Low-delay Bluetooth group communication system and communication method in physical education scene

Abstract

The invention provides a low-delay Bluetooth group communication system and communication method in a physical education scene. Belongs to the technical field of Bluetooth communication. The method comprises the steps that a two-dimensional code on a bracelet is scanned through a physical education special APP, after the APP reads two-dimensional code information, service data are issued to the bracelet, initialization binding of the bracelet is completed, and an initialized bracelet list is generated; dynamically grouping the student bracelets participating in the same physical education course according to the initialized bracelet list; in the data transmission process, a batch ACK mechanism is adopted to generate batch ACK packets, and the ACK packets are sent back to the bracelets through Bluetooth broadcast; and sending and receiving the batch ACKs, and marking the corresponding data packets to be in an uploaded state after the bracelet receives the batch ACKs. Through a subpackage sending mechanism, the problem of Bluetooth transmission byte limitation is effectively solved, complete transmission of heart rate, motion data and the like is ensured, data loss is avoided, and the accuracy and integrity of the data are ensured.

Description

TECHNICAL FIELD

[0001] The application provides a low-delay Bluetooth group communication system and communication method in a sports teaching scene, and belongs to the technical field of Bluetooth communication. BACKGROUND

[0002] In the sports teaching scene, especially in the one-to-many teaching mode (such as one sports teacher simultaneously teaching multiple students), it is necessary to collect the movement data (such as heart rate, skipping rope times, running speed, etc.) of each student in real time and accurately.

[0003] However, the traditional Bluetooth communication mode needs to be paired first, and then communication can be performed; when facing multiple devices and high real-time requirements, there are problems such as high delay, poor reliability, and easy to be disturbed, which cannot meet the needs of the sports teaching scene, so it is particularly important to develop a Bluetooth connection mode that does not need to be paired in advance, multiple parties simultaneously start Bluetooth scanning and broadcasting, and bidirectional communication is performed on different channels. SUMMARY

[0004] The application provides a low-delay Bluetooth group communication system and communication method in a sports teaching scene, which solves the problems mentioned in the background art.

[0005] The application provides a low-delay Bluetooth group communication method in a sports teaching scene, which comprises the following steps:

[0006] S1, scanning the two-dimensional code on the bracelet through a sports teaching special APP, the APP reads the two-dimensional code information, and then sends service data to the bracelet to complete the initialization binding of the bracelet and generate an initialized bracelet list;

[0007] S2, according to the initialized bracelet list, dynamically grouping the student bracelets participating in the same sports course; in the data transmission process, a batch ACK mechanism is adopted to generate a batch ACK packet and send it back to each bracelet through Bluetooth broadcasting; the sending and receiving of the batch ACK are performed, and after the bracelet receives the batch ACK, the corresponding data packet is marked as an uploaded state;

[0008] S3, before the data transmission starts, the bracelet and the APP perform adaptive negotiation of the Bluetooth protocol version, determine the highest Bluetooth protocol version supported by both parties, and adjust the byte limit and transmission rate of the data transmission according to the protocol version; according to the negotiation result, a data transmission strategy suitable for the current Bluetooth protocol version is generated;

[0009] S4, in the data transmission process, filtering the data packets of non-target bracelets through a logical isolation technology, and at the same time, using a feature verification mechanism to verify the received data packets to generate an effective data list after logical isolation and feature verification;

[0010] S5, the PAD displays the motion data of each student in real time according to the valid data list, and reports the collected data to the server for storage and analysis, to generate a real-time motion data display interface and a data analysis report.

[0011] The low-delay Bluetooth group communication system in the sports teaching scene comprises:

[0012] one or more processors;

[0013] a memory for storing one or more programs,

[0014] wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of the above.

[0015] The application has the advantages that: the packet sending mechanism effectively solves the Bluetooth transmission byte limit problem, ensures complete transmission of heart rate, motion data and the like, avoids data loss, and guarantees the accuracy and integrity of data; meanwhile, the added message confirmation (ACK) mechanism greatly improves the reliability of data transmission, makes data collection more accurate; the ACK mechanism is optimized for the one-to-many scene in class, a batch ACK mode is adopted, 1 ACK packet is broadcasted by being regularly summarized and combined, the number of instruction interactions is reduced, unnecessary overhead and delay are reduced, real-time performance is improved, data feedback in the sports class is more timely and efficient; the negotiation process is designed considering the Bluetooth version difference of student mobile phones, the bracelet can encapsulate data according to different versions, and the adaptability of the scheme is enhanced; moreover, the APP judges the identity of uploaded data, avoids uploading of data of others, and guarantees the compliance of business data. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a method step diagram of the application;

[0017] Figure 2 is a Bluetooth initialization schematic diagram of the application;

[0018] Figure 3 is a data transmission schematic diagram in a course;

[0019] Figure 4 is a protocol transmission process schematic diagram; DETAILED DESCRIPTION

[0020] The preferred embodiments of the application are described below in combination with the drawings, and it should be understood that the preferred embodiments described herein are only used for describing and explaining the application, and are not used for limiting the application.

[0021] One embodiment of the application is as follows: Figure 1As shown, a low-latency Bluetooth group communication method in a physical education teaching scenario includes:

[0022] S1. Scan the QR code on the wristband using the dedicated physical education teaching APP. The QR code contains information such as the wristband model, serial number, and manufacturer code. After reading the QR code information, the APP sends business data to the wristband. The business data includes the wristband's unique school identifier and MAC address, completing the initial binding of the wristband. Figure 2 As shown, an initialized list of wristbands is generated, which contains information such as the school's unique identifier, MAC address, and binding status of each wristband;

[0023] S2. Based on the initialized wristband list, dynamically group the wristbands of students participating in the same physical education course; during data transmission, a batch ACK mechanism is adopted, that is, the PAD (or teacher's handheld device) periodically summarizes all wristband data received within a certain period of time, generates a batch ACK packet, the batch ACK packet contains multiple message sequence numbers and device identifiers, and sends it back to each wristband via Bluetooth broadcast; batch ACK is sent and received, and after receiving a batch ACK, the wristband marks the corresponding data packet as uploaded, such as... Figure 3 As shown, this reduces the number of individual ACK transmissions and communication latency;

[0024] S3. Before data transmission begins, the wristband and the app conduct adaptive negotiation on the Bluetooth protocol version to determine the highest Bluetooth protocol version supported by both parties (such as BEL4.2, BEL5.0, or BEL5.3), and adjust the byte limit and transmission rate of data transmission according to the protocol version. During data transmission, the wristband can broadcast the latest data without waiting for the PAD's ACK, and the PAD generates batch ACKs periodically for confirmation. Based on the negotiation results, a data transmission strategy adapted to the current Bluetooth protocol version is generated. The data transmission strategy includes parameters such as data packet size and transmission frequency.

[0025] S4. During data transmission, data packets from non-target wristbands are filtered out using logical isolation technology to reduce the reception and processing of invalid data. At the same time, a feature verification mechanism is used to verify the received data packets to prevent interference from other Bluetooth devices (such as Bluetooth headsets). A list of valid data after logical isolation and feature verification is generated, which contains valid exercise data uploaded by each wristband (such as heart rate, number of rope skips, running speed, etc.).

[0026] S5 and PAD display each student's exercise data in real time based on the valid data list, allowing physical education teachers to monitor and guide them. At the same time, the collected data is reported to the server for storage and analysis, generating a real-time exercise data display interface and data analysis reports. Physical education teachers can adjust their teaching strategies based on this data and reports.

[0027] The working principle and effects of the above technical solution are as follows:

[0028] Teachers no longer need to manually check wristband numbers and enter device information one by one using a form. They can simply scan the wristband's QR code with the app to automatically complete the binding and generate a wristband list. The entire class's device preparation can be completed in just a few minutes, and it also avoids binding failures caused by manually entering the wrong MAC address. This improves the efficiency of wristband binding before class and reduces manual operation costs and the probability of errors.

[0029] During physical education class, dozens of students' wristbands transmit data simultaneously. The PAD does not need to send a confirmation message to each wristband individually. Instead, it periodically aggregates the data and sends a batch ACK packet. This avoids the channel being filled by a large number of ACK packets and allows the teacher to see the students' heart rate and number of jump ropes in real time. It also prevents the data from taking a long time to be displayed, reduces group communication latency, and reduces the transmission overhead of the Bluetooth channel.

[0030] Whether it's the old BEL4.2 wristbands previously purchased by the school or the newly equipped BEL5.3 wristbands, they can automatically negotiate a suitable protocol version with the APP, and will also adjust the packet size and transmission frequency according to the version. There is no need to replace the wristband because the device version is not consistent, which also reduces data packet loss and lag caused by version incompatibility, enhances device compatibility, and improves the stability of data transmission.

[0031] Students often wear Bluetooth headsets and smartwatches on the playground. Logical isolation can filter out data from other classes' wristbands, and feature verification can also block signals from these irrelevant devices, preventing invalid data from occupying PAD resources. This ensures that teachers see only the real exercise data of students in the current class, improving the accuracy of exercise data and reducing interference from external devices.

[0032] Teachers can see each student's heart rate changes in real time through the PAD. For example, if a student's heart rate is found to be too high, they can immediately ask him to stop and rest. The data analysis report after class can also help teachers review the effectiveness of the course, such as adjusting the intensity of the running class to make the teaching more in line with the students' actual situation, improving the pertinence of teaching guidance and reducing the risks of exercise.

[0033] In one embodiment of the present invention, S1 includes:

[0034] S11. Activate the wristband binding module of the dedicated sports teaching APP, call the device camera to scan the binding QR code on the wristband surface; use the APP's built-in QR code parsing engine to extract the core information encapsulated in the QR code, including the wristband model (type field, such as B4), wristband serial number (sn field, such as 2004A001FD4081002144) and manufacturer code (m field, hexadecimal format), and generate the wristband original information parsing table;

[0035] S12. The APP uses the serial number and manufacturer code from the original information parsing table of the bracelet as request parameters to call the bracelet binding API of the backend server; the server verifies the legality of the serial number (such as verifying the matching relationship between the manufacturer code and the serial number), generates a unique school identifier (2 bytes, supporting 65535 device identifiers) and a bracelet MAC address (6 bytes, used for Bluetooth communication and positioning) for the bracelet, and returns these two types of business data to the APP to generate a bracelet business data allocation table;

[0036] S13. The APP, based on the Bluetooth broadcast mechanism, packages the school's unique identifier and MAC address from the wristband's business data allocation table according to the protocol format (message type is set to 1, and the data content follows the {data type}{data length}{data} structure, such as 0x00 (MAC address type) + 0x06 (length) + 08:00:20:0A:8C:6D (MAC value)), and broadcasts it to the target wristband via Bluetooth; the wristband enables passive scanning mode to receive and temporarily store the business data sent by the APP.

[0037] S14. The wristband performs a validity check on the received business data. The validity check includes: first, checking the consistency between the MAC address and its own hardware MAC address; second, checking the format of the school's unique identifier (which must be a 2-byte unsigned integer). If the check passes, the wristband stores the school's unique identifier and MAC address in the local flash memory to prevent data loss in case of power failure, and generates an ACK response packet (message type set to 101, data content empty, message sequence number consistent with the sequence number of the command issued by the APP), and broadcasts it back to the APP via Bluetooth.

[0038] S15. After receiving the ACK response from the wristband, the APP marks the wristband binding status as activated and enters its information (school unique identifier, MAC address, binding time, and wristband model, etc.) into a table to generate an initialized wristband list. The initialized wristband list allows teachers to filter target wristbands by course later.

[0039] The working principle and effects of the above technical solution are as follows:

[0040] The app automatically extracts core information such as the model and serial number of the wristband by scanning the QR code. Teachers no longer need to manually enter the serial number of each wristband. The information collection of a wristband can be completed in just over ten seconds. It also avoids subsequent binding failures caused by manually entering long serial numbers incorrectly, thus improving the efficiency of wristband information collection and reducing manual input errors.

[0041] The server verifies the matching relationship between the serial number and the manufacturer's code. Only compliant campus-purchased wristbands can generate a unique school identifier and MAC address to prevent unauthorized wristbands from accessing the teaching system, avoid interfering with normal teaching data transmission, enhance device access security, and reduce the infiltration of illegal wristbands.

[0042] The APP packages the school identifier and MAC address according to a fixed protocol of data type + length + content. The wristband passively scans and receives the data, which will not cause the wristband to fail to recognize the data due to the chaotic data format. This ensures the accurate delivery of business data, improves the standardization of business data delivery, and reduces format incompatibility issues.

[0043] The wristband verifies the received MAC address and identifier format, and stores it in local flash memory after verification. Even if the wristband is powered off, the data will not be lost, avoiding the impact of subsequent communication on usage due to data errors or loss. This ensures the accuracy and durability of data storage and reduces the risk of data loss.

[0044] The generated list of initialized wristbands will indicate their binding status. Teachers can then directly filter for activated wristbands by course without having to check each wristband individually to see if it is bound. This saves pre-class preparation time, improves equipment preparation efficiency, and reduces the time teachers spend filtering wristbands.

[0045] In one embodiment of the present invention, S13 includes:

[0046] The APP reads the wristband business data allocation table, extracts the school unique identifier (2 bytes) and MAC address (6 bytes) of the wristband to be bound, organizes them according to the data type-data content correspondence (e.g., MAC address corresponds to data type 0x00, school unique identifier corresponds to data type 0x01), generates a list of business data to be packaged, and clarifies the type, length and content of each data item;

[0047] According to the Bluetooth communication protocol, the APP packages data into a message type + data segment structure: the message type is fixed at 1 (bound to the business data identifier), and the data segment follows the format {data type}{data length}{data} (e.g., the MAC address is packaged as 0x00+0x06+08:00:20:0A:8C:6D, and the school's unique identifier is packaged as 0x01+0x02+corresponding value); after packaging, a 1-byte check bit is added (for preliminary data integrity checking) to generate a business data broadcast packet.

[0048] The APP starts the Bluetooth module and configures the broadcast parameters: the broadcast power is set to medium (to ensure stable reception within 10 meters and adapt to the wristband binding scenario), the broadcast interval is set to 500ms (to improve the wristband reception probability), and the target device filter is set to unbound wristbands (preliminary filtering by Bluetooth name); after configuration, a Bluetooth broadcast configuration parameter table is generated, and the parameter ready status before sending is confirmed.

[0049] Based on the Bluetooth broadcast configuration parameter table, the APP starts the Bluetooth broadcast function and sends business data broadcast packets in a loop (3 loops by default to avoid loss in a single transmission); at the same time, it records information such as broadcast start time, data packet length and number of loops, and generates a business data broadcast delivery log.

[0050] The target wristband maintains a passive scanning mode (low power state, only receiving Bluetooth broadcasts). When a broadcast packet containing message type 1 is scanned, the data in the packet is extracted and temporarily stored in the local temporary buffer (RAM) to avoid occupying flash memory resources. After temporary storage is completed, the reception time and data packet size are recorded to generate a wristband business data reception temporary storage record.

[0051] The working principle and effects of the above technical solution are as follows:

[0052] The data is organized into a list to be packaged according to the data type and content correspondence. The type and length of each field are clearly defined. Then, the data is packaged according to a fixed protocol to avoid problems such as mixed data and missing fields. For example, the MAC address and the school's unique identifier will not be unrecognizable by the wristband due to format confusion. This improves the standardization of data packaging and reduces the failure to send data due to format errors.

[0053] Adding a 1-byte check bit after packaging can initially check whether the data is damaged during transmission. This avoids the need to wait for the wristband to receive the data to discover that it is incomplete, thus preventing duplicate transmissions caused by data corruption in advance, saving communication time, enhancing the integrity of data transmission, and reducing the risk of data corruption.

[0054] When configuring Bluetooth parameters, unpaired wristbands are filtered out, and the power is controlled within 10 meters. This ensures stable reception in paired scenarios and prevents other paired wristbands or irrelevant devices from receiving the signal from a distance. It also reduces the invalid occupation of Bluetooth channels, improves the targeting of broadcasts, and reduces interference from irrelevant devices.

[0055] By default, the system sends business data broadcast packets 3 times in a loop, eliminating the need for teachers to manually retry. Even if a broadcast is not received due to signal interference, the subsequent two broadcasts can be retransmitted, avoiding binding delays caused by single-transmission loss, reducing the probability of data transmission loss, and improving the wristband's reception success rate.

[0056] The band maintains a passive scanning mode, only receiving broadcast packets of message type 1, without actively searching for devices. Moreover, the data is temporarily stored in RAM instead of flash memory, reducing hardware power consumption and preventing the band from rapidly consuming power due to frequent flash memory reads and writes or active scanning. This saves the band's resources and extends its battery life.

[0057] In one embodiment of the present invention, S2 includes:

[0058] S21. Teachers select the current course type (e.g., running class, jump rope class) and class information in the APP on the PAD (or teaching-specific device). The APP calls the list of initialized wristbands, filters out wristbands that are active and whose class matches the current course; divides the wristbands into independent groups according to course type (e.g., running class for class A is the running group, jump rope class for class B is the jump rope group), generates a course-wristband group mapping table, and performs logical isolation of wristbands for different courses;

[0059] S22. The PAD, based on the course-wristband group mapping table, broadcasts a group identifier instruction (message type set to 3, data content includes course type code and group unique identifier) ​​to the wristbands of the target group. After receiving the instruction, the wristband verifies the consistency between the group unique identifier and its own group. If they match, it switches to intra-group communication mode and returns a group joining confirmation packet (containing its own school's unique identifier). The PAD summarizes the confirmation information and updates the group wristband online status table, such as... Figure 4 As shown;

[0060] S23. Teachers issue exercise mode commands via PAD (e.g., running mode is coded as 2, and jump rope mode is coded as 3). After receiving the command, the wristbands in the group start the training mode and actively broadcast exercise data at a frequency of 1 time / second (e.g., running data includes cadence and heart rate, and jump rope data includes number of times and heart rate). The data format follows the school's unique identifier + battery level + timestamp + data group structure. The PAD starts continuous passive scanning, receives and caches the broadcast data of all wristbands in the group, and generates a real-time wristband data cache table.

[0061] S24. PAD sets the batch aggregation period (default 1 second, can be adjusted as needed). After each period, it extracts the message sequence number of unconfirmed data and the school's unique identifier of the corresponding wristband from the real-time wristband data cache table, and packages them into batch ACK packets according to the protocol format (a single ACK packet can contain the identifiers and serial numbers of 77 devices to reduce transmission overhead). PAD sends the batch ACK packets to all wristbands in the group via Bluetooth broadcast, and updates the data confirmation status table at the same time.

[0062] S25. After receiving a batch of ACK packets, the wristband extracts the school's unique identifier from the packet and compares it with itself. If they match, it reads the corresponding message sequence number and marks the data with that sequence number stored locally as uploaded. If the wristband does not receive an ACK confirmation for a certain data within 3 summary cycles, it triggers a retransmission mechanism to rebroadcast the unacknowledged data to ensure that the data is not lost and generates a wristband data upload status report.

[0063] The working principle and effects of the above technical solution are as follows:

[0064] The wristbands are grouped and logically isolated according to course type. For example, the wristbands for running class and jump rope class are in separate groups. This prevents running data from class A from being mixed with jump rope data from class B. Teachers do not need to filter out irrelevant information when viewing the data, which reduces data interference from wristbands of different courses and improves the relevance of data transmission.

[0065] The PAD confirms the online status of the wristband by using group identification commands. It can update the online list in real time, avoid repeatedly sending commands to offline wristbands, save Bluetooth channel resources, enhance the clarity of device status within the group, and reduce invalid communication of offline devices.

[0066] The wristband actively broadcasts data once per second, and the PAD continuously receives and caches the data. Teachers can see students' heart rate, cadence, and other dynamics in a timely manner without having to wait a long time for the data to be refreshed, which improves the real-time performance of exercise data and reduces the delay in teachers obtaining data.

[0067] Batch ACK packets can process confirmation information from 77 devices at once, eliminating the need to send an ACK to each wristband individually. This reduces channel occupancy, avoids congestion caused by sending ACK packets when dozens of people are in class, reduces Bluetooth communication overhead, and improves group communication efficiency.

[0068] If the wristband does not receive an ACK within 3 cycles, it will retransmit. Even if the signal is weak and the transmission fails occasionally, it can be retransmitted, which will prevent the problem of missing student exercise data, reduce the probability of loss of exercise data, and ensure data integrity.

[0069] In one embodiment of the present invention, S24 includes:

[0070] The PAD reads the system's preset batch aggregation period (default 1 second) and allows teachers to manually adjust the period value via the APP (range 0.5-3 seconds); it generates a batch ACK period configuration table based on the configured period parameters. The batch ACK period configuration table includes the period duration, effective time, and applicable group information, which serves as the time benchmark for data aggregation.

[0071] At the end of each aggregation period, the PAD calls the real-time wristband data cache table, filters out unconfirmed records by the data confirmation status field, extracts the message sequence number of each record and the school's unique identifier for the corresponding wristband, and generates a detailed list of unconfirmed data.

[0072] The PAD packages the unacknowledged data details list according to the Bluetooth communication protocol format: the packet header is set to 0xAA (indicating the batch ACK type), the data area is arranged in the structure of school unique identifier (2 bytes) + message sequence number (4 bytes) (a single packet can hold a maximum of 77 groups of data, if it exceeds the limit, it will be split into multiple packets), and a CRC check code (2 bytes) is added to the end of the packet; after packaging, a batch ACK data packet is generated;

[0073] The PAD activates the Bluetooth broadcast module to broadcast batch ACK data packets to the target address of the group (based on the course-wristband group mapping table); and records the sending timestamp, number of data packets and target group identifier during the sending process to generate a batch ACK sending log.

[0074] After the PAD completes the broadcast, it marks the records in the unacknowledged data details list as having sent ACKs and updates the data acknowledgment status table synchronously. The data acknowledgment status table includes information such as the ACK sending time and the corresponding data packet number.

[0075] The working principle and effects of the above technical solution are as follows:

[0076] Teachers can adjust the aggregation period according to the number of students or the amount of data, instead of being stuck at a fixed 1 second. This adapts to the real-time needs of different teaching scenarios, improves the flexibility of period configuration, and reduces the limitations of using fixed periods.

[0077] Only unconfirmed data is filtered and packaged to avoid including confirmed data repeatedly. A single package can hold 77 sets of device information, without having to split into too many small packages, saving packaging time, improving the packaging accuracy of batch ACKs, and reducing redundant data overhead.

[0078] Adding a CRC checksum to the end of the packet can quickly detect whether the data transmission is corrupted, without waiting for feedback from the wristband to find the problem. This reduces the situation of repeated transmission due to data errors, enhances the transmission integrity of batch ACKs, and reduces retransmissions caused by data errors.

[0079] Group-based targeted broadcasting only sends batch ACKs to the wristbands of the current course, preventing other classes or irrelevant devices from receiving them. This avoids the channel being filled with invalid data, ensures smooth data transmission of sports data, reduces the occupancy rate of the Bluetooth channel, and reduces interference from irrelevant devices.

[0080] The data confirmation status table is updated in real time, marking records that have been acknowledged. This eliminates the need for repeated verification when querying data later, reducing the operational costs for teachers or the system, improving the clarity of data status, and reducing subsequent repetitive processing.

[0081] In one embodiment of the present invention, step S3 includes:

[0082] S31. Before data transmission, the wristband starts the protocol negotiation mode and sends a protocol capability report via Bluetooth broadcast. The report includes: supported Bluetooth protocol versions (BEL4.2 / BEL5.0 / BEL5.3), the maximum transmission bytes for each version (e.g., 31 bytes for BEL4.2 and 255 bytes for BEL5.0), and the hardware-supported transmission frequency (1-5 times / second). After receiving the report, the APP stores it in the wristband's protocol capability database.

[0083] S32. The APP reads the Bluetooth protocol versions it supports (such as the protocol versions encapsulated by Android / iOS systems), combines them with the supported versions of the bracelet in the bracelet protocol capability database, and determines the target protocol version by taking the highest compatible version (e.g., if the APP supports BEL5.0 and the bracelet supports BEL5.3, then the target version is BEL5.0); at the same time, it calculates the effective transmission bytes under this version (the bytes occupied by the system protocol need to be deducted, such as the actual effective bytes of BEL5.0 are 235 bytes), and generates a protocol version determination result table;

[0084] S33. Based on the protocol version determination result table, the APP generates a data transmission parameter configuration instruction, which includes: target protocol version, single data packet size (e.g., BEL4.2 not exceeding 27 bytes, BEL5.0 not exceeding 235 bytes), and broadcast frequency (default 1 time / second, which can be increased to 2 times / second when real-time requirements are high). The APP sends the instruction to the wristband via Bluetooth broadcast, and the wristband returns a parameter confirmation ACK after receiving it.

[0085] S34. The wristband, based on the data transmission parameter configuration instructions, formulates data packetization rules. The data packetization rules are as follows: if a single piece of exercise data (such as running data containing two sets of heart rate) exceeds the packet size, it is split according to timestamp + data segment identifier + data content format (e.g., splitting a 500-byte piece of data into three 235-byte packets, labeled as segment 1 / 3, segment 2 / 3, and segment 3 / 3); the wristband performs packetization pre-rehearsal using local simulated data to verify the correctness of the packetization logic and generates a packetization pre-rehearsal report;

[0086] S35. After the wristband completes parameter configuration and packet rehearsal, it switches to the no-wait broadcast mode: without waiting for the PAD's ACK confirmation, it directly broadcasts the latest unuploaded data (including complete data or packet data) at the frequency specified in the data transmission parameter configuration command; the PAD receives data at the same frequency, buffers it in the real-time data buffer, and generates batch ACKs after the aggregation period arrives, and performs broadcast-reception parallel processing.

[0087] The working principle and effects of the above technical solution are as follows:

[0088] The wristband actively reports the supported protocol versions and transmission capabilities. The APP combines its own supported versions and selects the highest compatibility value. For example, the old BEL4.2 wristband and the new BEL5.3 wristband can communicate normally with the APP without having to replace the device due to version issues. This improves the protocol compatibility between devices and reduces communication failures caused by version incompatibility.

[0089] Precisely configure packet size and broadcast frequency according to protocol version to avoid wasting space by transmitting small data in large packets, or frequently splitting large data due to packets being too small, thereby improving channel utilization, enhancing the adaptability of data transmission parameters, and reducing the waste of transmission resources.

[0090] By splitting massive amounts of data into smaller chunks using packet segmentation rules and combining this with fragment identifiers, PADs can be completely assembled, preventing transmission failures due to excessively large single packets. This is especially suitable for data transmission of running data containing multiple heart rate sets, reducing the probability of failure in large data transmissions and improving data integrity.

[0091] The wristband adopts a no-wait broadcast mode, which sends new data without waiting for the PAD to confirm. With the PAD receiving data in parallel, the movement data of dozens of students can be displayed on the PAD in seconds. Teachers can see the changes in students' status in time, reducing data transmission latency and improving real-time performance.

[0092] The broadcast frequency can be adjusted as needed. Jump rope classes with high real-time requirements can refresh the number of times faster, while ordinary running classes can maintain the regular frequency to save power, which enhances the flexibility of the transmission strategy and adapts to different teaching needs.

[0093] In one embodiment of the present invention, step S4 includes:

[0094] S41, PAD generates logical isolation rules based on the course-wristband grouping mapping table. The isolation rules are as follows: first, filtering by the school's unique identifier range (e.g., for the running group, the wristband identifier is 0001-0050, and only data within this range is received); second, filtering by course type encoding (e.g., for the jump rope course, only data packets of jump rope data type are received). PAD embeds these rules into the Bluetooth receiving module to automatically intercept data packets that do not match the rules.

[0095] S42. After receiving the Bluetooth data packet, PAD performs feature verification. The feature verification specifically includes: first, verifying whether the service_uuid is a fixed value 0xa390 (a proprietary identifier agreed upon by the protocol); and second, verifying the feature field (67 for the wristband and 69 for the APP). If either verification fails (e.g., the Bluetooth headset data packet does not have the 0xa390 identifier), the data packet is directly discarded, and an invalid data interception log is generated.

[0096] S43. For data packets that pass the feature verification, the PAD parses their data content and performs a second verification according to the protocol format. The second verification specifically includes: first, verifying the consistency between the message type and the course requirements (e.g., the running course only accepts running data type (message type 3)); second, verifying the validity of the timestamp (it must be within ±5 minutes of the current course time); and third, verifying the range of data values ​​(e.g., heart rate must be between 30-220 beats / minute, and the number of jump ropes must be a non-negative integer). Data that fails the verification is marked as abnormal data and temporarily stored in the abnormal data pending review table.

[0097] S44 and PAD categorize the data that has passed the format verification according to the unique school identifier of the wristband, extract the core information of each data (such as timestamp, heart rate value, number of rope skips, and step frequency), and associate it with the student name in the initialized wristband list to generate a list of valid data details; at the same time, abnormal data is reviewed (such as the teacher confirming whether a student's heart rate of 230 beats / minute is a false alarm by the device), and those that pass the review are added to the list of valid data details.

[0098] S45 and PAD set the effective data caching period (the default is the same as the course duration), periodically compress and store the list of effective data details (using lightweight JSON format), and clean up historical data that exceeds the caching period and invalid data interception logs; if the cache space is insufficient, prioritize retaining data that has not been uploaded to the server and generate a data cache optimization report.

[0099] The working principle and effects of the above technical solution are as follows:

[0100] The data is filtered by the identification range and type of the course group. For example, the running group only receives data identified by 0001-0050. Teachers do not need to manually filter information from other classes or courses, which saves subsequent processing time, reduces interference from irrelevant data, and improves the relevance of data reception.

[0101] By verifying the service_uuid and feature fields, data packets from Bluetooth headsets and ordinary smartwatches can be directly intercepted, preventing irrelevant data from occupying the PAD's channels and memory, ensuring smooth transmission of teaching data, enhancing data purity, and reducing interference from external Bluetooth devices.

[0102] Secondary verification of timestamps and numerical ranges marks obviously incorrect data as abnormal, preventing false data from affecting teachers' judgment, improving data accuracy, and reducing the mixing of abnormal data;

[0103] The data is linked to student names by wristband identification. The generated valid list can directly show a student's heart rate / number of jump ropes at a certain time, eliminating the need to look up the identification table. This reduces the teacher's operational costs, improves the usability of the data, and makes it easier for teachers to quickly match students.

[0104] Compress and store valid data, regularly clean up old logs, and prioritize retaining data that has not yet been uploaded. This avoids the problem of memory overflow causing new data to be unable to be stored, and also eliminates the need to delete critical information to store old data, thereby reducing the storage pressure on the PAD and minimizing the risk of data loss.

[0105] In one embodiment of the present invention, S41 includes:

[0106] The PAD analyzes the course-wristband grouping mapping table, extracts the school's unique identifier range (e.g., running group 0001-0050) and course type code (e.g., jump rope course code 0x02), generates an isolation dimension parameter table, and clarifies the specific numerical range of the two types of filtering conditions;

[0107] The parameters in the isolation dimension parameter table are converted into a rule format that the Bluetooth receiver module can recognize: the identification range is stored as a start value-end value string, the course type code is stored as a hexadecimal value, and a formatted isolation rule set is generated, which includes rule ID, condition type and matching value;

[0108] PAD writes the formatted isolation rule set into the filtering engine of the Bluetooth receiver module through the internal interface, configures the module to start real-time filtering mode, triggers rule matching checks for each received data packet, and generates module rule configuration logs.

[0109] During the data reception process, the Bluetooth receiving module compares the unique school identifier and course type code in the data packet with the format isolation rule set in real time. It directly discards data packets that do not match and generates real-time interception records.

[0110] PAD samples and checks the consistency between the real-time interception records and the formatted isolation rule set every 30 seconds to confirm that the intercepted data packets are all irregular data. If a false interception is found, the corresponding rule is temporarily suspended and an alarm is triggered, and a rule validity verification report is generated.

[0111] The working principle and effects of the above technical solution are as follows:

[0112] By extracting the identifier range and course code to generate an isolation dimension parameter table, the scattered filtering conditions are organized into clear numerical ranges. Teachers do not need to remember confusing parameters, and the filtering omissions caused by ambiguous conditions are avoided. This improves the clarity of the isolation rule configuration and reduces filtering errors caused by parameter confusion.

[0113] Converting parameters into a format that the module can recognize eliminates the need for repeated format debugging, ensuring that rules can be directly embedded into the filtering engine, saving configuration time, improving the compatibility between rules and Bluetooth modules, and reducing the problem of modules being unable to recognize rules;

[0114] The Bluetooth module filters out mismatched data in real time and discards data packets that cross classes or courses directly, without waiting for the data to be transmitted to the upper layer for processing. This avoids invalid data occupying memory and slowing down the PAD's running speed, reduces the subsequent data processing pressure on the PAD, and reduces the memory occupied by invalid data.

[0115] This technical solution reduces cross-scenario data interference and improves the targeting of data reception. For example, the running group only receives data marked 0001-0050, and will not mix in data packets from the jump rope class or other classes. Teachers do not need to filter irrelevant information when viewing data later and can focus on the data of the current course.

[0116] The interception records are sampled and verified every 30 seconds. If a false interception is found, the rule is paused and an alarm is triggered to avoid losing valid data that should have been received. This ensures data integrity, enhances the accuracy of rule execution, and reduces the loss of valid data caused by false interceptions.

[0117] In one embodiment of the present invention, step S5 includes:

[0118] Based on the list of valid data details, S51 and PAD call the visualization engine to generate a real-time exercise data dashboard: displaying real-time heart rate curves, cumulative jump rope counts, and cadence trends by student dimension; and displaying average heart rate, jump rope pass rate (e.g., 120 jumps per minute is considered pass) and abnormal data warnings (e.g., heart rate > 180 beats / minute is marked in red) by class dimension; the dashboard allows teachers to click on student names to view details and generate a real-time teaching monitoring interface;

[0119] The S52 and PAD monitor the data in the effective data details list in real time. If the preset warning threshold is triggered (such as heart rate >180 beats / minute for 10 seconds or no change in the number of jump ropes for 5 minutes), an abnormal warning prompt box will immediately pop up and send a reminder instruction to the corresponding student's wristband via Bluetooth broadcast (such as vibration + screen display to slow down the exercise pace). Teachers can guide students to adjust their exercise status on the spot according to the warning information and generate an abnormal data intervention record.

[0120] S53 and PAD set the data reporting cycle (default 30 seconds / time, can be adjusted as needed). After each cycle, the data that has not been reported in the list of valid data details is packaged in the protocol format (using encrypted JSON format to prevent data leakage) and uploaded to the backend server via 4G / 5G network. After receiving the data, the server verifies the integrity of the data and returns a reporting confirmation ACK. The PAD marks the corresponding data as reported.

[0121] S54. The server stores the received valid data in a distributed database (such as a MySQL cluster) and starts a real-time analysis engine: First, it calculates the trend of individual student exercise indicators (such as the change in a student's heart rate throughout the class and the increase in the number of rope skippings); second, it calculates the class teaching effectiveness indicators (such as the average exercise intensity of the class and the percentage of students who meet the standards); third, it generates a course data comparison report (such as the difference between the data and the previous course data of the same class); and finally outputs a physical education course data analysis report.

[0122] S55. Teachers can view the real-time teaching monitoring interface and the physical education course data analysis report returned by the server through the PAD. If the average heart rate of the class is found to be too low (<120 beats / minute), the exercise intensity will be increased (e.g., the running speed will be increased from 6km / h to 8km / h). If multiple students are found to have abnormal heart rates, the exercise will be suspended for rest and adjustment. The adjusted data will be re-collected, transmitted, and verified through steps S1-S4 to form a closed loop of teaching data collection-analysis-decision-adjustment-re-collection. Finally, a physical education course teaching summary report will be generated for subsequent course review and optimization.

[0123] The working principle and effects of the above technical solution are as follows:

[0124] The real-time dashboard displays heart rate curves and achievement rates by student and class, and allows teachers to view details by name. Teachers can grasp the overall exercise status at a glance without having to search through scattered tables, which improves the intuitiveness of teaching monitoring and reduces the complexity of reading data.

[0125] Real-time monitoring data triggers early warnings, immediately popping up alerts and causing the wristband to vibrate, allowing teachers to intervene promptly without waiting for students to feel unwell, thus reducing the risk of student movement and minimizing safety hazards.

[0126] The data is uploaded in encrypted JSON format, and the server also verifies its integrity to prevent data from being stolen or damaged during transmission, thus protecting the privacy of students' sports data, enhancing data transmission security, and reducing the risk of information leakage.

[0127] The server automatically calculates student indicator trends and class achievement rates, and can also compare data with the previous course. Teachers do not need to calculate manually, and the analysis report is generated quickly, which improves the efficiency of teaching analysis and reduces the workload of manual statistics.

[0128] Adjusting exercise intensity based on data feedback eliminates the need for experience-based judgments. Post-lesson review and optimization allow for more tailored lessons, enhancing the specificity of teaching adjustments and reducing haphazard instruction.

[0129] In one embodiment of the present invention, S54 includes:

[0130] After receiving the encrypted JSON data uploaded by the PAD, the server first decrypts the data using a preset key and parses out the core fields. These core fields include the wristband's unique school identifier, the type of exercise data, the timestamp, and specific exercise indicators (heart rate, number of jumps, etc.). The server then performs field validity checks on the parsed data (such as timestamp format and indicator value range), filters out invalid fields, and generates a standardized data table for storage.

[0131] The server shards the standardized data table into the database by time and class, and stores it on the corresponding nodes of the MySQL cluster (e.g., data from Class A on the same day is stored on node 1, and data from Class B is stored on node 2) to ensure the balance of distributed data storage. At the same time, it records information such as storage time, data source PAD identifier, and storage node number to generate a data storage log table.

[0132] The server starts the real-time analysis engine and loads the three preset analysis dimensions: first, the single student exercise index dimension (which needs to calculate the heart rate change curve and the growth trend of the number of rope skipping times); second, the class teaching effect dimension (which needs to calculate the average exercise intensity and the percentage of students who meet the standards); and third, the course data comparison dimension (which needs to extract the historical data of the previous course of the same class as the comparison benchmark). Based on the configuration, an analysis dimension parameter table is generated, which clarifies the calculation rules and data sources for each dimension.

[0133] The analysis engine uses data from a distributed database to perform calculations based on the analysis dimension parameter table: for the single student dimension, it generates heart rate-time and jump rope count-time trend data through time series algorithms; for the class dimension, it calculates indicators such as the class average heart rate and the number of students who passed the jump rope test / total number of students through statistical algorithms; for the course comparison dimension, it calculates data such as the difference in average heart rate between the current and previous courses and the change in the pass rate through difference analysis algorithms; after the calculations for each dimension are completed, a detailed table of multi-dimensional analysis results is generated.

[0134] The server transforms the data in the multi-dimensional analysis results table into visual charts (such as a single student's heart rate line chart, a class's pass rate bar chart, and a course comparison radar chart), and adds textual conclusions (such as a student's heart rate fluctuating steadily throughout the class, meeting the exercise intensity requirements, and the class's jump rope pass rate increasing by 15% compared to the previous time). By integrating the charts and conclusions, a structured physical education course data analysis report is generated, which can be viewed on the PAD via API.

[0135] The working principle and effects of the above technical solution are as follows:

[0136] After the server decrypts the data, it verifies the validity of the fields, filters out erroneous or missing data, and prevents dirty data from being stored in the database. This eliminates the need for manual cleanup of invalid information, improves the accuracy of the data entering the database, and reduces interference from invalid data.

[0137] Data is sharded by time and class and stored in the MySQL cluster. For example, data from Class A is stored on node 1 and data from Class B is stored on node 2 on the same day. This prevents a single node from accumulating too much data. Storage logs are also generated, making it easier to check the data source or node issues later. This reduces traceability time, improves storage balance, and reduces the pressure on a single node.

[0138] The real-time engine automatically calculates individual student heart rate trends, class achievement rates, and course data comparisons, eliminating the need for teachers to manually calculate curves or percentages from a large amount of data. This saves a significant amount of statistical time, improves analytical efficiency, and reduces the workload of manual statistical analysis.

[0139] The data is converted into line charts and bar charts, along with textual conclusions, so teachers don't have to look at dry data tables. They can grasp the course effectiveness at a glance, which enhances the intuitiveness of the report and improves teachers' comprehension efficiency.

[0140] PAD can directly access reports via API, eliminating the need to log in to the backend on a computer. Reports can be viewed during class breaks, facilitating timely review of course issues, enhancing report usability, and reducing viewing obstacles.

[0141] An embodiment of the present invention provides a low-latency Bluetooth group communication system for physical education teaching scenarios, comprising:

[0142] One or more processors;

[0143] Memory, used to store one or more programs.

[0144] Wherein, when the one or more programs are executed by the one or more processors, the one or more processors are made to implement the method described in any one of the above.

[0145] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A low-latency Bluetooth group communication method for physical education teaching scenarios, characterized in that, The method includes: S1. Scan the QR code on the wristband using the dedicated sports teaching APP. After reading the QR code information, the APP sends business data to the wristband, completes the initial binding of the wristband, and generates a list of initialized wristbands. S2. Based on the initialized wristband list, dynamically group the wristbands of students participating in the same physical education course; during data transmission, adopt a batch ACK mechanism to generate batch ACK packets and send them back to each wristband via Bluetooth broadcast; perform batch ACK sending and receiving, and after receiving the batch ACK, the wristband marks the corresponding data packet as uploaded; S3. Before data transmission begins, the wristband and the APP conduct adaptive negotiation on the Bluetooth protocol version to determine the highest Bluetooth protocol version supported by both parties, and adjust the byte limit and transmission rate of data transmission according to the protocol version; based on the negotiation results, a data transmission strategy adapted to the current Bluetooth protocol version is generated. S4. During data transmission, data packets from non-target wristbands are filtered out using logical isolation technology. At the same time, a feature verification mechanism is used to verify the received data packets, generating a list of valid data after logical isolation and feature verification. S5 and PAD display each student's exercise data in real time based on the list of valid data. At the same time, the collected data is reported to the server for storage and analysis, generating a real-time exercise data display interface and data analysis report.

2. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 1, characterized in that, S1 includes: S11. Activate the wristband binding module of the dedicated sports teaching APP, call the device camera to scan the binding QR code on the surface of the wristband; use the APP's built-in QR code parsing engine to extract the core information encapsulated in the QR code and generate the wristband's original information parsing table; S12. The APP uses the serial number and manufacturer code from the original information parsing table of the wristband as request parameters to call the wristband binding API of the backend server; the server verifies the legality of the serial number, generates the wristband's unique school identifier and wristband MAC address, and returns these two types of business data to the APP to generate the wristband business data allocation table. S13. The APP uses Bluetooth broadcasting mechanism to package the school's unique identifier and MAC address in the wristband's business data allocation table according to the protocol format and broadcasts them to the target wristband via Bluetooth; the wristband starts passive scanning mode to receive and temporarily store the business data sent by the APP. S14. The wristband verifies the legality of the received business data. If the verification is successful, the wristband stores the school's unique identifier and MAC address in the local flash memory, generates an ACK response packet, and broadcasts it to the APP via Bluetooth. S15. After receiving the ACK response from the wristband, the APP marks the wristband's binding status as activated, enters its information into a table, and generates a list of initialized wristbands.

3. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 1, characterized in that, S2 includes: S21. The teacher selects the current course type and class information in the APP on the PAD. The APP calls the list of initialized wristbands, filters out wristbands that are active and whose class matches the current course; divides the wristbands into independent groups according to course type, generates a course-wristband group mapping table, and performs logical isolation of wristbands for different courses. S22, PAD broadcasts group identifier instructions to the target group's wristbands based on the course-wristband grouping mapping table; after receiving the instructions, the wristband verifies the consistency between the group's unique identifier and its own group. If they match, it switches to intra-group communication mode and returns a group joining confirmation packet. PAD summarizes the confirmation information and updates the group wristband online status table. S23. The teacher issues a sports mode command via PAD. After receiving the command, the wristbands in the group start the training mode and actively broadcast sports data at a frequency of 1 time / second. The PAD starts continuous passive scanning, receives and caches the broadcast data of all wristbands in the group, and generates a real-time wristband data cache table. S24. PAD sets a batch aggregation cycle. After each cycle, it extracts the message sequence number of unconfirmed data and the school's unique identifier of the corresponding wristband from the real-time wristband data cache table, and packages them into a batch ACK packet according to the protocol format. PAD sends the batch ACK packet to all wristbands in the group via Bluetooth broadcast, and updates the data confirmation status table at the same time. S25. After receiving a batch of ACK packets, the wristband extracts the school's unique identifier from the packet and compares it with itself. If they match, it reads the corresponding message sequence number and marks the data with that sequence number stored locally as uploaded. If the wristband does not receive an ACK confirmation for a certain data within 3 summary cycles, it triggers a retransmission mechanism to rebroadcast the unacknowledged data and generate a wristband data upload status report.

4. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 1, characterized in that, The S3 includes: S31. Before data transmission, the wristband starts the protocol negotiation mode and sends a protocol capability report via Bluetooth broadcast. After the APP receives the report, it stores it in the wristband's protocol capability database. S32. The APP reads the Bluetooth protocol versions it supports, combines them with the supported versions of the wristband in the wristband protocol capability database, and determines the target protocol version by taking the highest compatible version; at the same time, it calculates the effective transmission bytes under this version and generates a protocol version determination result table. S33. Based on the protocol version determination result table, the APP generates a data transmission parameter configuration command. The APP sends the command to the wristband via Bluetooth broadcast. After receiving the command, the wristband returns a parameter confirmation ACK. S34. The wristband formulates data packet rules according to the data transmission parameter configuration instructions. The wristband performs packet pre-reaction through local simulation data to verify the correctness of the packet logic and generate a packet pre-reaction report. S35. After the wristband completes parameter configuration and packet pre-rehearsal, it switches to the no-wait broadcast mode; the PAD receives data at the same frequency, buffers it in the real-time data buffer, and generates batch ACKs after the aggregation period arrives, and performs broadcast-reception parallel processing.

5. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 4, characterized in that, The data packetization rule is as follows: if a single piece of motion data exceeds the packet size, it is split according to timestamp + data segment identifier + data content format. Specifically, a 500-byte piece of data is split into three 235-byte packets, labeled as segment 1 / 3, segment 2 / 3, and segment 3 / 3.

6. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 1, characterized in that, The S4 includes: S41, PAD generates logical isolation rules based on the course-bracelet grouping mapping table; PAD embeds these rules into the Bluetooth receiving module to automatically intercept data packets that do not match the rules; S42. After receiving a Bluetooth data packet, PAD performs feature verification. If any verification fails, the data packet is discarded and an invalid data interception log is generated. S43. For data packets that pass the feature verification, the PAD parses their data content and performs a second verification according to the protocol format; data that fails the verification is marked as abnormal data and temporarily stored in the abnormal data pending review table. S44 and PAD categorize the data that has passed the format verification according to the unique identifier of the school on the wristband, extract the core information of each data, and associate it with the student names in the initialized wristband list to generate a list of valid data details; at the same time, abnormal data is reviewed, and those that pass the review are added to the list of valid data details. S45 and PAD set an effective data caching period, periodically compress and store the list of effective data details, and clean up historical data that exceeds the caching period and invalid data interception logs; if the cache space is insufficient, prioritize retaining data that has not been uploaded to the server and generate a data cache optimization report.

7. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 6, characterized in that, S41 includes: PAD analyzes the course-wristband grouping mapping table, extracts the school's unique identifier range and course type code, generates an isolation dimension parameter table, and clarifies the specific numerical range of the two types of filtering conditions; Convert the parameters in the isolation dimension parameter table into a rule format that the Bluetooth receiver module can recognize, and generate a formatted isolation rule set; PAD writes the formatted isolation rule set into the filtering engine of the Bluetooth receiver module through the internal interface, configures the module to start real-time filtering mode, triggers rule matching checks for each received data packet, and generates module rule configuration logs. During the data reception process, the Bluetooth receiving module compares the unique school identifier and course type code in the data packet with the format isolation rule set in real time. It directly discards data packets that do not match and generates real-time interception records. PAD samples and checks the consistency between the real-time interception records and the formatted isolation rule set every 30 seconds to confirm that the intercepted data packets are all irregular data. If a false interception is found, the corresponding rule is temporarily suspended and an alarm is triggered, and a rule validity verification report is generated.

8. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 1, characterized in that, The S5 includes: S51 and PAD use a visualization engine to generate a real-time motion data dashboard based on a list of valid data details. The dashboard allows teachers to click on a student's name to view details and generate a real-time teaching monitoring interface. The S52 and PAD monitor the data in the list of valid data details in real time. If the preset warning threshold is triggered, an abnormal warning prompt box will immediately pop up and send a reminder instruction to the corresponding student's wristband via Bluetooth broadcast. Based on the warning information, the teacher will guide the student to adjust the exercise status on the spot and generate an abnormal data intervention record. S53 and PAD set the data reporting period. After each period, the data that has not been reported in the list of valid data details is packaged according to the protocol format and uploaded to the backend server through the 4G / 5G network. After receiving the data, the server verifies the integrity of the data and returns a reporting confirmation ACK. The PAD marks the corresponding data as reported. S54. The server stores the received valid data into a distributed database and starts the real-time analysis engine, ultimately outputting a sports course data analysis report. S55. Teachers can view the real-time teaching monitoring interface and the physical education course data analysis report returned by the server through the PAD. If the average heart rate of the class is found to be too low, the intensity of exercise will be increased. If multiple students are found to have abnormal heart rates, exercise will be suspended for rest and adjustment. The adjusted data will be re-collected, transmitted and verified through steps S1-S4 to form a closed loop of teaching data collection-analysis-decision-adjustment-re-collection, and finally generate a physical education course teaching summary report.

9. The low-latency Bluetooth group communication method in a physical education teaching scenario according to claim 8, characterized in that, S54 includes: After receiving the encrypted JSON data uploaded by the PAD, the server first decrypts the data using a preset key, parses out the core fields, performs field validity checks on the parsed data, filters out invalid fields, and generates a standardized data table for database entry. The server shards the standardized data tables into shards based on time and class dimensions, and stores them on the corresponding nodes of the MySQL cluster to ensure the balance of distributed data storage. At the same time, it records information such as storage time, data source PAD identifier, and storage node number to generate a data storage log table. The server starts the real-time analysis engine and loads the preset configurations for the three main analysis dimensions; it then generates an analysis dimension parameter table based on the configuration, clarifying the calculation rules and data sources for each dimension. The analysis engine uses data from a distributed database to perform calculations based on the analysis dimension parameter table; after the calculations for each dimension are completed, a detailed table of multi-dimensional analysis results is generated. The server transforms the data in the multi-dimensional analysis results table into visual charts and adds textual conclusions; it then integrates the charts and conclusions to generate a structured sports course data analysis report, which can be viewed on a tablet via API.

10. A low-latency Bluetooth group communication system for physical education teaching scenarios, including: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 9.

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