communication service interface fails, the warning command will be rerouted to a backup cloud communication service interface.

[0014] Furthermore, it also includes: After receiving confirmation from the driver, a notification completion log is generated; The notification completion log is associated with and stored with the original alarm information for subsequent statistical analysis.

[0015] This invention also discloses another technical solution: a visual recognition-based, API-free automatic alarm notification system for trucks using BeiDou navigation, the system comprising: The visual recognition acquisition module, without API interface, data interaction, port connection or any form of data exchange with the Beidou vehicle dynamic monitoring platform, uses visual recognition technology to collect vehicle license plate, alarm type, specific speeding value and fatigue driving duration from the Beidou platform interface. The license plate number matching module uses the extracted vehicle license plate number as a unique retrieval identifier to match the corresponding driver's mobile phone number in a pre-established database; The early warning command generation module verifies the validity and completeness of the acquired alarm information, filters out duplicate alarms and missing data, generates standardized early warning commands based on valid alarms, and calls any available third-party cloud communication service interface. The automatic notification execution module, based on the warning instruction, automatically sends a text message warning containing alarm information to the relevant driver and simultaneously initiates an automatic voice call reminder; The dual data storage module stores license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result both locally and in the cloud.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention can obtain alarm information by visually recognizing and collecting interface images without any API interface, port connection, data interaction, or protocol interoperability with the Beidou platform. It is still usable in scenarios where traditional technologies cannot be implemented, such as closed platforms, outdated platforms, and platforms without authorization, and has extremely strong applicability. 2. No need to apply for interfaces, no need for custom development, no need to debug communication protocols. It can be put into operation simply by visually collecting data from the existing monitoring computer interface, which greatly reduces the deployment and maintenance costs for enterprises. Small and medium-sized freight enterprises can also use it easily. 3. It can adaptively learn the interface layout and display style of the Beidou monitoring platform, automatically adjust the recognition parameters, and stably adapt to Beidou monitoring platforms of different regions, versions and interface styles, without becoming ineffective with platform upgrades; 4. Verify the validity and completeness of alarm information, automatically filter duplicate alarms and incomplete data, generate standardized warning instructions, avoid false alarms and random alarms, and ensure that the notification content is true and accurate; adopt a dual-link notification method of SMS warning plus automatic voice call push, which greatly improves the driver's reception rate; at the same time, it supports automatic switching of third-party communication interfaces, and routes to the backup channel in case of failure to ensure that the notification is not interrupted. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the steps of the present invention. Figure 2 This is a system architecture diagram of the present invention. Detailed Implementation

[0018] 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 the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: As Figure 1 As shown, this embodiment provides a visual recognition-based automatic notification method for truck Beidou alarms without API integration, including: Step 101: Without API integration, data interaction, port connection, or any form of data exchange with the Beidou vehicle dynamic monitoring platform, use visual recognition technology to collect real-time images of the Beidou monitoring platform interface, identify and extract vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving duration; visual recognition technology covers all visual, image processing, and pattern recognition methods that can acquire alarm information from the platform interface. Step 102: Using the extracted vehicle license plate number as the unique retrieval identifier, match the corresponding driver's mobile phone number in the pre-established database; Step 103: Verify the validity and completeness of the acquired alarm information, filter out duplicate alarms and information with missing data, generate standardized early warning instructions based on valid alarms, and call any available third-party cloud communication service interface; the third-party cloud communication service interface includes all cloud service platforms that can realize SMS sending and voice call functions; Step 104: Based on the warning instruction, automatically send a text message warning containing alarm information to the relevant driver and simultaneously initiate an automatic voice call reminder; at the same time, store the license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result both locally and in the cloud.

[0020] The above solution, without relying on BeiDou platform APIs, ports, protocols, or data interaction, completes alarm information collection, parsing, matching, and automatic notification solely through visual recognition. This solves the problems of difficult access permissions, high deployment costs, and inability to use closed platforms in traditional methods. It improves alarm accuracy through validity verification and deduplication mechanisms; increases reach through SMS + voice dual-link notifications; and achieves full-process traceability through local + cloud dual storage. This significantly improves the real-time performance and coverage of truck alarm notifications while ensuring regulatory compliance.

[0021] In some embodiments, visual recognition technology is used to acquire real-time images of the Beidou monitoring platform interface, identify and extract vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving duration, including: Using computer vision and image processing algorithms, screenshots and video streams were analyzed from the real-time early warning interface and alarm record page of the Beidou monitoring platform. The system extracts key information such as vehicle license plate number, alarm type, specific speeding value, and duration of fatigue driving. This process does not involve data interaction with the BeiDou platform; it only relies on visual recognition technology to parse the content displayed on the interface.

[0022] Specifically, this step involves capturing frame-by-frame images of the BeiDou monitoring platform's display interface using a desktop image acquisition component. The acquisition process only reads pixel data from the display cache, without initiating network requests, reading or writing platform files, injecting programs, or calling system interfaces; there is no data interaction with the BeiDou platform. After acquiring the interface image, it is first converted to grayscale to reduce computational interference. Then, Gaussian filtering is used to remove screen reflections, moiré patterns, and noise caused by ambient light, improving image clarity. Next, edge detection algorithms are used to locate text and data areas within the interface, distinguishing different areas such as panel titles, vehicle lists, alarm prompts, and status labels. Suspected license plate numbers, alarm text areas, and numerical display areas are then segmented separately. Optical character recognition (OCR) is used to parse each segmented area character by character, converting pixel information into text information. Keyword matching rules are then used to filter out alarm type text such as license plate numbers, speeding, fatigue driving, offline status, and fence crossing, as well as alarm-related speed and time values, completing the extraction and structured organization of all key information.

[0023] In some embodiments, the extracted vehicle license plate number is used as a unique retrieval identifier to match the corresponding driver's mobile phone number in a pre-established database, including: The extracted license plate number is used as a unique retrieval identifier to search for the corresponding driver's mobile phone number in a pre-established local and cloud database; Through an efficient indexing mechanism and a precise data matching algorithm, we ensure that driver information corresponding to the alarm vehicle is obtained quickly and accurately.

[0024] Specifically, before the system runs, a vehicle information database is pre-built, recording the license plate numbers, driver names, mobile phone numbers, fleet affiliations, and responsible person information of all freight vehicles within the company's jurisdiction. This forms a standardized, structured dataset, which is simultaneously stored in a local embedded database and a cloud server database, enabling rapid local retrieval and cloud backup redundancy. During data matching, the license plate number string output by visual recognition is used as the search keyword. A constructed hash index structure quickly locates the corresponding record in the database. The indexing mechanism converts the license plate number characters into fixed-length index values, achieving millisecond-level location. To address potential confusion caused by similar characters in character recognition, the system sets fault-tolerant matching rules. It compares easily confused numbers and letters for similarity, automatically correcting individual error bits when the overall character count is consistent, preventing matching failures due to single-character recognition errors. After matching, the mobile phone number field in the corresponding entry is read, and the mobile phone number is bound to the license plate number and alarm information, providing a target address for subsequent warning notifications.

[0025] In some embodiments, the acquired alarm information is validated for validity and completeness, duplicate alarms and missing data are filtered out, standardized warning instructions are generated based on valid alarms, and any available third-party cloud communication service interface is invoked, including: The communication module is highly compatible and scalable, and can seamlessly connect to various third-party cloud communication service interfaces, including but not limited to SMS sending platforms and voice call services; Upon receiving the alarm information and the corresponding driver's contact information, a standardized warning instruction is generated, and a notification is prepared to be sent to the driver via a cloud communication service interface.

[0026] Specifically, the validity check is divided into field integrity check and logical rationality check. The system checks in turn whether the license plate number is empty, whether it conforms to the vehicle license plate coding rules, whether the alarm type is within the preset legal type range, whether the speeding value is within the reasonable range of 0 to 150 kilometers per hour, and whether the fatigue driving duration is a valid value greater than 0. If any item fails to meet the requirements, it is directly marked as invalid information and discarded. After the validity check is completed, the duplicate alarm filtering process begins. The system reads the historical alarm records within the most recent time period from the local cache, compares the current alarm's license plate number and alarm type with the historical records one by one, and calculates the time interval between the two records. If the license plate number and alarm type are completely consistent and the time interval is less than the set filtering threshold, it is determined to be a duplicate alarm and will not proceed to the next process. After the verification and filtering are completed, the system combines all valid information according to a fixed format to generate a structured warning instruction containing the license plate number, alarm type, specific value, and trigger time. The system has a built-in unified communication adaptation layer to convert the warning instruction into request parameters that conform to the third-party interface specifications, realizing universal access to various SMS platforms and voice call platforms without the need to redevelop code for different service providers.

[0027] In some embodiments, based on a warning instruction, an SMS warning containing alarm information is automatically sent to the relevant driver, and an automatic voice call reminder is simultaneously initiated, including: Automatically send SMS alerts containing detailed alarm information to relevant drivers via cloud communication service interface; Simultaneously initiate automatic voice call reminders to ensure that drivers can receive alarm notifications in a timely manner.

[0028] Specifically, the system concatenates the content of the warning instruction into SMS text according to a preset template. The template includes the license plate number, alarm type, specific value, and safety reminder content. After concatenation, the system assembles the request message according to the protocol specifications of the third-party SMS interface and sends it to the SMS gateway via the network protocol. The gateway then completes the final delivery. Simultaneously with the SMS sending, the system initiates a voice notification task in parallel, converting the text information in the warning instruction into voice stream data. The system generates a playable audio file through the voice synthesis module and then calls the voice call interface to initiate a call to the target mobile phone number. Once the call is connected, the synthesized alarm voice is automatically played. The SMS notification and voice call notification adopt an asynchronous parallel execution mode. The two channels are independent of each other, do not wait for each other, and do not block each other. Even if one channel is delayed or fails, the other channel can still deliver normally, thereby significantly improving the arrival rate and timeliness of alarm notifications.

[0029] In some embodiments, before automatically sending a text message warning containing alarm information to the relevant driver according to the warning instruction, the method further includes: Monitor the operational status of dedicated monitoring personnel; When dedicated monitoring personnel do not intervene manually, an automatic notification process will be executed; this method is only an auxiliary tool for dedicated monitoring personnel and does not replace their legally mandated manual monitoring responsibilities.

[0030] Specifically, the system uses an input device monitoring module to collect real-time operation information such as mouse movement, mouse clicks, and keyboard key presses. Simultaneously, it monitors page switching, record marking, pop-up operations, and manual entry of processing results on the BeiDou monitoring platform, classifying these actions as manual intervention by dedicated monitoring personnel. When the system identifies a valid alarm, it does not immediately execute an automatic notification but initiates a fixed-duration wait timer, continuously monitoring for any manual intervention. If, before the timer expires, it detects that a monitoring personnel has viewed, marked, registered, responded to, or processed the alarm, it is determined that the alarm has been manually taken over, and the system automatically terminates the current automatic notification process to avoid repeated alerts. If no manual intervention is detected after the wait timer expires, the system continues with subsequent automatic notification processes, ensuring that the automation function serves only as a supplementary auxiliary means to manual monitoring, fully complying with the legal requirements for dedicated monitoring personnel to perform their duties in road transport safety supervision.

[0031] In some embodiments, before using visual recognition technology to acquire real-time images of the BeiDou monitoring platform interface, the method further includes: Adaptive learning is performed on the interface layout and display style of the Beidou monitoring platform; By using intelligent image processing and pattern recognition algorithms, the recognition parameters are adjusted to accurately extract alarm information from different platform versions.

[0032] Specifically, during the initialization phase, the system automatically enters an adaptive learning process, continuously acquiring multiple frames of images from the BeiDou monitoring platform interface. It comprehensively extracts features from the interface's regional distribution, font style, character color, background tone, table borders, alarm indicator positions, and list arrangement, forming a feature set for the current interface. Subsequently, the extracted interface features are compared with multiple built-in standard templates for similarity calculation, matching the closest template type from BeiDou platform templates from different regions, versions, and operators. Based on the matching results, the system automatically adjusts key visual recognition parameters, including character recognition area range, image binarization threshold, character segmentation step size, keyword matching dictionary, and effective area coordinate range, ensuring the recognition logic perfectly aligns with the current platform's interface structure. In the event of subsequent platform upgrades or interface redesigns, the system can restart the adaptive learning process, automatically updating recognition parameters and ensuring continuous and stable operation without manual intervention.

[0033] In some embodiments, after generating standardized warning instructions, the method further includes: Listen for the availability status of third-party cloud communication service interfaces; When a specific communication service interface fails, the warning command will be rerouted to a backup cloud communication service interface.

[0034] Specifically, the system maintains real-time status monitoring of the primary communication interface through a heartbeat detection mechanism. Lightweight test requests are sent to the primary interface at fixed time intervals, and interface availability is comprehensively judged based on request response time, connection status, return status code, and call success rate. If the primary interface experiences a failure state such as connection timeout, server abnormality, return error code, service suspension due to unpaid fees, or traffic restrictions, the system immediately initiates a routing switch mechanism. The system repackages the currently pending warning command according to the protocol specifications of the backup interface and automatically switches to the preset backup communication interface for transmission. The switching process is fully automated, requiring no manual operation and ensuring no loss of alarm information. This guarantees that warning commands can still be delivered normally even if any communication channel is abnormal, improving the overall reliability and stability of the system.

[0035] In some embodiments, it also includes: After receiving confirmation from the driver, a notification completion log is generated; The notification completion log is associated with and stored with the original alarm information for subsequent statistical analysis.

[0036] Specifically, the system monitors driver feedback in real time, including SMS replies, call connection status, voice broadcast completion markers, and platform confirmation receipts. When the system receives a driver's reply via a specified feedback command, a successful call connection and voice broadcast, and a successful confirmation from the platform, it marks the notification as confirmed. Based on the feedback information, the system generates a notification completion log containing the feedback time, method, notification channel, sending result, and receiving status. This log entry is uniquely linked to the original alarm information, license plate number, driver information, alarm time, and warning content, forming a complete closed-loop data chain. All data is simultaneously written to both a local database file and a cloud database for dual storage. The system supports searching, filtering, exporting, and report generation by time, license plate number, alarm type, and notification status, providing complete and verifiable data for enterprise safety management, regulatory verification, and accountability.

[0037] Example 2: Please refer to Figure 2 As shown, based on Embodiment 1, this embodiment also provides a visual recognition-based automatic notification system for truck Beidou alarms without API integration, including: The visual recognition acquisition module 201 is used to collect vehicle license plate numbers, alarm types, specific speeding values ​​and fatigue driving durations from the Beidou platform interface without API interface, data interaction, port connection and any form of data exchange with the Beidou vehicle dynamic monitoring platform. The license plate number matching module 202 is used to match the corresponding driver's mobile phone number in a pre-established database using the extracted vehicle license plate number as the unique retrieval identifier. The early warning instruction generation module 203 is used to verify the validity and completeness of the acquired alarm information, filter out duplicate alarms and missing data, generate standardized early warning instructions based on valid alarms, and call any available third-party cloud communication service interface. The automatic notification execution module 204 is used to automatically send SMS warnings containing alarm information to relevant drivers based on the warning instructions, and simultaneously initiate automatic voice call reminders. The dual data storage module 205 is used to store the license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result both locally and in the cloud.

[0038] In summary, this invention achieves seamless collection and analysis of BeiDou alarm information through pure visual recognition technology. Under the core condition of completely avoiding API integration, data interaction, port connections, and any form of data exchange with the BeiDou vehicle dynamic monitoring platform, it automates the entire process of alarm information extraction, driver information matching, warning command generation, automatic notification via SMS and voice dual links, and dual storage of local and cloud data. This invention fundamentally eliminates dependence on the BeiDou platform's open permissions, communication protocols, and data interfaces, effectively solving a series of technical problems inherent in traditional technologies, such as high API integration barriers, difficult permission applications, poor platform compatibility, high deployment costs, and inapplicability to closed systems. Simultaneously, through mechanisms such as information validity verification, duplicate alarm filtering, compatibility with manual monitoring status, and automatic communication interface switching, it ensures the accuracy, timeliness, and regulatory compliance of alarm notifications. Through dual notification channels, dual storage mechanisms, and adaptive interface learning, it significantly improves the system's stability, adaptability, and data traceability across different platforms and environments. It provides freight companies with a low-cost, easy-to-deploy, comprehensive, compliant, and secure BeiDou alarm automatic notification solution, possessing strong practicality and broad promotional value.

[0039] It should 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 process, method, article, or apparatus.

[0040] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for automatic notification of BeiDou alarms for trucks without API integration based on visual recognition, characterized in that: The method includes: Without API integration, data interaction, port connection, or any form of data exchange with the Beidou vehicle dynamic monitoring platform, visual recognition technology is used to acquire real-time images of the Beidou monitoring platform's interface, identify and extract vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving durations; the visual recognition technology covers all visual, image processing, and pattern recognition methods that can acquire alarm information from the platform interface. Using the extracted vehicle license plate number as a unique retrieval identifier, the corresponding driver's mobile phone number is matched in a pre-established database; The system verifies the validity and completeness of the acquired alarm information, filters out duplicate alarms and missing data, generates standardized early warning instructions based on valid alarms, and calls any available third-party cloud communication service interface; the third-party cloud communication service interface includes all cloud service platforms that can realize SMS sending and voice call functions; Based on the warning instruction, an SMS warning containing alarm information is automatically sent to the relevant driver, and an automatic voice call reminder is initiated simultaneously; at the same time, the license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result are stored both locally and in the cloud.

2. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, The Beidou monitoring platform uses visual recognition technology to acquire images of its interface in real time, identifying and extracting vehicle license plate numbers, alarm types, specific speeding values, and fatigue driving durations, including: Using computer vision and image processing algorithms, screenshots and video streams were analyzed from the real-time early warning interface and alarm record page of the Beidou monitoring platform. The system extracts key information such as vehicle license plate number, alarm type, specific speeding value, and duration of fatigue driving. This process does not involve data interaction with the BeiDou platform; it only relies on visual recognition technology to parse the content displayed on the interface.

3. The method for automatic notification of Beidou alarms for trucks without API integration based on visual recognition according to claim 1, characterized in that, Using the extracted vehicle license plate number as a unique retrieval identifier, the corresponding driver's mobile phone number is matched within a pre-established database, including: The extracted license plate number is used as a unique retrieval identifier to search for the corresponding driver's mobile phone number in a pre-established local and cloud database; Through an efficient indexing mechanism and a precise data matching algorithm, we ensure that driver information corresponding to the alarm vehicle is obtained quickly and accurately.

4. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, The acquired alarm information is validated for validity and completeness, and duplicate alarms and missing data are filtered out. Based on valid alarms, standardized warning commands are generated, and any available third-party cloud communication service interface is invoked, including: The communication module is highly compatible and scalable, and can seamlessly connect to various third-party cloud communication service interfaces, including but not limited to SMS sending platforms and voice call services; Upon receiving the alarm information and the corresponding driver's contact information, a standardized warning instruction is generated, and a notification is prepared to be sent to the driver via a cloud communication service interface.

5. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, Based on the aforementioned warning instruction, an SMS warning containing alarm information is automatically sent to the relevant driver, and an automatic voice call reminder is simultaneously initiated, including: Automatically send SMS alerts containing detailed alarm information to relevant drivers via cloud communication service interface; Simultaneously initiate automatic voice call reminders to ensure that drivers can receive alarm notifications in a timely manner.

6. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, Before automatically sending a text message containing alarm information to the relevant driver according to the aforementioned warning instruction, the process also includes: Monitor the operational status of dedicated monitoring personnel; When dedicated monitoring personnel do not intervene manually, an automatic notification process will be executed; this method is only an auxiliary tool for dedicated monitoring personnel and does not replace their legally mandated manual monitoring responsibilities.

7. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, Before using visual recognition technology to acquire real-time images of the interface of the Beidou monitoring platform, the following steps are also included: Adaptive learning is performed on the interface layout and display style of the Beidou monitoring platform; By using intelligent image processing and pattern recognition algorithms, the recognition parameters are adjusted to accurately extract alarm information from different platform versions.

8. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 4, characterized in that, After generating standardized warning instructions, it also includes: Listen for the availability status of third-party cloud communication service interfaces; When a specific communication service interface fails, the warning command will be rerouted to a backup cloud communication service interface.

9. The method for automatic notification of Beidou alarm for trucks without API interface based on visual recognition according to claim 1, characterized in that, Also includes: After receiving confirmation from the driver, a notification completion log is generated; The notification completion log is associated with and stored with the original alarm information for subsequent statistical analysis.

10. A visual recognition-based automatic notification system for BeiDou-based truck alarms without API docking, used to implement the visual recognition-based automatic notification method for BeiDou-based truck alarms without API docking as described in any one of claims 1-9, characterized in that, The system includes: The visual recognition acquisition module, without API interface, data interaction, port connection or any form of data exchange with the Beidou vehicle dynamic monitoring platform, uses visual recognition technology to collect vehicle license plate, alarm type, specific speeding value and fatigue driving duration from the Beidou platform interface. The license plate number matching module uses the extracted vehicle license plate number as a unique retrieval identifier to match the corresponding driver's mobile phone number in a pre-established database; The early warning command generation module verifies the validity and completeness of the acquired alarm information, filters out duplicate alarms and missing data, generates standardized early warning commands based on valid alarms, and calls any available third-party cloud communication service interface. The automatic notification execution module, based on the warning instruction, automatically sends a text message warning containing alarm information to the relevant driver and simultaneously initiates an automatic voice call reminder; The dual data storage module stores license plate number, alarm type, speeding value, fatigue duration, driver contact information, notification time and notification result both locally and in the cloud.

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