RFID tag reader-writer for state verification of dumb resource equipment and data collaborative updating method

Abstract

The invention discloses an RFID tag reader-writer for dumb resource equipment state verification and a data collaborative updating method, relates to the technical field of RFID technology and equipment management, and also belongs to the field of data identification. The reader-writer comprises an environment interference dynamic response module, a distance adaptation power regulation module, a multi-source data integration storage module and a core control cooperation module, by integrating the environment interference dynamic response module, the data acquisition stability in an industrial scene is improved; traditional equipment is easily interfered in a complex electromagnetic environment to cause data loss or error, but the module effectively avoids an interference source and ensures continuous and reliable capture of state data by monitoring electromagnetic signal characteristics in real time and dynamically switching frequency bands or modulation modes; meanwhile, the core control cooperation module adopts a multi-master-slave SPI bus architecture, multi-module data streams can be scheduled in parallel, communication delay is reduced, and the data integrity is further guaranteed in combination with a double-link verification mechanism of the multi-source data integration storage module.

Description

Technical Field

[0001] This invention relates to the fields of RFID technology and equipment management technology, and also to the field of data identification. Specifically, it relates to an RFID tag reader / writer for verifying the status of dumb resource equipment and a data collaborative update method. Background Technology

[0002] With the deep integration of IoT technology, the status monitoring of dumb resource devices has become a key link in the industrial internet. These devices are widely distributed in the power, manufacturing, and logistics sectors, and their operating status directly affects production efficiency and system safety. However, traditional monitoring methods rely on manual inspections or wired sensors, which suffer from high deployment costs, poor flexibility, and insufficient real-time data. RFID technology, due to its non-contact and batch reading characteristics, has gradually become the mainstream solution for dumb resource status acquisition. However, electromagnetic interference in industrial environments, the coexistence of multiple devices, and the dynamic changes in tag reading distance cause traditional RFID readers to be prone to data loss, misreading, or excessive energy consumption. Therefore, developing an RFID reader that can adapt to complex industrial scenarios and has anti-interference capabilities and adaptive adjustment functions has become an urgent need to improve the efficiency of dumb resource management.

[0003] The prior art disclosed in CN118487762A is an RFID tag key update method, device, system, RFID tag reader, electronic device, and storage medium. Its core is to obtain the key dispersion factor (including the tag's internal UID / TID, EPC, and customer-specified factor external to the tag) through a host computer, generate a dispersion key using a cryptographic machine in conjunction with the root key, encrypt it with a protection key, and then send the encrypted text to the reader via the host computer for decryption and writing to the tag. This technology primarily addresses the problem of key interception and cracking during transmission, ensuring key writing security to prevent tag application data tampering. However, this technology has significant shortcomings. It lacks a mechanism to address electromagnetic interference in industrial scenarios, making it unable to dynamically avoid interference to maintain data acquisition stability. Furthermore, it does not consider the impact of dynamic changes in the distance between the reader and the tag on the reading effect, lacks adaptive power adjustment capabilities, and is prone to short-range signal overload or long-range missed readings. Simultaneously, data processing fails to achieve semantic association and enhancement of multi-source information, making it difficult to directly support intelligent application needs such as AI fault diagnosis in industrial scenarios. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an RFID tag reader and writer for verifying the status of dumb resource equipment and a data collaborative update method. By integrating four major modules—dynamic response to environmental interference, distance-adaptive power adjustment, multi-source data integration and storage, and core control collaboration—it solves the problems of weak anti-interference ability, rigid reading strategies, and fragmented data processing of traditional RFID equipment in industrial scenarios.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: On the one hand, an RFID tag reader for verifying the status of dumb resource equipment, the reader comprising: a dynamic response module for environmental interference, a distance adaptation power adjustment module, a multi-source data integration and storage module, and a core control and coordination module; The environmental interference dynamic response module is used to monitor electromagnetic signals in the industrial environment, identify interference characteristics, switch operating frequency bands or modulation methods, and capture and output dummy resource equipment status verification data. The distance adaptation power adjustment module: detects the distance to the RFID tag, adjusts the transmission power according to the distance, and reads and outputs RFID tag data and distance and power related data; The multi-source data integration and storage module receives data output from the environmental interference dynamic response module and the distance adaptation power adjustment module, and performs data verification, correlation, format unification and storage. The core control and coordination module is connected to the environmental interference dynamic response module, the distance adaptation power adjustment module, and the multi-source data integration and storage module, respectively. It sends control commands, receives feedback information from each module, and coordinates the work of each module.

[0006] Furthermore, the electromagnetic signal monitoring frequency of the environmental interference dynamic response module is 10 to 15 full-band scans per second, and the interference feature identification includes the frequency range, intensity, and duration of the interference signal; the operating frequency band includes at least one of the 902 to 928 MHz and 2.4 to 2.4835 GHz frequency bands, and the modulation mode switching includes the conversion between ASK modulation and FSK modulation.

[0007] Furthermore, the distance detection frequency of the distance adaptation power adjustment module is once every 100ms; the transmission power is adapted to the distance range of the RFID tag, wherein the transmission power increases accordingly as the distance increases; the output RFID tag data includes the tag ID and the device status parameters stored in the tag.

[0008] Furthermore, the multi-source data integration and storage module receives data via dual independent links. Data verification includes field integrity checks and checksum comparisons. When associating data, data with a timestamp deviation of 30 to 100 ms are determined to be data from the same time point. The stored data is classified and archived according to the module source and collection time.

[0009] Furthermore, the core control coordination module communicates with other modules via an SPI bus, which supports a multi-master-slave mode and can establish three independent communication links simultaneously. The control commands include the command type, target module identifier, and data processing parameters.

[0010] On the other hand, a data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource devices, the specific steps of which are as follows: S100, collaborative data retrieval and collection: The core control and collaboration module sends data retrieval instructions to the environmental interference dynamic response module and the distance adaptation power adjustment module, and sends data reception instructions to the multi-source data integration and storage module; the environmental interference dynamic response module and the distance adaptation power adjustment module output data to the multi-source data integration and storage module respectively, and the multi-source data integration and storage module collects data according to module source and timestamp to form the original data set; S200, Triggering Data Verification and Completion: The core control and coordination module triggers the data verification process, and the multi-source data integration and storage module performs format verification on the original data set. When data is found to be missing or incomplete, the multi-source data integration and storage module feeds back to the core control and coordination module, which then sends a retransmission command to the corresponding module. After receiving the retransmitted data, the multi-source data integration and storage module verifies it again, and marks the data as processable after completion. S300, Instruction Processing of Standardized Data: Data processing instructions are sent to the multi-source data integration and storage module through the core control and coordination module. The multi-source data integration and storage module associates cross-module data using timestamps as the core dimension, unifies the data format and removes duplicate data to form a standardized data set. Among them, when associating cross-module data, a data fusion weight algorithm is used to calculate the association confidence. S400, Enhanced Matching and Data Generation: The core control coordination module sends semantic enhancement commands to the multi-source data integration and storage module. Simultaneously, the core control coordination module calls an external sensor system to acquire supplementary data and transmits it to the multi-source data integration and storage module. The multi-source data integration and storage module matches the supplementary data with the standardized dataset, injects information to generate semantically enhanced data, and marks it as pending update after verification. Among these steps, a semantic enhancement confidence algorithm is used to calculate the matching degree when matching the supplementary data with the standardized dataset. S500, determine transmission feedback update: the core control collaboration module determines the data transmission interface and target and sends the transmission command. The multi-source data integration and storage module transmits the semantically enhanced data to the device management backend database and the AI ​​fault diagnosis system. After the transmission is completed, the multi-source data integration and storage module feeds back the result to the core control collaboration module. The core control collaboration module records the update information and sends an update completion notification to the device management backend.

[0011] Furthermore, in S100, during the collaborative retrieval and collection of data, the data retrieval instruction sent by the core control coordination module includes a time range and a list of data types; the data output by the environmental interference dynamic response module includes at least one of interference frequency band records, frequency band switching records, and equipment voltage and temperature data; the data output by the distance adaptation power adjustment module includes at least one of distance monitoring values, power adjustment values, RFID tag IDs, and equipment runtime data; when the environmental interference dynamic response module and the distance adaptation power adjustment module transmit data, each predefined number of data entries carries a transmission confirmation signal; after receiving the confirmation signal, the multi-source data integration and storage module continues to receive subsequent data; if no confirmation signal is received within a preset time, the sending end retransmits the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module.

[0012] Furthermore, in S300, when the multi-source data integration and storage module associates cross-module data during the instruction processing of standardized data, it generates an association confirmation list for data marked as needing manual confirmation. The list contains the complete content of two data items, timestamp deviation values, and data numbers, and is pushed to the device management backend through the core control collaboration module.

[0013] Furthermore, in S400, when the external sensor system is called to obtain supplementary data in the enhanced matching data generation process, a request-response mode is adopted. The request information includes a list of target RFID tag IDs and the required supplementary data type code. The response information must be returned within 500ms. If the timeout occurs, a retry mechanism is triggered. The supplementary data and the standardized data set are matched according to the dual dimensions of RFID tag ID + timestamp.

[0014] Furthermore, in S500, during the transmission feedback update, the multi-source data integration and storage module transmits data according to a predefined batch size; before transmission, it sends a pre-announcement message containing batch information to the receiving end; after the receiving end responds with a confirmation of receipt based on the pre-announcement message, it initiates the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module; after transmission is completed, the multi-source data integration and storage module generates a transmission report containing the transmission status.

[0015] Compared with existing technologies, this RFID tag reader and data collaborative update method for verifying the status of dumb resource devices has the following advantages: I. This invention improves the stability of data acquisition in industrial scenarios by integrating a dynamic environmental interference response module. Traditional equipment is susceptible to interference in complex electromagnetic environments, leading to data loss or errors. However, this module effectively avoids interference sources and ensures continuous and reliable acquisition of status data by monitoring electromagnetic signal characteristics in real time and dynamically switching frequency bands or modulation methods. At the same time, the core control and coordination module adopts a multi-master-slave SPI bus architecture, which can schedule data streams from multiple modules in parallel, reducing communication latency. Combined with the dual-link verification mechanism of the multi-source data integration and storage module, data integrity is further guaranteed. This anti-interference design and efficient collaborative architecture enable the equipment to maintain high-precision status monitoring in highly interference scenarios such as power and manufacturing, reducing the risk of equipment misjudgment due to data anomalies.

[0016] Second, this invention achieves energy efficiency optimization and data semantic enhancement in RFID tag reading through the innovative linkage of a distance-adaptive power adjustment module and a multi-source data integration and storage module. Traditional readers use fixed power transmission, which can easily cause short-range overload or long-range missed readings. This module dynamically adjusts the transmission power according to the real-time distance, reducing energy consumption while ensuring the success rate of reading. The multi-source data integration and storage module breaks through the limitation of a single data source. Through the dual association of timestamps and RFID tag IDs, it integrates environmental interference data, equipment status parameters, and supplementary information from external sensors into a semantically enhanced dataset. This structured data not only improves the accuracy of fault diagnosis but also provides richer feature dimensions for AI models, helping predictive maintenance upgrade from "passive response" to "proactive optimization," and has significant industry promotion value.

[0017] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 Architecture diagram of the RFID tag reader / writer for verifying the status of dumb resource devices; Figure 2 A schematic diagram illustrating the entire process of collaborative data update for RFID tag readers in verifying the status of dumb resource devices. Figure 3Core output diagram of the collaborative update steps for RFID tag reader data for status verification of dumb resource equipment; Figure 4 This diagram illustrates the data transmission of each module in an RFID tag reader / writer for verifying the status of dumb resource devices. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] Example 1:

[0022] An RFID tag reader / writer for verifying the status of dumb resource equipment.

[0023] The RFID tag reader / writer for verifying the status of dumb resource equipment described in this embodiment is suitable for monitoring the status of dumb resource equipment such as motors and water pumps in industrial production workshops that do not have active data transmission capabilities. Its core is to achieve accurate collection, integration and management of equipment status data in complex industrial environments through the collaborative work of four functional modules. The overall hardware architecture adopts an industrial-grade metal shell for encapsulation, with a protection level of IP65, and can adapt to a temperature range of -20℃ to 70℃ and workshop environments with high dust and strong electromagnetic interference.

[0024] From the perspective of module connectivity, the core control coordination module establishes bidirectional communication links with the environmental interference dynamic response module, the distance adaptation power adjustment module, and the multi-source data integration and storage module via the SPI bus. The bus supports multi-master / slave mode, allowing simultaneous parallel transmission of information from three independent data channels. Each channel maintains a stable transmission rate of 1.2 Mbps, ensuring real-time command issuance and data feedback. The core control coordination module is equipped with a 32-bit ARM Cortex-M4 processor and has a built-in 256KB Flash memory for storing preset control logic algorithms and module communication protocols. The environmental interference dynamic response module integrates electromagnetic signal detection. The chip and frequency band switching controller receive frequency band switching commands from the core control coordination module via the SPI bus, and simultaneously transmits back the monitored interference characteristic data. The distance adaptation power adjustment module includes an ultrasonic ranging sensor and an RF power amplifier. It changes the transmission power according to the power adjustment commands from the core control coordination module and simultaneously uploads distance detection values ​​and RFID tag read data. The multi-source data integration and storage module is equipped with dual independent data receiving interfaces (corresponding to the first two functional modules respectively), has a built-in 16GB SD card for data storage, receives data processing and storage commands from the core control coordination module via the SPI bus, and feeds back data verification results and storage status, such as... Figure 1 As shown.

[0025] In the data transmission process, such as Figure 4 As shown, each module follows a closed-loop logic of "command-response-data feedback". When the reader starts, the core control coordination module first sends an electromagnetic signal monitoring command to the environmental interference dynamic response module. This module immediately starts a full-band scan of 10 to 15 times per second, covering the range of 902 to 928 MHz and 2.4 to 2.4835 GHz. It captures electromagnetic interference signals generated by frequency converters and welding machines in the industrial environment through a detection chip, extracting characteristic parameters such as the frequency range (accuracy ±50 kHz), intensity (dBm), and duration (ms) of the interference signals. These parameters are packaged into binary data frames and transmitted back to the core control and coordination module via the SPI bus. The core control and coordination module analyzes the interference characteristic data. If it determines that the current frequency band interference intensity exceeds -85dBm, it immediately issues a frequency band switching command to the environmental interference dynamic response module. For example, it switches from the 902 to 928MHz frequency band to the 2.4 to 2.4835GHz frequency band, or switches the modulation mode (from ASK modulation to FSK modulation) within the same frequency band to avoid the interference area and ensure that the status verification data of the dummy resource device (such as the device operating voltage and temperature threshold) can be accurately captured.

[0026] Meanwhile, the core control coordination module sends a distance detection command to the distance adaptation power adjustment module. The ultrasonic ranging sensor of this module completes a distance detection every 100ms, with a measurement range of 0.1 to 5m and a measurement accuracy of ±2cm. It transmits the detected distance data between the device and the RFID tag in real time. The core control coordination module matches a preset power adjustment strategy according to the distance range: when the distance is 0.1 to 1m, it controls the RF power amplifier to adjust the transmission power to 10dBm; when the distance is 1 to 3m, the transmission power is increased to 15dBm; and when the distance is 3 to 5m, the transmission power is further increased to 20dBm. This ensures that the RFID tag data can be stably read at different distances. The read RFID tag data includes a unique tag ID (128-bit code) and device status parameters stored in the tag (such as motor speed and water pump pressure). These data, along with distance and power-related data, are packaged together and transmitted to the multi-source data integration and storage module via the SPI bus.

[0027] The multi-source data integration and storage module receives data from the environmental interference dynamic response module and the distance adaptation power adjustment module via dual independent links. First, it performs a data verification process: on one hand, it checks the completeness of data fields (e.g., interference characteristic data must include frequency, intensity, and duration; missing any field indicates incompleteness); on the other hand, it calculates the checksum of the data frame (using the CRC32 algorithm) and compares it with the checksum attached to the sending end. If they do not match, the data is considered incorrect. For data that passes verification, the module processes it according to the "timestamp association" rule, classifying data from different modules with timestamp deviations within 30 to 100 ms as device status data at the same time point. For example, it associates environmental interference data at a certain moment with distance, power, and RFID tag data within the same time period. Then, it converts the data to JSON format and stores it on an SD card according to the naming rule of "module source + acquisition time" (e.g., "environment module_20240520143000" "distance and power module_20240520143000"). Simultaneously, it sends a data storage completion signal back to the core control and coordination module, achieving orderly data management and backup.

[0028] Example 2:

[0029] A method for collaborative data update of RFID tag readers for verifying the status of dumb resource equipment.

[0030] This embodiment, based on the RFID tag reader / writer described in Embodiment 1, takes the status monitoring data update of 10 stamping machines (dumb resource equipment) in an automotive parts production workshop as an example to elaborate on the complete usage process of the data collaborative update method. This process, through a core control collaboration module, coordinates the collaboration between various modules and external systems, achieving a closed-loop process from data collection and verification to final update to the management backend and diagnostic system. Figure 3 As shown.

[0031] After the process starts, the first step is to collaboratively retrieve and collect data: The core control collaboration module generates a data retrieval command based on the preset collection cycle in the equipment management background (set to once every 30 minutes in this embodiment). This command includes a time range of "20240520140000-20240520143000" and a list of data types including "interference frequency band records, distance monitoring values, RFID tag IDs, and equipment voltages". This command is sent to the environmental interference dynamic response module and the distance adaptation power adjustment module via the SPI bus. After receiving the command, the environmental interference dynamic response module filters out the interference frequency band records (e.g., interference exists in the 915 to 918MHz frequency band between 14:05 and 14:08), frequency band switching records (switching from 915MHz to 2450MHz at 14:06), and the voltage (380V±5V) and temperature (45 to 55℃) data of 10 stamping machines within the specified time range. These data are packaged into a data frame of 50 records each, and a transmission confirmation signal is appended to the end of each data frame. The power adjustment module filters out the distance monitoring values ​​(e.g., the distance to the tag of press No. 1 is stable at 1.2 to 1.3m), power adjustment values ​​(15dBm), RFID tag IDs (e.g., "RFID-001-202405"), and equipment running time (cumulative running time of 1200 hours) of the corresponding time period for each press's RFID tag. This data is packaged according to the rule of 50 data points with one confirmation signal. Both modules synchronously transmit the data frames to the multi-source data integration and storage module via the SPI bus. Each time this module receives a data frame and detects a confirmation signal, it sends a "reception successful" command to the sending end. If no confirmation signal is received within 500ms (e.g., due to momentary interference causing signal loss), the sending end immediately retransmits the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module until successful reception. Finally, the multi-source data integration and storage module aggregates the two types of data according to module source and timestamp, forming a raw data set containing 30 minutes of status data for 10 presses. Figure 2 As shown.

[0032] Next, the data verification and completion phase begins: After the original data set is collected, the core control coordination module automatically sends a "start data verification" command to the multi-source data integration and storage module. This module immediately performs format verification and checksum comparison on the original data set. The format verification reveals that three temperature data points for press #2 between 14:15 and 14:20 are missing, and the RFID tag ID field for press #5 is incomplete in the data frame at 14:25. The checksum comparison reveals that the distance data checksum for press #7 at 14:10 is inconsistent with the sending end. The multi-source data integration and storage module feeds back these anomalies (device number, time point, and error type of missing data) to the core control coordination module via the SPI bus. The core control coordination module generates retransmission commands for the corresponding time periods of presses 2, 5, and 7, and sends them to the corresponding modules: It sends a command to the environmental interference dynamic response module to "retransmit temperature data of press 2 from 14:15 to 14:20", and a command to the distance adaptation power adjustment module to "retransmit tag ID of press 5 at 14:25 and distance data of press 7 at 14:10". Both modules re-extract and retransmit the retransmitted data. The multi-source data integration and storage module receives the data and performs verification again. After confirming the data is complete and the checksum is consistent, it marks the original data set as "processable" and sends a "verification and completion complete" signal back to the core control coordination module.

[0033] The process then proceeds to the instruction processing and standardized data stage: the core control and coordination module sends a data processing instruction to the multi-source data integration and storage module, containing rules such as "timestamp-based association, unified JSON format, and removal of duplicate data." This module first performs cross-module association on environmental data (e.g., interference-free 2450MHz band), distance power data (1.2m, 15dBm), and RFID tag data ("RFID-001-202405") at the same timestamp (e.g., 14:10:00.000). During the association process, it was found that the timestamp deviation between the environmental data of press No. 3 at 14:22:00.050 and the distance data at 14:22:00.160 was 110ms, exceeding the automatic association range of 30 to 100ms. When associating cross-module data, a data fusion weighting algorithm is used to calculate the association confidence level, with the formula: ,in, This represents the association confidence level, with a value ranging from 0 to 1. , , These are the weighting coefficients, and , This represents the timestamp deviation between the two data sets. For data field matching degree, For the maximum field matching degree, Given the current environmental interference intensity, For the maximum tolerable interference intensity, when If it is determined to be a strong association, it will be automatically associated; when... When it is determined to be a weak association, manual confirmation is required; when The data was determined to be unrelated, and redundant data was removed. The data set was then marked as "awaiting manual confirmation of association". A list of data to be confirmed was generated, which included the complete content of two data sets (environmental data: 2450MHz without interference, time 14:22:00.050; distance data: 1.3m, time 14:22:00.160), timestamp deviation (110ms), and data numbers (HJ-3-1422, JL-3-1422). This list was pushed to the equipment management backend through the core control collaboration module. For data that did not require manual confirmation, the module uniformly converted it into JSON format containing fields such as "equipment number, timestamp, interference status, distance, power, tag ID, voltage, and temperature". Two duplicate data sets caused by repeated transmission by the module were removed. Finally, a standardized data set of 10 stamping machines was formed, and the core control collaboration module was notified that "data standardization is complete".

[0034] Next, the data generation stage of enhanced matching begins: The core control collaboration module first sends a "start semantic enhancement" command to the multi-source data integration and storage module, and then establishes a connection with the external sensor system (such as vibration sensors and noise sensors) via industrial Ethernet. It sends a request containing a list of RFID tag IDs for 10 stamping machines ("RFID-001-202405" to "RFID-010-202405") and the required supplementary data type codes (vibration: 001, noise: 002). The external sensor system uses a request-response mode, returning the corresponding data within 450ms (e.g., vibration value of stamping machine No. 1: 0.8mm / s, noise: 75dB). If a timeout occurs (e.g., due to network latency), a retry mechanism is triggered, with a maximum of 3 retries. After receiving the supplementary data, the multi-source data integration and storage module matches it with the standardized data set according to the dual dimensions of "RFID tag ID + timestamp." The matching degree is calculated using a semantic enhancement confidence algorithm when matching the supplementary data with the standardized data set. The formula is: ,in, To enhance semantic matching, the value ranges from 0 to 1. , , These are the weighting coefficients, and It can be the mean. Number of fields to match for RFID tag ID This represents the total number of fields in the ID field. To compensate for the discrepancy between the data and the standardized data timestamps, The attenuation coefficient is... To supplement the feature similarity between the data and the standardized data, For reference similarity, when If a match is deemed valid, supplementary data is injected; when... If the data is deemed to be a mismatch, the supplementary data is discarded and the anomaly is recorded. The vibration and noise data of the No. 1 press from 14:00 to 14:30 are injected into the standardized data of the corresponding time period to generate semantically enhanced data containing "equipment operating parameters + environmental interference + external sensing" (e.g., "equipment number: 1, time: 14:10:00, interference: none, distance: 1.2m, power: 15dBm, vibration: 0.8mm / s, noise: 75dB"). After verifying the data again to confirm that there are no conflicts, it is marked as "pending update status" and feedback "semantic enhancement completed" is sent to the core control coordination module.

[0035] Finally, the transmission feedback update phase begins: The core control and coordination module, based on the transmission parameters configured in the device management backend, determines that the data transmission interface is Ethernet (TCP / IP protocol), and the transmission targets are the device management backend database and the AI ​​fault diagnosis system. It generates a transmission command containing the target IP addresses (backend database: 192.168.1.100, AI system: 192.168.1.200) and sends it to the multi-source data integration and storage module. This module divides the data into batches of 20 semantically enhanced data (8 batches in this embodiment). Before transmitting each batch, it sends a pre-announcement message to both receiving ends, containing the batch number (e.g., "Batch-01"), the number of data entries (20), and the data size (10KB). The receiving ends then respond with "Confirmation". Upon receiving the "receive" response, the module initiates the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module. After all batches of transmission are completed, the multi-source data integration and storage module generates a transmission report containing "transmission target, transmission batch, number of successful transmissions (158), and number of failed transmissions (2, which were successfully retried)". This report is fed back to the core control and coordination module via the SPI bus. The core control and coordination module records the transmission report and update time (20240520143500) to its local memory and sends a "data update complete" notification to the device management backend. Upon receiving the notification, the backend updates the device status display interface. The AI ​​fault diagnosis system then begins to analyze the fault risks of the 10 stamping machines based on the newly received data. At this point, the entire data collaborative update process is complete.

[0036] In summary, Example 2, using the status monitoring data update of 10 stamping machines in an automotive parts production workshop as a scenario, fully presents the entire process of collaborative data update for RFID tag readers. First, the core control and collaboration module retrieves and collects environmental, distance, and power-related data to form an initial set; then, data anomalies are corrected through verification and completion; subsequently, the data is standardized, and special data is pushed for manual confirmation; next, semantically enhanced data is generated by combining external sensor data; finally, the data is transmitted to the target system in batches, and update information is fed back and recorded. This achieves closed-loop management of data from dumb resource devices from collection to application, adapting to the precise data update needs of industrial scenarios.

[0037] Example 3:

[0038] A method for collaborative data update of RFID tag readers for verifying the status of dumb resource equipment.

[0039] Based on the aforementioned RFID tag reader, this embodiment takes the inventory status monitoring data update of 50 shelves (dumb resource devices) in a logistics warehouse as an example to detail the complete process of the data collaborative update method. This process coordinates the linkage between various functional modules and the warehouse management system through the core control collaboration module to achieve full-link management from data collection and processing to final update, adapting to the data update needs of warehouses with multiple shelves and dynamic storage environments.

[0040] After the process is initiated, the collaborative data retrieval and collection phase begins. The core control and collaboration module, based on the 2-hour data collection cycle set by the warehouse management system, generates a data retrieval command containing the time range "20240610090000-20240610110000" and the data for "interference intensity, tag distance, RFID tag ID, and cargo weight." This command is sent via the SPI bus to the environmental interference dynamic response module and the distance adaptation power adjustment module. The environmental interference dynamic response module filters out interference records generated by warehouse forklifts (operating frequency 860 to 960 MHz) during that time period (e.g., strong interference on shelf A between 10:15 and 10:20), frequency band switching records (switching from 915 MHz to 2.4 GHz at 10:16), and the weight of goods on each shelf. According to the data (e.g., the load-bearing capacity of shelf A1 is 500kg±5kg), 100 data points are packaged into one frame and an acknowledgment signal is attached. The distance adaptation power adjustment module extracts the distance value between the corresponding time period and each shelf RFID tag (e.g., the distance to shelf B3 is stable at 2.5 to 2.6m), power adjustment value (18dBm), tag ID (e.g., "RFID-Shelf-B3-2024"), and goods storage time (e.g., the goods on shelf C5 have been stored for 72 hours). It is also packaged into 100 data points with acknowledgment signals. The two modules transmit the data synchronously to the multi-source data integration and storage module. After receiving and detecting the acknowledgment signal, the module sends back a success command. If it does not receive the acknowledgment signal within 500ms, it triggers a retransmission. Finally, a raw set containing 2 hours of status data for 50 shelves is formed.

[0041] Next, the data completion and verification phase begins. The core control and coordination module sends a verification command to the multi-source data integration and storage module. This module performs format verification and checksum comparison: it finds that 5 weight data entries for shelf A7 from 9:30 to 9:40 are missing, the label ID field for shelf D2 at 10:05 is incorrect, and the checksum of the distance data for shelf F4 at 9:50 does not match. After the abnormal information is fed back to the core control and coordination module via the SPI bus, a targeted supplementary transmission command is generated: the corresponding weight data for shelf A7 for the corresponding time period is supplemented to the environment module, and the label ID for shelf D2 and the distance data for shelf F4 are supplemented to the distance and power module. After the supplementary data is verified to be correct, the original data set is marked as "processable" and a verification completion signal is fed back.

[0042] The process then proceeds to the instruction processing and standardized data stage. The core control and coordination module issues processing instructions containing rules for "timestamp association, unified JSON format, and deduplication." The multi-source data integration and storage module associates data with the same timestamp (such as interference, distance, and label data for 10:00:00.000) at 200ms granularity. The association operation calculates the association confidence using a data fusion weighting algorithm, with the formula as follows: The environmental data at 10:30:00.100 and the distance data at 10:30:00.310 for shelf E3 were quantitatively analyzed. Based on the calculated association confidence results, the data was determined to be a weak association requiring manual confirmation. A confirmation list containing data details, deviation values, and numbers was generated and pushed to the warehouse management system. The remaining data was converted into JSON format containing "shelf number, timestamp, interference status, distance, power, tag ID, weight, and storage duration". After removing three duplicate data entries, a standardized set was formed, and a processing completion signal was fed back.

[0043] Next, the data generation phase for enhanced matching begins. The core control and coordination module instructs the multi-source data integration and storage module to initiate semantic enhancement and sends a request containing 50 shelf tag IDs and data types such as "goods quantity" and "location occupancy" via Wi-Fi connection to the warehouse camera system. The camera system returns the corresponding data within 400ms. During matching, a semantic enhancement confidence algorithm is used to calculate the matching degree, using the following formula: The system quantitatively evaluates the supplementary data, such as the quantity of goods and the occupancy of storage locations on the B3 shelf returned by the camera system, against the corresponding standardized data. After determining that the data is a valid match based on the calculation results, the supplementary data is injected to form semantically enhanced data, marked as "pending update status," and a signal indicating that the enhancement is complete is fed back.

[0044] Finally, the transmission feedback update phase begins. The core control and collaboration module, configured according to the warehouse management system, determines that the data will be transmitted to the inventory database and intelligent scheduling system via Wi-Fi (MQTT protocol). It sends a transmission command containing the target IP (inventory database: 192.168.2.100, scheduling system: 192.168.2.200). The multi-source data integration and storage module transmits the enhanced data in 12 batches, sending a pre-announcement message before each batch. After receiving confirmation, the transmission is initiated. Once all transmissions are complete, a report containing "target, batch, number of successful records (1180 records), and number of successful records after retrying failures (20 records)" is generated. The core control and collaboration module records this information and notifies the management system. The system updates the inventory display interface, and the intelligent scheduling system optimizes the allocation of storage locations based on the new data. The process then ends.

[0045] In summary, Example 3 uses the data update of 50 shelves in a logistics warehouse as a scenario to fully demonstrate the collaborative data update process of RFID tag readers. First, the core control and collaboration module retrieves environmental, distance, and power data at a 2-hour cycle and collects them into a raw set. Then, the data is verified, completed, and corrected for missing and incorrect data. Subsequently, the data is standardized, and data exceeding the threshold is pushed for manual confirmation. Next, semantically enhanced data is generated by combining data from the camera system. Finally, the data is transmitted in batches to the inventory database and scheduling system, and the results are fed back and recorded. The entire process realizes a closed loop of shelf data from collection to application, adapting to the data update requirements of dynamic storage scenarios with multiple shelves in warehouses.

[0046] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. An RFID tag reader / writer for verifying the status of dumb resource equipment, characterized in that, The reader / writer includes: an environmental interference dynamic response module, a distance adaptation power adjustment module, a multi-source data integration and storage module, and a core control and coordination module; The environmental interference dynamic response module is used to monitor electromagnetic signals in the industrial environment, identify interference characteristics, switch operating frequency bands or modulation methods, and capture and output dummy resource equipment status verification data. The distance adaptation power adjustment module: detects the distance to the RFID tag, adjusts the transmission power according to the distance, and reads and outputs RFID tag data and distance and power related data; The multi-source data integration and storage module receives data output from the environmental interference dynamic response module and the distance adaptation power adjustment module, and performs data verification, correlation, format unification and storage. The core control and coordination module is connected to the environmental interference dynamic response module, the distance adaptation power adjustment module, and the multi-source data integration and storage module, respectively. It sends control commands, receives feedback information from each module, and coordinates the work of each module.

2. The RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 1, characterized in that, The electromagnetic signal monitoring frequency of the environmental interference dynamic response module is 10 to 15 full-band scans per second. The interference feature identification includes the frequency range, intensity, and duration of the interference signal. The operating frequency band includes at least one of the 902 to 928 MHz and 2.4 to 2.4835 GHz bands. The modulation mode switching includes the conversion between ASK modulation and FSK modulation.

3. The RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 1, characterized in that, The distance detection frequency of the distance adaptation power adjustment module is once every 100ms; the transmission power is adjusted according to the distance range with the RFID tag, wherein the transmission power increases accordingly as the distance is greater; the output RFID tag data includes the tag ID and the device status parameters stored in the tag.

4. An RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 1, characterized in that, The multi-source data integration and storage module receives data via dual independent links. Data verification includes field integrity checks and checksum comparisons. When associating data, data with a timestamp deviation of 30 to 100 ms are considered to be data from the same time point. The stored data is archived according to the module source and collection time.

5. An RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 1, characterized in that, The core control coordination module communicates with other modules via an SPI bus. The bus supports multiple master-slave modes and can establish three independent communication links simultaneously. Control commands include command type, target module identifier, and data processing parameters.

6. A data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource equipment, the method being applicable to the RFID tag reader / writer for verifying the status of dumb resource equipment as described in any one of claims 1-5, characterized in that, The specific steps of this method are as follows: S100, collaborative data retrieval and collection: The core control and collaboration module sends data retrieval instructions to the environmental interference dynamic response module and the distance adaptation power adjustment module, and sends data reception instructions to the multi-source data integration and storage module; the environmental interference dynamic response module and the distance adaptation power adjustment module output data to the multi-source data integration and storage module respectively, and the multi-source data integration and storage module collects data according to module source and timestamp to form the original data set; S200, Triggering Data Verification and Completion: The core control and coordination module triggers the data verification process, and the multi-source data integration and storage module performs format verification on the original data set. When data is found to be missing or incomplete, the multi-source data integration and storage module feeds back to the core control and coordination module, which then sends a retransmission command to the corresponding module. After receiving the retransmitted data, the multi-source data integration and storage module verifies it again, and marks the data as processable after completion. S300, Instruction Processing of Standardized Data: Data processing instructions are sent to the multi-source data integration and storage module through the core control and coordination module. The multi-source data integration and storage module associates cross-module data using timestamps as the core dimension, unifies the data format and removes duplicate data to form a standardized data set. Among them, when associating cross-module data, a data fusion weight algorithm is used to calculate the association confidence. S400, Enhanced Matching and Data Generation: The core control coordination module sends semantic enhancement commands to the multi-source data integration and storage module. Simultaneously, the core control coordination module calls an external sensor system to acquire supplementary data and transmits it to the multi-source data integration and storage module. The multi-source data integration and storage module matches the supplementary data with the standardized dataset, injects information to generate semantically enhanced data, and marks it as pending update after verification. Among these steps, a semantic enhancement confidence algorithm is used to calculate the matching degree when matching the supplementary data with the standardized dataset. S500, determine transmission feedback update: the core control collaboration module determines the data transmission interface and target and sends the transmission command. The multi-source data integration and storage module transmits the semantically enhanced data to the device management backend database and the AI ​​fault diagnosis system. After the transmission is completed, the multi-source data integration and storage module feeds back the result to the core control collaboration module. The core control collaboration module records the update information and sends an update completion notification to the device management backend.

7. The data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 6, characterized in that, In S100, during the collaborative retrieval and collection of data, the data retrieval instruction sent by the core control coordination module includes a time range and a list of data types; the data output by the environmental interference dynamic response module includes at least one of interference frequency band records, frequency band switching records, and equipment voltage and temperature data; the data output by the distance adaptation power adjustment module includes at least one of distance monitoring values, power adjustment values, RFID tag IDs, and equipment runtime data; when the environmental interference dynamic response module and the distance adaptation power adjustment module transmit data, each predefined number of data entries carries a transmission confirmation signal; after receiving the confirmation signal, the multi-source data integration and storage module continues to receive subsequent data; if no confirmation signal is received within a preset time, the sending end retransmits the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module.

8. The data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 6, characterized in that, In S300, when the multi-source data integration and storage module associates cross-module data during the instruction processing of standardized data, it generates an association confirmation list for data marked as needing manual confirmation. The list includes the complete content of two data items, timestamp deviation value, and data number, and is pushed to the device management backend through the core control and collaboration module.

9. The data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 6, characterized in that, In the S400 process, when the external sensor system is called to obtain supplementary data during the enhanced matching data generation, a request-response mode is adopted. The request information includes a list of target RFID tag IDs and the required supplementary data type code. The response information must be returned within 500ms. If the timeout occurs, a retry mechanism is triggered. The supplementary data and the standardized data set are matched according to the dual dimensions of RFID tag ID + timestamp.

10. The data collaborative update method for an RFID tag reader / writer for verifying the status of dumb resource equipment according to claim 6, characterized in that, In step S500, during the transmission feedback update, the multi-source data integration and storage module transmits data according to a predefined batch size. Before transmission, a pre-announcement message containing batch information is sent to the receiving end. After the receiving end responds with a confirmation of receipt based on the pre-announcement message, it initiates the data set output by the environmental interference dynamic response module and the distance adaptation power adjustment module. After transmission is completed, the multi-source data integration and storage module generates a transmission report containing the transmission status.

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