Multi-protocol compatible fitness equipment data acquisition system and method

Abstract

The invention provides a multi-protocol compatible fitness equipment data acquisition system and method, and relates to the technical field of fitness equipment data acquisition, and the system comprises a sensor unit which is a bolt type strain sensor, is installed in a counterweight structure of fitness equipment, detects the displacement of a counterweight sheet through a strain sheet, and generates an original data flow; the identity recognition module is applied to the mobile terminal, acquires equipment parameters by scanning the equipment identification code and automatically associates with the corresponding sensor; the protocol analysis engine is internally provided with a multi-brand protocol library, original data flow is converted into a standardized data structure according to a predefined rule, and automatic data collection of oxygen-free instruments such as a flying bird machine and a rowing machine is achieved for the first time through combination of a bolt type strain sensor and the dynamic protocol analysis engine. The sensor is directly embedded into a counterweight structure, physical displacement is detected through a strain gauge, and the problem of data missing caused by the fact that an anaerobic instrument has no circuit interface is solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of fitness equipment data collection, more specifically, particularly relates to a multi-protocol compatible fitness equipment data collection system and method. BACKGROUND

[0002] At present, fitness equipment data collection is mostly used in aerobic equipment, especially in treadmills, which mainly realizes the data collection of exercise data by using the real-time access of pin sensor data: Defects in collection range: The existing scheme is only suitable for aerobic equipment (such as treadmills) that need external power supply, and the 60% of the total amount of gym equipment (flyer machines, rowing machines, etc.) have no circuit interface, resulting in complete data loss.

[0003] Protocol closed barrier: Head brands (Taynojia / Lijian / Bique) use private communication protocols (such as Taynojia's.tgd binary format), which require the purchase of a special gateway (the cost of a single machine is more than 50,000 yuan) to decode data.

[0004] Data islandization: Different brand equipment data is stored in independent systems (such as treadmill data stored in brand A local server, and spin bike data needs to be viewed by brand B APP), and members cannot obtain a unified view across equipment.

[0005] High operation complexity: Non-standard equipment needs to manually configure serial port parameters (baud rate 115200bps / data bits 8 bits / stop bit 1 bit), and the average single device configuration time is more than 3 minutes.

[0006] System migration cost: When the gym replaces equipment brands, the data platform needs to be reconfigured (case: the replacement of 20 treadmills in a venue results in a system reconfiguration cost of 150,000 yuan), and the user's historical training data cannot be inherited.

[0007] Energy imbalance: Traditional Bluetooth collection devices need to run continuously at high power (peak current ≥ 15mA) to maintain real-time connection, or rely on frequent manual reconnection by users.

[0008] Inefficient data acquisition: Historical records need to be exported through professional software, and ordinary users cannot quickly obtain them through mobile terminals (such as scanning the code to retrieve the training trend of a deep squat machine for 3 months). SUMMARY

[0009] In order to solve the above technical problems, the present application provides a multi-protocol compatible fitness equipment data collection system and method to solve the above problems.

[0010] A multi-protocol compatible fitness equipment data acquisition system, comprising: a sensor unit: a bolt-type strain sensor installed in the weight structure of a fitness equipment, which detects the displacement of the weight plate through a strain gauge and generates a raw data stream; an identity recognition module: a mobile terminal application that obtains device parameters by scanning the equipment identification code and automatically associates the corresponding sensor; a protocol analysis engine: a built-in multi-brand protocol library that converts the raw data stream into a standardized data structure according to predefined rules and supports remote protocol library updates; a dual-channel transmission controller: real-time motion data is transmitted through the message queue protocol, and non-real-time data is periodically uploaded through the hypertext transfer protocol; a data integration platform: aggregates cross-brand equipment data and stores it in a time series database, generating user training reports.

[0011] Preferably, the sensor unit uses low-power Bluetooth communication, the device broadcast packet contains the equipment type characteristic code and a unique serial number identifier, and the conversion rules of the protocol analysis engine include: identifying the device type identifier of the first byte of the data stream; parsing the action count data segment and the resistance value data segment; verifying data integrity based on the cyclic redundancy check code, the dual-channel transmission controller performs intelligent routing: real-time data stream is transmitted through the message queue protocol with quality of service level 1, and the topic format is / device_topic / {device ID}; non-real-time data is sent to the cloud interface through the hypertext transfer protocol after a specified time, the identity recognition module realizes zero-configuration binding, calls the terminal Bluetooth interface to automatically discover the device, and the binding process takes no more than 10 seconds, and the data integration platform includes: a structured storage module: establishing data index according to user identifier, equipment identifier and time stamp; a report generation module: generating training trend charts based on strength equipment data.

[0012] A multi-protocol compatible fitness equipment data acquisition method, comprising: scanning the equipment identification code to analyze the device parameters and activate the Bluetooth matching process; listening to the characteristic code in the sensor broadcast packet to establish a Bluetooth low-power connection; receiving real-time byte streams and converting them into structured data through a protocol library; performing real-time data transmission and batch data upload in parallel; cloud-integrating cross-equipment data to generate training reports, and the protocol analysis process is compatible with the Tarena, LiJian, and BiQu brand equipment protocols, without the need for a dedicated gateway device.

[0013] A fitness equipment data acquisition kit, comprising a bolt sensor and a near-field communication tag, the tag is pre-installed with an equipment identification code and supports mobile terminal touch binding.

[0014] Dynamic protocol analysis mechanism: Establish a multi-brand protocol mapping library to convert raw byte streams into structured data in real time; Support remote updating of protocol rules to adapt to new equipment protocols.

[0015] Dual-channel transmission architecture: Real-time channel uses message queue protocol to ensure instant transmission of critical data; Batch channel periodically uploads non-critical data, reducing server load.

[0016] Non-inductive identity binding: Automatic association of devices through identification code scanning, eliminating manual configuration steps.

[0017] Compared with the prior art, the present application has the following beneficial effects: Breakthrough in data acquisition of anaerobic equipment: Through the combination of a latch-type strain sensor and a dynamic protocol analysis engine, the automatic data acquisition of anaerobic equipment such as flywheel machines and rowing machines (accounting for 90% of the total amount of gym equipment) is realized for the first time. The sensor is directly embedded in the weight structure, and the physical displacement is detected by the strain gauge (accuracy ±0.5%), solving the problem of data loss caused by the lack of circuit interface in anaerobic equipment.

[0018] Break brand protocol barriers: The dynamic protocol analysis engine has built-in conversion rules for private protocols of mainstream brands such as Tarena, Li Jian, and Bi Qu, which can convert the original 16-bit byte stream (such as 0x22 0xE3 0x00 0x01) into standardized JSON format in real time. Without manufacturer authorization or special gateway (single-brand access cost from 50,000 yuan to close to zero), cross-brand equipment is realized.

[0019] Eliminate data silos: The unified data platform establishes an index based on user ID + equipment ID + timestamp, and aggregates multi-brand data such as treadmills and strength equipment. Members can view cross-equipment historical training reports (such as deep squat / bench press trend comparison chart) in a single interface, and the data utilization rate is improved by 300%.

[0020] Revolutionary improvement in operational efficiency: Scan / code (NFC) triggers Bluetooth automatic matching: The mobile terminal accurately associates the equipment through broadcast packet characteristic values (such as device name "SN_XXX" and characteristic code 0xE3); The binding process takes ≤8 seconds, which is 22 times more efficient than traditional manual configuration (≥3 minutes per machine).

[0021] Dual-channel transmission ensures data integrity: Real-time channel: MQTT protocol transmits critical data with QoS=1 level (end-to-end delay <50ms), and messages are persisted locally when the network is disconnected, and automatically supplemented after reconnection; Batch channel: HTTP protocol uploads non-real-time data (such as power, temperature) every 10 seconds, and the server concurrent pressure is reduced by 40%; the data packet loss rate is reduced to 0.01% through the cooperation of the double-channel.

[0022] Seamless migration capability of historical data: User training data is decoupled from hardware devices. When a gym replaces equipment brands, historical records (such as resistance values and motion counts) can be migrated to new brand systems through a unified data platform, avoiding 150,000 yuan-level data system reconstruction costs caused by equipment replacement.

[0023] Optimization of energy efficiency ratio: Adopting low-power Bluetooth (BLE) design: Standby current ≤0.1mA (peak current reduced by 80% compared with traditional solutions); Device endurance time is increased by 3 times, supporting continuous 30-day maintenance-free operation.

[0024] Expand AI training ecology: Standardized data format provides infrastructure for AI applications: Real-time JSON data stream can be directly input into AI models to generate personalized training plans; Cross-brand historical data constructs user strength growth curve, supporting dynamic adjustment of course intensity. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 is the data flow diagram of the present application; Figure 2 is the aerobic equipment data flow diagram of the present application; Figure 3 is a schematic diagram of cloud connection. DETAILED DESCRIPTION

[0026] The embodiments of the present application will be further described in detail below in combination with the drawings and examples. The following examples are used to illustrate the present application, but cannot be used to limit the scope of the present application.

[0027] Please refer to Figures 1-3The application provides a multi-protocol compatible fitness equipment data acquisition system, comprising: a sensor unit: a bolt type strain sensor installed in a fitness equipment weight structure, which detects the displacement of the weight piece through a strain gauge and generates an original data stream; an identity recognition module: a mobile terminal application, which obtains equipment parameters by scanning the equipment identification code and automatically associates the corresponding sensor; a protocol analysis engine: a built-in multi-brand protocol library, which converts the original data stream into a standardized data structure according to predefined rules and supports remote protocol library updating; a dual-channel transmission controller: real-time motion data is transmitted through the message queue protocol, and non-real-time data is periodically uploaded through the hypertext transfer protocol; a data integration platform: aggregating cross-brand equipment data and storing it in a time series database to generate a user training report.

[0028] The sensor unit adopts low-power Bluetooth communication, the device broadcast packet contains an equipment type characteristic code and a unique serial number identifier, the conversion rules of the protocol analysis engine include: identifying the device type identifier of the first byte of the data stream; analyzing the action count data segment and the resistance value data segment; verifying the data integrity based on the cyclic redundancy check code, the dual-channel transmission controller performs intelligent routing: the real-time data stream is transmitted through the message queue protocol with a quality of service level of 1, and the topic format is / device_topic / {device ID}; the non-real-time data is sent to the cloud interface through the hypertext transfer protocol after being cached for a specified time, the identity recognition module realizes zero-configuration binding, calls the terminal Bluetooth interface to automatically discover the device, and the binding process takes no more than 10 seconds, and the data integration platform comprises: a structured storage module: establishing a data index according to a user identifier, an equipment identifier and a time stamp; a report generation module: generating a training trend chart based on the strength equipment data.

[0029] A multi-protocol compatible fitness equipment data acquisition method, comprising: scanning an equipment identification code to analyze equipment parameters and activate a Bluetooth matching process; listening to the characteristic code in the sensor broadcast packet to establish a Bluetooth low-power connection; receiving real-time byte streams and converting them into structured data through a protocol library; performing real-time data transmission and batch data uploading in parallel; integrating cross-equipment data on the cloud to generate a training report, the protocol analysis process is compatible with the Tarena, LiJian and Biqu brand equipment protocols, and no special gateway device is needed.

[0030] A fitness equipment data acquisition kit, comprising a bolt sensor and a near field communication tag, the tag is pre-provisioned with an equipment identification code and supports mobile terminal touch binding.

[0031] The system of the application comprises a hardware data acquisition device (such as a bolt sensor) and a supporting software system (such as a mobile terminal applet and a cloud platform). The core working process is as follows: 1. Find the equipment o Scan trigger: The user scans the device's preset QR code (containing the device ID and parameters). The client software (such as a WeChat mini-program) parses the QR code data and redirects to the device connection interface. → Corresponding appendix Figure 1 User interaction layer → Bluetooth scanning module o Device matching: The client automatically matches the name of the pin sensor device associated with the QR code information. 2. Bluetooth initialization phase, device pairing o Initialization: Call the Bluetooth API (wx.openBluetoothAdapter) to initialize the Bluetooth adapter. o Device scanning: Listen for pin devices containing a specific name ("SN_Zxxxx") in broadcast packets, and match these pins using their signatures and service information. → Corresponding appendix Figure 1 Bluetooth scanning module → Device discovery interface 3. From receiving data through the latch to parsing the data. o Data monitoring: After establishing a Bluetooth channel, receive raw byte stream data in real time.

[0032] Example data stream: 0x22 0xE3 0x00 0x01 0x00 0x01 0x01 0x07 0x27 → Corresponding Appendix Figure 1 Data receive buffer o Protocol Analysis The client has a built-in dynamic protocol parsing library that converts raw byte streams according to predefined rules. Parsing logic: static parseData(data) { / / Parse data const deviceType = data[1]; const weightCount = (data[2] << 8) | data[3]; const count = (data[4] << 8) | data[5]; const acceleration = (data[6] << 8) | data[7]; const battery = data[8]; return { deviceType: `0x${deviceType.toString(16)}`, weightCount, count, acceleration, battery: `${battery}%` }; } Output normalized data: { "deviceType": "0xe3", "weightCount": 11, "count": 3, "acceleration": 840, "battery": "81%" } Cloud Step 4: Dual-channel cloud transmission

[0033]

[0034] Key details of data interaction • Raw data format: Hexadecimal byte stream (example: 0x01 0x05 0x32 0x0A) • Structure after parsing: Standard JSON format, containing device type, weight count, acceleration, and other motion parameters • Transmission protocol: • MQTT real-time channel: Suitable for large-scale activities or data saving under special circumstances (phone runs out of power in the middle) HTTP batch channel: Periodically (default 10 seconds) upload cached data.

[0035] Embodiments of the present application are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the application to the forms disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. Embodiments are chosen and described in order to best explain the principles of the application and its practical application, and to enable others skilled in the art to understand the application for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. A multi-protocol compatible fitness equipment data collection system, characterized by, Comprising: Sensor unit: Plug-in strain sensor installed in the weight structure of the fitness equipment, detecting the displacement of the weight plate through strain gauges and generating raw data streams; Identity recognition module: Mobile terminal application, obtaining device parameters by scanning equipment identification code, automatically associating corresponding sensors; Protocol analysis engine: Built-in multi-brand protocol library, converting raw data streams into standardized data structures according to predefined rules, supporting remote protocol library updates; Dual-channel transmission controller: Real-time motion data is transmitted through message queue protocol, and non-real-time data is periodically uploaded through hypertext transfer protocol; Data integration platform: Aggregates cross-brand equipment data and stores it in a time series database, generating user training reports.

2. The system of claim 1, wherein: The sensor unit uses low-power Bluetooth communication, and the device broadcast packet contains equipment type characteristic code and unique serial number identification.

3. The system of claim 1, wherein: The conversion rules of the protocol analysis engine include: Identifying the device type identifier in the first byte of the data stream; Parsing the action count data segment and resistance value data segment; Verifying data integrity based on cyclic redundancy check code.

4. The system of claim 1, wherein: The dual-channel transmission controller performs intelligent routing: Real-time data streams are transmitted through message queue protocol with quality of service level 1, and the topic format is / device_topic / {device ID}; Non-real-time data is sent to the cloud interface through hypertext transfer protocol after a specified time.

5. The system of claim 1, wherein: The identity recognition module realizes zero-configuration binding, automatically discovers devices by calling the terminal Bluetooth interface, and the binding process takes no more than 10 seconds.

6. The system of claim 1, wherein: The data integration platform includes: Structured storage module: Establishes data index according to user identification, equipment identification, and time stamp; Report generation module: Generates training trend charts based on strength equipment data.

7. A multi-protocol compatible fitness equipment data collection method, characterized by, Comprising: Scanning equipment identification code to parse device parameters and activate Bluetooth matching process; Listening to the characteristic code in the sensor broadcast packet to establish Bluetooth low-power connection; Real-time reception of raw byte streams and conversion to structured data through protocol library; Parallel execution of real-time data transmission and batch data upload; Cloud integration of cross-equipment data to generate training reports.

8. The method of claim 7, wherein: The protocol analysis process is compatible with Tarena, Liqian, and Biquan brand equipment protocols, without the need for a dedicated gateway device. 9.A computer readable storage medium storing program instructions, and the program instructions comprise the following steps: When the instructions are executed, the steps of the method according to any one of claims 7-8 are implemented. ​ 10. A fitness equipment data acquisition kit comprising the plug-in sensor of claim 1 and a near-field communication tag, the tag is pre-installed with equipment identification code, supporting mobile terminal touch binding.

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