Intelligent doorplate dynamic management system and method based on LORA technology

Abstract

The invention relates to the field of intelligent doorplate management, and particularly discloses an intelligent doorplate dynamic management system and method based on an LORA technology, which are characterized in that external heterogeneous source data such as OA, educational administration and the like are grabbed, cleaned and packaged in a standardized manner at a front end through protocol adaptation and data engine technologies, and information islands are broken to realize automatic content production; the transmission layer reconstructs network data into high-penetrability LORA radio-frequency signals for wide-area broadcasting by utilizing a cloud compiling and gateway protocol conversion mechanism; and the terminal side adopts a periodic wake-up strategy based on a CAD mechanism, and drives the electronic ink screen to refresh and immediately and automatically cut off the power supply only after the verification of the effective signaling is passed. Therefore, real-time synchronization of the physical identification and the digital service is realized without manual intervention through full-link data closed-loop circulation, and meanwhile, extremely-low-power-consumption long-term operation of the system is ensured by utilizing a bistable display characteristic.

Description

Technical Field

[0001] This application relates to the field of intelligent doorplate management, and more specifically, to an intelligent doorplate dynamic management system and method based on LoRa technology. Background Technology

[0002] With the rapid development of smart cities and digital office management, enterprises, institutions, office buildings, and campuses are increasingly demanding more sophisticated management of space resources. In these scenarios, information exchange is frequent, including changes in office staff, meeting room occupancy, and adjustments to course schedules. Traditional static signage can no longer meet the urgent needs of modern management for real-time and interactive information.

[0003] Specifically, existing doorplate management solutions have significant technical limitations in practical applications. Traditional physical doorplates are typically made of metal or acrylic; once the information is recorded, it is permanently fixed, and any changes require re-creation and reinstallation, resulting in not only delays but also significant waste of manpower and resources. While some electronic doorplates based on LCD or LED have emerged, these solutions mostly suffer from excessive power consumption, relying on continuous wired power or frequent battery replacements, leading to complex deployment and heavy maintenance burdens. More importantly, existing electronic doorplate management systems are often isolated information silos, unable to achieve deep data interoperability with users' OA office systems, academic affairs systems, or HR scheduling systems. This necessitates manual re-entry of doorplate display content, easily causing information asynchrony and management chaos. Furthermore, at the wireless communication level, traditional Wi-Fi or Bluetooth solutions are insufficient in terms of penetration and coverage distance to meet the networking needs of large buildings or complex campuses, and struggle to maintain low power consumption while ensuring long-distance transmission.

[0004] Therefore, in order to break down the barriers between physical identification and digital information and improve the intelligence level and operational efficiency of space management, an optimized intelligent doorplate dynamic management system based on LoRa technology is desired. Summary of the Invention

[0005] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a smart doorplate dynamic management system and method based on LoRa technology.

[0006] According to one aspect of this application, a method for dynamic management of smart doorplates based on LoRa technology is provided, comprising: S1: Capture and clean external source data to transform it into a raw object stream that can be recognized within the system; S2: Use the data engine to perform semantic parsing and field mapping on the original object stream, and encapsulate the mapped data into standardized unified protocol data packets through format conversion technology; S3: The cloud management platform receives unified protocol data packets and compiles them into control commands containing display parameters. It also performs address addressing and routing encapsulation based on the network topology location of the target terminal to generate downlink command frames that conform to the low-power wide area network protocol. S4: The gateway device receives downlink command frames through the backhaul link, and uses its internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. S5: The smart doorplate terminal captures radio frequency modulation signals in the periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on them through the communication module to parse out the display rendering data; S6: Uses display rendering data to drive the e-ink screen controller to perform electrophoretic display updates to form visible human-readable information, and cuts off the power supply to the communication module and drive circuit after the update is completed to automatically switch back to deep sleep mode.

[0007] According to another aspect of this application, a smart doorplate dynamic management system based on LoRa technology is provided, comprising: The data capture and cleaning module is used to perform step S1: capture and clean external source data to transform it into a raw object stream that can be recognized by the system. The field mapping module is used to perform step S2: using the data engine to perform semantic parsing and field mapping on the original object stream, and encapsulating the mapped data into a standardized unified protocol data packet through format conversion technology; The downlink command frame generation module is used to execute step S3: The cloud management platform receives the unified protocol data packet and compiles it into a control command containing display parameters, and performs address addressing and routing encapsulation in combination with the network topology location of the target terminal to generate a downlink command frame that conforms to the low power wide area network protocol. The radio frequency broadcast modulation module is used to perform step S4: the gateway device receives downlink command frames through the backhaul link, and uses the internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. The signal demodulation and verification module is used to perform step S5: the smart doorplate terminal captures the radio frequency modulation signal in the periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on it through the communication module to parse out the display rendering data; The electrophoretic display update module is used to perform step S6: using display rendering data to drive the electronic ink screen controller to perform electrophoretic display update to form visible human-readable information, and after the update is completed, cutting off the power supply to the communication module and the drive circuit to automatically switch back to deep sleep mode.

[0008] Compared with existing technologies, this application provides a smart doorplate dynamic management system and method based on LoRa technology. At the front end, through protocol adaptation and data engine technology, it captures, cleans, and standardizes heterogeneous data from external sources such as OA and academic affairs, breaking down information silos and achieving automated content production. At the transmission layer, it utilizes cloud compilation and gateway protocol conversion mechanisms to reconstruct network data into highly penetrating LoRa radio frequency signals for wide-area broadcasting. At the terminal side, it employs a periodic wake-up strategy based on a CAD mechanism, only driving the e-ink screen to refresh after valid signaling verification and then automatically cutting off the power. In this way, through a closed-loop data flow across the entire link, real-time synchronization of physical identification and digital services is achieved without manual intervention, while the bistable display characteristics ensure extremely low power consumption and long-term operation of the system. Attached Figure Description

[0009] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0010] Figure 1 This is a flowchart of a smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application; Figure 2 This is a schematic diagram of the data flow in the smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application; Figure 3 This is a flowchart of step S4 of the smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application; Figure 4 This is a flowchart of step S6 of the smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application; Figure 5 This is a block diagram of a smart doorplate dynamic management system based on LoRa technology according to an embodiment of this application. Detailed Implementation

[0011] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0012] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0013] While this application makes various references to certain modules of the systems according to embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The modules described are merely illustrative, and different aspects of the systems and methods may use different modules.

[0014] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0015] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0016] To address the shortcomings of traditional doorplate management, such as reliance on slow manual updates, high energy consumption and difficult maintenance of continuously powered display terminals, and data silos caused by a lack of interfaces with OA or academic affairs systems, this application proposes a dynamic intelligent doorplate management method based on LoRa technology. This mechanism first actively captures, cleans, and semantically analyzes data from various heterogeneous external business sources through a backend data engine, reconstructing it into standardized unified protocol data packets to break down data barriers. Then, through cloud routing and gateway physical layer protocol conversion, logical data is compiled into radio frequency modulation signals with long-distance penetration capabilities for precise distribution. Finally, in conjunction with the periodic listening strategy of the terminal device, after ensuring the validity of instructions using cyclic redundancy check, the e-ink screen is driven to update the image using bistable characteristics. After the operation is completed, communication and power supply to the drive circuit are automatically cut off, entering deep sleep mode. This achieves real-time, seamless synchronization of business data on the screen while completely solving the energy consumption bottleneck of long-term maintenance-free operation through intermittent working mode.

[0017] Figure 1 This is a flowchart of a smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application. Figure 2 This is a schematic diagram of the data flow in the smart doorplate dynamic management method based on LoRa technology according to an embodiment of this application. Figure 1 and Figure 2 As shown, the intelligent doorplate dynamic management method based on LoRa technology according to an embodiment of this application includes the following steps: S1, capturing and cleaning external source data to transform it into a raw object stream that can be recognized by the system; S2, using a data engine to perform semantic parsing and field mapping on the raw object stream, and encapsulating the mapped data into a standardized unified protocol data packet through format conversion technology; S3, the cloud management platform receives the unified protocol data packet and compiles it into control instructions containing display parameters, and performs address addressing and routing encapsulation in combination with the network topology location of the target terminal to generate a downlink command frame that conforms to the low-power wide area network protocol; S4, the gateway device receives the downlink command frame through the backhaul link, and uses the internal processor to convert the network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulation signals to the coverage area; S5, the intelligent doorplate terminal captures the radio frequency modulation signal in a periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on it through the communication module to parse out the display rendering data; S6: using the display rendering data to drive the electronic ink screen controller to perform electrophoretic display updates to form visible human-readable information, and cutting off the power supply to the communication module and the drive circuit after the update is completed to automatically switch back to deep sleep mode.

[0018] Specifically, in step S1, external source data is captured and cleaned to transform it into a raw object stream recognizable within the system. It should be understood that source data output from heterogeneous business systems such as OA office automation, academic affairs management, or HR scheduling exhibits significant differences in communication protocols, encoding formats, and field definitions. Furthermore, directly acquired data often contains redundant communication information or garbled characters unrelated to business operations. Without unified pre-processing, it cannot be directly recognized by the system kernel. Therefore, in the technical solution of this application, external source data is captured and cleaned to transform it into a raw object stream recognizable within the system, thereby shielding the access differences of the underlying heterogeneous data sources and eliminating data noise. This ensures that the data input to the core engine possesses high purity and format uniformity, laying a data foundation for subsequent accurate instruction generation.

[0019] More specifically, in the embodiments of this application, step S1 includes: performing protocol identification and adapter instantiation based on feature matching on external source data to obtain a protocol adapter component, and establishing a communication handshake with the data source using the protocol adapter component; calling the unpacking method of the protocol adapter component to strip the communication layer protocol header, extracting the core original business payload, and performing character set standardization transcoding and invalid field filtering cleaning operations on the original business payload to obtain cleaned structured data; and performing serialization conversion on the cleaned structured data based on a predefined intermediate layer data definition to obtain the original object stream.

[0020] Specifically, in a concrete example of this application, the access layer first detects the header feature bytes or port identifiers of the external source data. By comparing them with a pre-built protocol feature library, it accurately identifies the specific protocol type used by the external data source, such as identifying the SOAP protocol used by the academic affairs system. Then, it uses the factory pattern to instantiate the corresponding SOAP protocol adapter component to complete the authentication handshake connection. Subsequently, the adapter component parses the received data packets, strips communication protocol headers such as SOAP Envelope, and extracts the original business payload in XML format containing course names and classroom occupancy. The data cleaning module then performs transcoding operations on the original business payload to uniformly convert GBK encoding to UTF-8 format, and traverses the XML nodes to remove null tags or illegal control characters to generate standard cleaned structured data. Finally, the serialization engine maps the structured data into memory objects in binary or POJO form according to the internal data exchange standard, and encapsulates it into a raw object stream in sequence for output to the downstream module.

[0021] Specifically, in step S2, a data engine is used to perform semantic parsing and field mapping on the original object stream, and the mapped data is encapsulated into a standardized unified protocol data packet using format conversion technology. It should be understood that although the original object stream generated in the preceding steps has achieved binary data formatting, it still retains the heterogeneous field definitions and logical structures of the source system, and has not yet been given specific business semantics suitable for electronic doorplate display. Furthermore, there is a significant mapping gap between the field naming rules of different business systems and the hardware display driver interface of the doorplate terminal; direct transmission would result in the terminal being unable to correctly parse and render the data. Therefore, in the technical solution of this application, a data engine is further used to perform semantic parsing and field mapping on the original object stream, and the mapped data is encapsulated into a standardized unified protocol data packet using format conversion technology. This gives the data clear business attributes and masks the differences in field definitions between heterogeneous systems. In this way, discrete source-end business data can be reconstructed into a system-wide standardized instruction format, ensuring the logical consistency and parsability of data on the transmission link and display terminal in subsequent stages.

[0022] More specifically, in the embodiments of this application, step S2 includes: extracting key business entities from the original object stream based on semantic analysis to obtain a set of business entities; performing intelligent field mapping and data normalization verification on the set of business entities to obtain standard intermediate data containing standard structure descriptions; and performing XSLT transformation and unified protocol encapsulation on the standard intermediate data containing standard structure descriptions to obtain unified protocol data packets.

[0023] Accordingly, the original object stream is subjected to semantic analysis to extract key business entities to obtain a set of business entities. It should be understood that although the original object stream generated by the preceding processing achieves a unified encoding format, the data fields it carries still follow the naming rules and logical structure of the heterogeneous source system. This includes a large amount of redundant metadata, such as database indexes and operation serial numbers, which are meaningless for terminal display. If the system kernel lacks a deep understanding of the data content, it will be unable to accurately locate the core information that truly needs to be displayed from the massive amount of data. Therefore, in the technical solution of this application, the original object stream is further subjected to semantic analysis to extract key business entities to obtain a set of business entities. This allows for the intelligent identification and extraction of business elements with actual display value from the unstructured heterogeneous data stream. This effectively eliminates interfering data unrelated to the address card function, ensuring that subsequent processing focuses only on payloads with clear business semantics, eliminating data noise while providing standardized information input for accurate field mapping.

[0024] Specifically, in one example of this application, the original object stream in binary form is first deserialized into a memory-accessible list of key-value pairs. Then, a pre-set industry domain knowledge base and regular expression rule set are loaded, and a deep scan is performed on each key-value pair in the list. The system uses natural language processing algorithms to calculate the semantic similarity between the key name strings and the standard business dictionary. For example, fields identified as "kcmc" or "mtg_topic" in the source data are uniformly identified as business topic entities. At the same time, regular expression rules are used to verify the numerical format, and strings that conform to the calendar or clock format are determined to be time entities. Finally, the parsing engine automatically filters out system log data with confidence levels lower than the standard based on a preset business relevance threshold, and extracts and aggregates all data items that pass the verification and have clear semantic labels, thereby constructing a compact and clearly defined set of business entities.

[0025] Accordingly, intelligent field mapping and data normalization verification are performed on the business entity set to obtain standard intermediate data containing standard structural descriptions. It should be understood that although the business entity set extracted in the previous steps clarifies the business meaning of the data, its character length, date format, and data type still retain the original state of the source system. Furthermore, each entity has not yet established a definite coordinate or logical correspondence with the specific physical screen layout area of ​​the electronic doorplate terminal. If directly sent, it is highly likely that excessive data length or format incompatibility will lead to terminal display misalignment, text overflow, or even rendering failure. Therefore, in the technical solution of this application, intelligent field mapping and data normalization verification are further performed on the business entity set to obtain standard intermediate data containing standard structural descriptions. This establishes a precise adaptation mechanism between logical data and physical display resources and enforces a unified data content presentation standard. This ensures that the data transmitted to the terminal strictly conforms to the input requirements of the hardware driver layer, guaranteeing that the final screen display effect is both complete and aesthetically pleasing, and completely eliminating display anomalies caused by data format differences.

[0026] Specifically, in a specific example of this application, the data processing engine first loads the screen layout configuration file and field mapping table defined for the target door terminal model, and then traverses the input set of business entities based on this. The system searches for the corresponding screen display area identifier in the mapping table according to the semantic tag of each business entity. For example, it forces the entity identified as a course topic to be mapped to the title display area at the top of the screen, and maps the entity identified as time to the status area on the side, thereby establishing the binding relationship between logical fields and physical areas. Next, it performs strict normalization processing on the mapped field values, uses a preset formatting function to uniformly convert heterogeneous date and time strings into a short time-division format that conforms to the screen display standard, and calculates the pixel width of the text data in real time. Once it detects that the content of a field exceeds the display boundary of the corresponding physical area, it immediately triggers an automatic truncation or abbreviation algorithm to adapt the text. Finally, it reassembles all the mapped and cleaned fields into standard intermediate data in XML or JSON format that conforms to the system's internal standard interface definition and contains a standard structure description.

[0027] Accordingly, standard intermediate data containing standard structural descriptions undergoes XSLT conversion and unified protocol encapsulation to obtain unified protocol data packets. It should be understood that although the previously generated data possesses a standardized logical structure, it is essentially still a general exchange format based on text descriptions. The data volume is relatively large and lacks the control signaling and security identifiers required for transmission in the underlying communication link. Directly transmitting this data in a low-power wide-area network (LPWAN) with extremely limited bandwidth and power sensitivity would not only cause severe channel congestion and transmission delays but also prevent terminal devices from correctly identifying instruction types and boundaries due to the lack of necessary communication protocol headers. Therefore, in the technical solution of this application, standard intermediate data containing standard structural descriptions is further subjected to XSLT conversion and unified protocol encapsulation to obtain unified protocol data packets. This transforms the application layer's logical data into a highly compact binary instruction stream that conforms to the underlying transmission protocol specifications. This maximizes the compression of the payload volume to reduce air interface transmission time while adding control information to the data packets to ensure transmission reliability and security, ensuring that instructions can be efficiently routed by the network layer and accurately parsed by the terminal layer.

[0028] Specifically, in one example of this application, the protocol conversion engine first calls a pre-loaded extensible stylesheet language conversion processor to load a style conversion script customized for the target terminal firmware version. It then performs a structural transformation operation on the input standard intermediate data containing standard structural descriptions, converting redundant tagged text data into a compact binary rendering instruction set that the device controller can directly execute. Next, it constructs a data packet header according to the system-defined private communication protocol specifications, filling it with the protocol version number, instruction function code, and encryption algorithm identifier bit by bit. Finally, it uses a generator polynomial algorithm to perform cyclic redundancy check calculations on the converted instruction set to generate a data integrity check code. Finally, the system concatenates the constructed protocol header, binary rendering instruction set, and check code in strict byte order, ultimately packaging them into a unified protocol data packet with a complete structure, self-describing capabilities, and suitable for wireless channel transmission.

[0029] Specifically, in step S3, the cloud management platform receives the unified protocol data packet and compiles it into control instructions containing display parameters. It then performs address addressing and routing encapsulation based on the target terminal's network topology location to generate a downlink command frame conforming to the Low Power Wide Area Network (LPWAN) protocol. It should be understood that since the previously generated unified protocol data packet only carries the display logic at the service layer and does not yet include the network address, radio frequency parameters, and security encryption encapsulation required for LPWAN physical layer transmission, and if the transmission rate is not adaptively adjusted according to the current wireless channel environment or duplicate data is not intercepted, it will lead to unnecessary power consumption and reduced spectrum utilization in the terminal device. Therefore, in the technical solution of this application, the cloud management platform receives unified protocol data packets and compiles them into control commands containing display parameters. It then performs address addressing and route encapsulation based on the network topology location of the target terminal to generate downlink command frames conforming to the Low Power Wide Area Network (LPWAN) protocol. Specifically, this includes compiling and differentiating the unified protocol data packets to obtain the command payload; performing adaptive rate routing calculation based on link quality on the command payload to obtain a route configuration set; encrypting the command payload to obtain a ciphertext payload; and encapsulating the ciphertext payload with LoRaWAN protocol frames to obtain the downlink command frame. This constructs secure transmission data frames adapted to physical channel characteristics and optimizes transmission energy efficiency. This ensures that logical commands are accurately routed to specific physical terminals in complex wireless network topologies, while minimizing communication power consumption through differentiated updates and link adaptation mechanisms.

[0030] More specifically, in the embodiments of this application, step S3 includes: performing instruction compilation and differential update determination on the unified protocol data packet to obtain the instruction payload; performing adaptive rate routing calculation based on link quality on the instruction payload to obtain the route configuration set; encrypting the instruction payload to obtain the ciphertext payload; and encapsulating the ciphertext payload with LoRaWAN protocol frames to obtain the downlink instruction frame.

[0031] Accordingly, the unified protocol data packets are compiled and differentiated for update determination to obtain the instruction payload. It is understandable that the unified protocol data packets received by the cloud may contain duplicate instructions that are completely identical to the content currently displayed on the terminal, or that retransmitting all data would consume a significant amount of wireless transmission bandwidth and terminal power. In low-power wide-area network scenarios, any extra bit transmission will significantly shorten battery life, and directly transmitting the entire amount of data clearly does not conform to the system's energy-saving design principles. Therefore, in the technical solution of this application, the unified protocol data packets are further compiled and differentiated for update determination to obtain the instruction payload, thereby intercepting redundant communication at the source and implementing an on-demand update strategy. This ensures that only data differences with actual update value are transmitted through the wireless channel, thereby significantly reducing airborne transmission time and extending the battery life of the terminal device.

[0032] In a specific example of this application, the cloud instruction processing engine first deconstructs the input unified protocol data packet, extracting the target device ID and core display data block contained therein. The system then queries the cache database for the state snapshot of the data sent to the device in the previous frame, calculates the hash fingerprint of the current data block and the historical snapshot using MD5 or SHA-256 algorithms respectively, and performs a strict comparison between the two. Once the fingerprints match, the system determines that no update is needed and directly discards the current instruction. Otherwise, if the fingerprints are different, the system further compares the binary bitmaps of the old and new data, extracts only the changed pixel areas or text fields, and calls the LZW lossless compression algorithm to encode and compile these differences. At the same time, the system marks the local refresh or global refresh type in the header according to the size of the difference data, and finally generates an instruction payload with an extremely optimized size.

[0033] Accordingly, adaptive rate routing calculation based on link quality is performed on the command payload to obtain a route configuration set. It should be understood that wireless signals propagating in complex building environments are affected by factors such as distance, wall obstruction, and electromagnetic interference, causing the communication link quality of terminal devices at different locations to change dynamically. If fixed and conservative low-rate transmission parameters are always used, although reliability can be guaranteed, it will result in a serious waste of channel resources and an unnecessary increase in terminal receiving power consumption; conversely, blindly using high rates may lead to packet loss and retransmission. Therefore, in the technical solution of this application, adaptive rate routing calculation based on link quality is further performed on the command payload to obtain a route configuration set, thereby dynamically matching the optimal physical layer communication parameters for each specific downlink transmission task. This ensures successful delivery of commands while minimizing the signal's flight time, thereby reducing the overall network collision probability and significantly improving system spectral efficiency.

[0034] In a specific example of this application, the routing calculation engine first retrieves the physical layer address and associated optimal gateway list of the target device in the network topology mapping table based on the logical ID of the instruction target device. Simultaneously, it retrieves historical link statistics reported by the gateway during the terminal's most recent uplink communication, including the average signal-to-noise ratio and received signal strength indication value. The system then evaluates the current link budget margin using a preset channel fading model and calculates the target spreading factor that can be used while meeting the demodulation signal-to-noise ratio threshold in real time using an adaptive data rate algorithm model. The calculation logic is as follows: ;in, This represents the target spreading factor for this downlink transmission, and its value is typically constrained to be an integer between 7 and 12. This represents the minimum spreading factor allowed by the network protocol, corresponding to the maximum data rate; This indicates the spreading factor used by the current terminal in its last communication. This indicates the floor function; This represents the measured signal-to-noise ratio when the gateway most recently received a signal from this terminal; This represents the theoretical demodulation signal-to-noise ratio threshold value required by the demodulator under the current spreading factor; This indicates a safety margin reserved to cope with the rapid fading of the wireless channel, typically ranging from 3 to 5 dB; This represents the step size for improving the signal-to-noise ratio (SNR) required to reduce the spreading factor by one level, typically 2.5 dB. Through the calculation using the above formula, the system can accurately quantify the current channel quality's margin of error relative to demodulation requirements and decide whether to reduce the spreading factor to increase the transmission rate. If the calculation results indicate excellent channel quality, the processor will generate configuration data containing a lower spreading factor, corresponding bandwidth, and transmit power parameters. These physical layer parameters will then be integrated and packaged with the target gateway ID and routing path information to ultimately construct a routing configuration set guiding subsequent signal transmission.

[0035] Accordingly, the instruction payload is encrypted to obtain a ciphertext payload, and then encapsulated with LoRaWAN protocol frames to obtain a downlink instruction frame. It should be understood that due to the inherently open nature of wireless communication media, plaintext data broadcast in the air is highly susceptible to security risks such as malicious eavesdropping, tampering, or replay attacks by third parties. Furthermore, raw data streams lacking standard link-layer protocol headers cannot be correctly identified by standardized terminal radio frequency protocol stacks regarding address and instruction boundaries. Therefore, in the technical solution of this application, the instruction payload is further encrypted to obtain a ciphertext payload, and then encapsulated with LoRaWAN protocol frames to obtain a downlink instruction frame. This constructs a secure transmission channel with high confidentiality and integrity protection mechanisms and endows data packets with a physical structure that strictly conforms to network standards. This ensures that core business instructions are only visible to legitimate terminals holding specific decryption keys, effectively defending against unauthorized access and data injection attacks, while guaranteeing that the transmission frame can be accurately parsed by all hardware devices conforming to the LoRaWAN specification.

[0036] In a specific example of this application, the dedicated application session key pre-installed in the system security domain is first read. The advanced encryption standard AES-128 algorithm is invoked, and encryption operations are performed on the input instruction payload in counter mode (CTR) to transform plaintext business data into ciphertext payload without semantic features. Subsequently, the protocol encapsulation engine strictly constructs the frame structure according to the LoRaWAN link layer specification, first generating a MAC header identifying the data packet type, and constructing a frame header containing the target terminal device's network address, frame control word, and a frame counter for replay attack prevention. Next, the computing unit uses the network session key to perform calculations on the combination of the header information and the ciphertext payload based on the AES-CMAC algorithm, generating a four-byte message integrity checksum for verifying the legality and integrity of the data source. Finally, the encapsulation module concatenates the MAC header, frame header, port number identifier, ciphertext payload, and message integrity checksum according to standard byte order, ultimately generating a structurally complete downlink instruction frame with dual security protection.

[0037] Specifically, in step S4, the gateway device receives downlink command frames via the backhaul link and uses its internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. It should be understood that since the downlink command frames sent from the cloud are essentially digital logic signals transmitted via wired networks, they cannot directly propagate over long distances in free space. Furthermore, different countries and regions have strict duty cycle and transmission timing restrictions on the use of radio spectrum. Without precise transmission scheduling and analog signal modulation, signals may fail to radiate or cause channel collisions due to illegal transmissions. Therefore, in the technical solution of this application, the gateway device receives downlink command frames via the backhaul link and uses its internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. This crosses the boundary between the digital network and physical space, converting logical commands into electromagnetic wave signals with strong anti-interference capabilities. This ensures that control commands, while strictly adhering to spectrum regulations, utilize the gain advantage of spread spectrum technology to penetrate building obstructions and accurately cover target terminals within a wide area.

[0038] Figure 3 This is a flowchart illustrating a method for dynamic management of smart doorplates based on LoRa technology according to an embodiment of this application. The flowchart describes how a gateway device receives downlink command frames via a backhaul link, converts network protocol data into physical layer protocol data using an internal processor, and performs radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. Figure 3 As shown, step S4 includes: S41, performing downlink instruction buffering and timing scheduling on the downlink instruction frame to obtain the baseband data to be modulated; S42, reading instruction header metadata to configure radio frequency parameters, mapping the baseband data to be modulated into a linear frequency modulation signal whose frequency changes linearly with time, and synthesizing a digital IQ signal stream containing in-phase and quadrature components accordingly; S43, performing digital-to-analog conversion and radio frequency power amplification and broadcasting on the digital IQ signal stream to obtain a radio frequency modulated signal.

[0039] Accordingly, in step S41, downlink command buffering and timing scheduling are performed on the downlink command frame to obtain the baseband data to be modulated. It should be understood that, because the LoRaWAN communication protocol is based on a strict time-division duplex and receive window mechanism, and gateway devices operating in unlicensed spectrum must strictly comply with radio management duty cycle regulations, if the gateway directly broadcasts asynchronously after receiving data from the cloud without scheduling, it is highly likely to fail to communicate due to missing the terminal's wake-up window, which lasts only a few milliseconds, or to violate regulations by occupying the channel due to timeout. Therefore, in the technical solution of this application, downlink command buffering and timing scheduling are further performed on the downlink command frame to obtain the baseband data to be modulated, thereby constructing a transmit queue management mechanism based on precise timestamps and establishing transmit compliance. This ensures that each frame of data can be precisely delivered in strict alignment with the target terminal's receive time slot, maximizing channel utilization while meeting spectrum regulatory constraints.

[0040] Specifically, in one example of this application, the main control processor inside the gateway first stores the downlink command frame received through the network interface into an internal high-speed first-in-first-out buffer queue to smooth network jitter and prevent packet loss caused by sudden traffic. Next, the timing scheduler parses the absolute timestamp or relative delay parameter attached to the header of the command frame, and combines it with the nanosecond-level reference clock provided by the GPS timing module to accurately calculate the exact microsecond moment when the frame signal should be transmitted in physical space. At the same time, the system reads the historical cumulative transmission duration data of the gateway's current operating frequency band, estimates its flight time in the air by combining the spreading factor and payload length of the command, and performs a strict duty cycle pre-check calculation. Only when it is confirmed that the transmission will not cause the cumulative duty cycle to exceed the statutory threshold (such as 1%) and the time slot is not occupied by high-priority signaling will the transmission window be locked. Finally, in a specific instruction cycle before the scheduled transmission time, the processor pushes the instruction data to the input buffer of the baseband chip through the internal high-speed bus, and finally generates the ready-to-modulate baseband data.

[0041] Accordingly, in step S42, the instruction header metadata is read to configure the radio frequency parameters, and the baseband data to be modulated is mapped to a linear frequency modulated (LFM) signal whose frequency changes linearly with time. Based on this, a digital IQ signal stream containing in-phase and quadrature components is synthesized. It should be understood that since the original baseband data is only binary logic high and low levels, without spread spectrum modulation, its anti-interference capability in complex wireless channels is extremely weak and its transmission distance is limited. The core advantage of LoRa technology lies in using LFM spread spectrum technology to achieve extremely high receiving sensitivity at the cost of bandwidth. Therefore, in the technical solution of this application, the instruction header metadata is further read to configure the radio frequency parameters, and the baseband data to be modulated is mapped to a LFM signal whose frequency changes linearly with time. Based on this, a digital IQ signal stream containing in-phase and quadrature components is synthesized, thereby expanding the narrowband digital information into wideband analog waveform characteristics. This endows the signal with extremely strong noise and multipath fading resistance, allowing it to be demodulated by the terminal even in environments with extremely low signal-to-noise ratios.

[0042] Specifically, in one particular example of this application, the baseband processor first parses the center frequency, bandwidth, and spreading factor parameters specified in the instruction header metadata, and initializes the RF link register accordingly. Subsequently, the modulation engine, based on the Chirp Spread Spectrum modulation principle, divides the input baseband data to be modulated into symbol groups bit by bit. Each symbol value determines an initial frequency offset and drives the frequency synthesizer to generate a Chirp waveform whose frequency increases or decreases linearly with time, i.e., a linear frequency modulation signal. The system calculates the instantaneous phase of the waveform at each sampling moment in real time, and uses trigonometric function transformation logic to calculate the cosine component as in-phase path data and the sine component as quadrature path data, and finally synthesizes two parallel and phase-orthogonal digital IQ signal streams.

[0043] Accordingly, in step S43, the digital IQ signal stream undergoes digital-to-analog conversion and radio frequency power amplification and broadcasting to obtain a radio frequency modulated signal. It should be understood that since the IQ signal stream generated in the digital domain exists only in the processor's logic unit and is a discrete mathematical expression, it cannot directly drive the antenna to generate electromagnetic radiation. Furthermore, to cover a wide physical area, the signal must have sufficient power density and the correct carrier frequency. Therefore, in the technical solution of this application, the digital IQ signal stream is further subjected to digital-to-analog conversion and radio frequency power amplification and broadcasting to obtain a radio frequency modulated signal, thereby completing the final transition from the digital logic domain to the physical analog domain. This allows the spread-spectrum baseband information to be loaded onto a high-frequency carrier and its energy enhanced, ensuring that electromagnetic waves can effectively radiate to distant locations across physical barriers.

[0044] Specifically, in one particular example of this application, a high-speed digital-to-analog converter first converts two discrete digital IQ signal streams at a high sampling rate, outputting a pair of continuous analog baseband signals. Subsequently, a quadrature modulator uses a radio frequency carrier generated by a local oscillator to mix these two analog signals, shifting the baseband spectrum to a specified center frequency such as 470MHz or 868MHz without distortion. Next, a radio frequency power amplifier linearly amplifies the weak radio frequency signal, ensuring its output power accurately reaches the system's set transmit power level (e.g., 20dBm). Finally, the amplified current directly drives an omnidirectional antenna to generate an alternating electromagnetic field, thereby radiating a radio frequency modulated signal carrying complete service information omnidirectionally into the surrounding space.

[0045] Specifically, in step S5, the smart doorplate terminal captures the radio frequency modulation signal in a periodic wake-up state and performs signal demodulation and cyclic redundancy check processing through the communication module to parse the display rendering data. It should be understood that since the smart doorplate is mainly powered by a battery, prolonged use in a receiving state will quickly deplete its power. Furthermore, the wireless channel is filled with various interferences and radio frequency noise not originating from the system itself. Therefore, the terminal must possess the ability to accurately identify valid system signals at extremely low duty cycles. Thus, in the technical solution of this application, the smart doorplate terminal captures the radio frequency modulation signal in a periodic wake-up state and performs signal demodulation and cyclic redundancy check processing through the communication module to parse the display rendering data, thereby balancing an extremely low-power sleep strategy with a highly reliable data reception mechanism. This ensures that the terminal only consumes energy for subsequent processing when it confirms that it has received a valid control command sent to itself, thereby significantly extending the device's lifespan.

[0046] More specifically, in the embodiments of this application, step S5 includes: performing channel activity detection and signal locking based on the CAD mechanism on the radio frequency modulated signal to obtain the original baseband sampling stream; performing CSS demodulation and frame integrity verification on the original baseband sampling stream to obtain valid encrypted frame data; and performing AES decryption and display instruction extraction on the valid encrypted frame data to obtain display rendering data for screen refresh.

[0047] Accordingly, channel activity detection and signal locking based on the CAD mechanism are performed on the RF modulated signal to obtain the original baseband sampling stream. It should be understood that since smart doorplate devices are in deep sleep mode most of the time to maintain microampere-level power consumption, blindly activating the entire receiving link for long-term listening every time they are woken up would result in huge unnecessary power consumption. Furthermore, activating the high-power demodulation module before a valid signal is detected in the wireless environment is unnecessary. Therefore, in the technical solution of this application, channel activity detection and signal locking based on the CAD mechanism are further performed on the RF modulated signal to obtain the original baseband sampling stream, thereby utilizing extremely low-power detection technology to quickly determine whether a valid preamble signal exists in the air. This enables an on-demand intelligent wake-up strategy, fully activating the receiving circuit only when LoRa signal activity is confirmed on the channel, thus keeping the average standby current at an extremely low level.

[0048] In a specific example of this application, the timer inside the smart doorplate terminal drives the radio frequency front-end into channel activity detection mode every fixed short period (e.g., 1 second). In this mode, the radio frequency chip only activates part of the receiving link, quickly captures the radio frequency modulation signal in the air and performs correlation matching calculation with the locally pre-stored standard LoRa preamble waveform. The system determines whether there is a valid LoRa spread spectrum signal in the current channel based on the correlation peak value of the calculation output. If the peak value is lower than a preset threshold, the chip immediately shuts down and returns to sleep mode. Conversely, if a valid preamble feature is detected, the system quickly adjusts the frequency and locks the timing phase of the signal, then activates the full-function receiving mode, starts the analog-to-digital converter to continuously sample the subsequent data payload, and finally generates a digital original baseband sample stream containing complete signal information.

[0049] Accordingly, the original baseband sample stream is demodulated using CSS and its frame integrity is verified to obtain valid encrypted frame data. It should be understood that, since the original baseband sample stream physically represents a digital sequence of broadband waveform characteristics modulated by linear frequency modulation (LFM), it does not directly correspond to a binary bit stream that a computer can process. Furthermore, wireless radio frequency signals are highly susceptible to multipath fading or interference from environmental electromagnetic noise during spatial propagation, which can lead to bit flips or packet incompleteness in the received data. Therefore, in the technical solution of this application, the original baseband sample stream is further demodulated using CSS and its frame integrity is verified to obtain valid encrypted frame data. This utilizes the spread spectrum processing gain to recover the digital signal from the noise and constructs a strict data quality firewall. This ensures that the data delivered to the upper-layer application is accurate both physically and logically, effectively preventing instruction parsing errors or abnormal system behavior caused by channel errors.

[0050] In a specific example of this application, the digital baseband demodulator first performs pointwise complex multiplication of the received raw baseband sample stream with a locally generated downlink chirp reference signal with opposite frequency change slopes to eliminate the linear frequency variation characteristic of the signal over time, thus completing the demodulation operation. Next, the processor performs a fast Fourier transform on the demodulated signal block, searching for the frequency unit index with the largest energy amplitude on the frequency domain spectrum. Based on this, it determines the symbol value represented by each symbol period and then performs deinterleaving and Hamming code forward error correction decoding on the demodulated symbol sequence to reconstruct the original binary data packet. Finally, the protocol stack uses a preset network key to calculate the message integrity check code for the content of the data packet and compares the calculation result with the check field carried at the end of the data packet. Only when the two are completely identical is the packet considered valid, and finally, valid encrypted frame data is output.

[0051] Accordingly, the valid encrypted frame data is decrypted using AES and the display instructions are extracted to obtain the display rendering data used for screen refresh. It should be understood that, to ensure the security of business data transmission in public wireless bands, the transmitted data frames are encapsulated using a high-strength symmetric encryption algorithm at the link layer. The terminal receives only the ciphertext payload, and direct reading cannot obtain any meaningful instruction content. Furthermore, the data packet also contains multiple layers of protocol headers and footers used for network addressing and transmission control, which are invalid payloads for the display module. Therefore, in the technical solution of this application, the valid encrypted frame data is further decrypted using AES and the display instructions are extracted to obtain the display rendering data used for screen refresh. This removes the security lock, restores the plaintext business logic, and strips away all communication layer encapsulation. In this way, clean, executable display control data can be accurately delivered to the application layer, ensuring that the screen driver can directly read and correctly render the target image.

[0052] In a specific example of this application, the system first indexes the device address in the frame header to the pre-set dedicated application session key in the secure storage area. Combined with the frame counter parameters carried in the frame, the system uses the AES-128 encryption engine to generate a key stream sequence with the same length as the ciphertext. The system then performs a bitwise XOR operation to restore the payload ciphertext in the valid encrypted frame data to a plaintext byte stream. Next, the instruction parser scans the plaintext data stream, identifies and removes MAC layer command words and padding bytes added to complete the encryption block. Based on the predefined business protocol format, the system extracts the instruction header that identifies the partial refresh and the compressed bitmap or text encoded data that follows. Finally, the system outputs display rendering data that is in a standardized format and can be directly used for screen control.

[0053] Specifically, in step S6, the display rendering data is used to drive the e-ink screen controller to perform electrophoretic display updates to form visible, readable information. After the update is completed, the power supply to the communication module and the drive circuit is cut off to automatically switch back to deep sleep mode. It should be understood that because e-ink screens use the electrophoretic display principle, they not only rely on specific voltage waveform sequences to precisely control the migration direction and suspension position of charged particles, but the viscosity of the fluid inside the microcapsules is also significantly affected by ambient temperature. If the driving parameters are not adapted to the temperature, it will directly lead to insufficient image contrast or severe image retention. Simultaneously, this type of screen possesses unique bistable characteristics, meaning that even after the electric field is removed, the image can still be permanently maintained by locking the physical positions of the particles. If the peripheral communication module and drive circuit remain in standby mode during screen stillness, unnecessary static power consumption will occur. Therefore, in the technical solution of this application, the display rendering data is further used to drive the e-ink screen controller to perform electrophoretic display updates to form visible, readable information. After the update is completed, the power supply to the communication module and the drive circuit is cut off to automatically switch back to deep sleep mode, thereby ensuring the quality of the image update and maximizing the use of the bistable mechanism to achieve ultimate energy saving of the system. This ensures that the doorplates provide a clear, paper-like reading experience in various temperature and humidity environments, and reduces the overall power consumption of the device to the microamp level during long non-refreshing periods.

[0054] Figure 4 This is a flowchart illustrating the process of using display rendering data to drive an electronic ink screen controller to perform electrophoretic display updates to form readable information, and then cutting off power to the communication module and drive circuit after the update is completed to automatically switch back to deep sleep mode. (See the flowchart for an example of a LoRa-based smart doorplate dynamic management method.) Figure 4 As shown, step S6 includes: S61, decompressing the display rendering data and writing it into the target frame buffer, calculating the pixel grayscale difference between it and the current display screen data to obtain the basic waveform sequence; S62, performing temperature compensation driving based on viscosity coefficient on the basic waveform sequence to obtain a stable physical display screen; S63, performing grounding discharge processing on the common electrode to lock the stable physical display screen using bistable characteristics and backing up the current frame data to non-volatile memory; S64, turning off the RF module and display driver power supply and suspending the processor interrupt to form visible human-readable information and enter deep sleep mode.

[0055] Accordingly, in step S61, the display rendering data is decompressed and written to the target frame buffer, and the pixel grayscale difference between it and the current display screen data is calculated to obtain the basic waveform sequence. It should be understood that, in order to save wireless transmission bandwidth, the transmitted display data is usually encoded with a high compression ratio (such as run-length encoding (RLE) or bitmap compression), and cannot be directly mapped to a physical pixel matrix. Furthermore, the driving mechanism of an e-ink screen is not simply about turning pixels on or off; it requires applying voltage pulses of different polarities and durations based on the specific change path of each pixel from its current grayscale to the target grayscale. If the previous frame's state is not compared before full-screen refresh, not only will uncomfortable black-and-white flicker occur, but refresh power consumption and time will also increase significantly. Therefore, in the technical solution of this application, the display rendering data is further decompressed and written to the target frame buffer, and the pixel grayscale difference between it and the current display screen data is calculated to obtain the basic waveform sequence. This is used to restore the compressed logical image to a physical pixel matrix and determine the exact driving strategy for each microcapsule unit. This enables fast differential refresh based on local conditions, eliminating the global black screen flickering phenomenon during screen redraw, and significantly improving visual smoothness and response speed.

[0056] Specifically, in one particular example of this application, the display controller first calls a decompression algorithm to decode the input display rendering data stream, restores the complete two-dimensional bitmap array, and fills it into the target frame buffer. At the same time, the system reads the image data currently displayed on the screen from the video memory as a reference frame, and starts a comparator to scan and compare the data contents of the two buffers line by line and pixel by pixel. For each pixel, the system determines its state transition type (e.g., from white to black, from black to black, or from white to gray), and uses this transition type as an index to retrieve the corresponding voltage drive waveform data in the waveform lookup table preset in the firmware. Finally, the drive waveform data of all pixels on the screen are combined in time sequence to generate the basic waveform sequence that guides the source driver operation.

[0057] Accordingly, in step S62, the basic waveform sequence is driven by temperature compensation based on the viscosity coefficient to obtain a stable physical display image. It should be understood that since the microcapsules of the electronic ink screen are filled with an electrophoretic fluid, its viscosity is extremely sensitive to changes in ambient temperature. Especially at low temperatures, the fluid viscosity increases significantly, leading to increased resistance to particle migration. If a fixed driving waveform duration is maintained, charged particles will not reach the expected aggregation position due to insufficient kinetic energy, resulting in display defects such as insufficient contrast or ghosting. Therefore, in the technical solution of this application, the basic waveform sequence is further driven by temperature compensation based on the viscosity coefficient to obtain a stable physical display image. This dynamically adjusts the driving energy according to environmental changes to counteract the physical hysteresis caused by fluid viscosity. This ensures that electronic particles can accurately complete grayscale state transitions under a wide temperature range, guaranteeing the consistency and clarity of the final display effect.

[0058] Specifically, in one particular example of this application, the terminal processor first reads the real-time voltage value of the onboard NTC thermistor through the analog-to-digital interface and converts it into the current absolute temperature value. The system then calls the fluid viscosity temperature drift model pre-stored in the firmware based on the Arrhenius equation to calculate the viscosity decay ratio of the current temperature relative to the standard laboratory temperature. The system then uses this ratio to perform a weighted correction operation on the standard frame number of the basic waveform sequence to generate a corrected drive cycle number that has been extended or shortened. Subsequently, the display controller controls the source driver to output precisely timed voltage pulses to the pixel electrode according to the corrected drive cycle number. This forces the black and white charged particles to overcome the fluid resistance corresponding to the current temperature and complete the physical migration to the top or bottom of the microcapsule, thereby solidifying and forming a stable physical display image with high contrast.

[0059] Accordingly, in step S63, a grounding discharge process is performed on the common electrode to lock a stable physical display image using bistable characteristics and back up the current frame data to non-volatile memory. It should be understood that although the e-ink screen possesses bistable characteristics, if a DC component remains on the electrode plate after driving, it will cause the charged particles within the microcapsules to drift unpredictably and slowly, blurring the image. Furthermore, the persistent residual electric field will accelerate the aging and decomposition of the electrophoretic fluid. Simultaneously, to completely cut off the system's main memory power supply during deep sleep to reduce power consumption, the current image data in the volatile memory will be cleared. If not persistently saved, the system will lack a reference base for differential calculations upon the next wake-up. Therefore, in the technical solution of this application, a grounding discharge process is further performed on the common electrode to lock a stable physical display image using bistable characteristics and back up the current frame data to non-volatile memory, thereby eliminating residual screen potential and establishing a state data snapshot across sleep cycles. This ensures that the physical display remains clear and stable even when the power is off, and provides accurate historical status input for the next business update, thereby guaranteeing the display quality and logical continuity of the smart doorplate dynamic management system based on LoRa technology throughout its entire lifecycle.

[0060] Specifically, in one particular example of this application, after the terminal microcontroller detects the busy state signal reset of the e-ink screen controller, it immediately sends an instruction to the power management unit through the general-purpose input / output pin to control the common electrode and all source-gate drive lines to be connected to the ground potential for rapid discharge, thereby eliminating the potential difference between the two ends of the microcapsule to physically lock the particle position and ensure that the formed stable physical display screen no longer drifts. Immediately afterwards, the system starts the direct memory access channel to completely copy and transmit the current frame data containing the latest screen information located in the static random access memory to the onboard serial peripheral interface flash memory or electrically erasable programmable read-only memory and other non-volatile memory for solid-state storage. After confirming that the write verification is successful, the system updates the status flag bit and officially prepares to enter the power-off sleep process.

[0061] Accordingly, in step S64, the RF module and display driver power supply are turned off, and the processor interrupt is suspended to form a visually readable information and enter a deep sleep mode. It should be understood that because e-ink screens possess unique bistable display characteristics—that is, even after the external power supply field is completely removed, the charged particles within the microcapsules can still maintain a predetermined image state for a long time due to their physical position locking—if the RF communication module, display driver chip, and main control processor associated with the screen continue to be powered in standby mode during long non-refreshing idle periods, it will generate continuous and significant static leakage current. This is an unacceptable energy waste for IoT devices that rely on limited battery capacity. Therefore, in the technical solution of this application, the RF module and display driver power supply are turned off, and the processor interrupt is suspended to form a visually readable information and enter a deep sleep mode, thereby completely eliminating all unnecessary power loads after the image is physically solidified. This instantly reduces the total system current of the terminal device from the milliamp level in the working state to the microamp level, achieving ultra-long-term maintenance-free operation of the device while utilizing the bistable characteristics to continuously display information.

[0062] Specifically, in one specific example of this application, after receiving the busy state reset signal from the display controller, the power management unit in the terminal immediately pulls down the enable pin of the RF transceiver chip through the general-purpose input / output interface and disconnects the power supply circuit between the source and gate drive circuits of the display screen, retaining only the weak power supply to the low-power real-time clock circuit to maintain system timing and the countdown for the next wake-up; then, the main control processor saves the critical system context and register state to the low-power backup domain, configures the wake-up event source based on the timer, and then executes a specific shutdown instruction to suspend all non-wake-up interrupt services, forcing the central processing unit and core logic bus into a deep sleep mode. At this time, the stable physical display image permanently retained on the screen constitutes the visible human-readable information that does not require power maintenance.

[0063] In summary, the intelligent doorplate dynamic management method based on LoRa technology according to the embodiments of this application is explained. At the front end, through protocol adaptation and data engine technology, it captures, cleans, and standardizes heterogeneous data from external sources such as OA and academic affairs, breaking down information silos and achieving automated content production. At the transmission layer, it utilizes cloud compilation and gateway protocol conversion mechanisms to reconstruct network data into highly penetrating LoRa radio frequency signals for wide-area broadcasting. At the terminal side, it adopts a periodic wake-up strategy based on a CAD mechanism, only driving the e-ink screen to refresh after valid signaling verification and then automatically cutting off the power. In this way, through closed-loop data flow across the entire link, real-time synchronization of physical identification and digital services is achieved without manual intervention, while the bistable display characteristics ensure extremely low power consumption and long-term operation of the system.

[0064] Furthermore, a smart doorplate dynamic management system based on LoRa technology is also provided.

[0065] Figure 5 This is a block diagram of a smart doorplate dynamic management system based on LoRa technology according to an embodiment of this application. Figure 5 As shown, the intelligent doorplate dynamic management system 100 based on LoRa technology according to an embodiment of this application includes: a data capture and cleaning module 110, used to perform step S1: capturing and cleaning external source data to convert it into a raw object stream recognizable by the system; a field mapping module 120, used to perform step S2: using a data engine to perform semantic parsing and field mapping on the raw object stream, and encapsulating the mapped data into a standardized unified protocol data packet through format conversion technology; and a downlink command frame generation module 130, used to perform step S3: the cloud management platform receives the unified protocol data packet and compiles it into a control command containing display parameters, and performs address addressing and routing encapsulation based on the network topology location of the target terminal to generate a low-power wide area network protocol. Downlink command frame; RF broadcast modulation module 140, used to execute step S4: the gateway device receives the downlink command frame through the backhaul link, and uses the internal processor to convert the network protocol data into physical layer protocol data and perform RF broadcast modulation to transmit the RF modulation signal to the coverage area; signal demodulation and verification module 150, used to execute step S5: the smart doorplate terminal captures the RF modulation signal in the periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on it through the communication module to parse the display rendering data; electrophoretic display update module 160, used to execute step S6: use the display rendering data to drive the electronic ink screen controller to perform electrophoretic display update to form visible human-readable information, and cut off the power supply to the communication module and the drive circuit after the update is completed to automatically switch back to deep sleep mode.

[0066] As described above, the LoRa-based intelligent doorplate dynamic management system 100 according to the embodiments of this application can be implemented in various wireless terminals, such as servers with LoRa-based intelligent doorplate dynamic management algorithms. In one possible implementation, the LoRa-based intelligent doorplate dynamic management system 100 according to the embodiments of this application can be integrated into the wireless terminal as a software module and / or hardware module. For example, the LoRa-based intelligent doorplate dynamic management system 100 can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the LoRa-based intelligent doorplate dynamic management system 100 can also be one of many hardware modules of the wireless terminal.

[0067] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for dynamic management of smart doorplates based on LoRa technology, characterized in that, include: S1: Capture and clean external source data to transform it into a raw object stream that can be recognized within the system; S2: Use the data engine to perform semantic parsing and field mapping on the original object stream, and encapsulate the mapped data into standardized unified protocol data packets through format conversion technology; S3: The cloud management platform receives unified protocol data packets and compiles them into control commands containing display parameters. It also performs address addressing and routing encapsulation based on the network topology location of the target terminal to generate downlink command frames that conform to the low-power wide area network protocol. S4: The gateway device receives downlink command frames through the backhaul link, and uses its internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. S5: The smart doorplate terminal captures radio frequency modulation signals in the periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on them through the communication module to parse out the display rendering data; S6: Uses display rendering data to drive the e-ink screen controller to perform electrophoretic display updates to form visible human-readable information, and cuts off the power supply to the communication module and drive circuit after the update is completed to automatically switch back to deep sleep mode.

2. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S1 includes: The protocol is identified and the adapter is instantiated based on feature matching of external source data to obtain the protocol adapter component, and the protocol adapter component is used to establish a communication handshake with the data source. The protocol adapter component's unpacking method is invoked to strip the communication layer protocol header, extract the core original business payload, and perform character set standardization transcoding and invalid field filtering on the original business payload to obtain cleaned structured data. Based on a predefined intermediate layer data definition, the cleaned structured data is serialized to obtain the original object stream.

3. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S2 includes: Extract key business entities from the original object stream based on semantic analysis to obtain a set of business entities; Intelligent field mapping and data normalization validation are performed on the set of business entities to obtain standard intermediate data containing standard structure descriptions; XSLT transformation and unified protocol encapsulation are performed on standard intermediate data containing standard structure descriptions to obtain unified protocol data packets.

4. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S3 includes: The unified protocol data packets are compiled with instructions and their differences are determined to obtain the instruction payload; Perform adaptive rate routing calculations based on link quality on the command payload to obtain a set of routing configurations; The instruction payload is encrypted to obtain the ciphertext payload; The encrypted payload is encapsulated with LoRaWAN protocol frames to obtain downlink command frames.

5. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S4 includes: Downlink command frames are buffered and timed to obtain the baseband data to be modulated. Read the instruction header metadata to configure the radio frequency parameters, map the baseband data to be modulated into a linear frequency modulated signal whose frequency changes linearly with time, and synthesize a digital IQ signal stream containing in-phase and quadrature components accordingly; Digital-to-analog conversion and radio frequency power amplification of digital IQ signal streams are performed for broadcasting to obtain radio frequency modulated signals.

6. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S5 includes: Channel activity detection and signal locking based on CAD mechanism are performed on the radio frequency modulated signal to obtain the original baseband sampling stream; CSS demodulation and frame integrity verification are performed on the original baseband sample stream to obtain valid encrypted frame data; The valid encrypted frame data is decrypted using AES and the display instructions are extracted to obtain the display rendering data used for screen refresh.

7. The method for dynamic management of smart doorplates based on LoRa technology according to claim 1, characterized in that, Step S6 includes: The display rendering data is decompressed and written to the target frame buffer, and the pixel grayscale difference between the data and the current display screen data is calculated to obtain the basic waveform sequence. Temperature compensation based on viscosity coefficient is applied to the basic waveform sequence to obtain a stable physical display image; A grounding discharge process is performed on the common electrode to lock a stable physical display screen using bistable characteristics, and the current frame data is backed up to non-volatile memory; The RF module and display driver power are turned off and the processor interrupt is suspended to form a visible human-readable information and enter a deep sleep mode.

8. A smart doorplate dynamic management system based on LoRa technology, characterized in that, include: The data capture and cleaning module is used to perform step S1: capture and clean external source data to transform it into a raw object stream that can be recognized by the system. The field mapping module is used to perform step S2: using the data engine to perform semantic parsing and field mapping on the original object stream, and encapsulating the mapped data into a standardized unified protocol data packet through format conversion technology; The downlink command frame generation module is used to execute step S3: The cloud management platform receives the unified protocol data packet and compiles it into a control command containing display parameters, and performs address addressing and routing encapsulation in combination with the network topology location of the target terminal to generate a downlink command frame that conforms to the low power wide area network protocol. The radio frequency broadcast modulation module is used to perform step S4: the gateway device receives downlink command frames through the backhaul link, and uses the internal processor to convert network protocol data into physical layer protocol data and perform radio frequency broadcast modulation to transmit radio frequency modulated signals to the coverage area. The signal demodulation and verification module is used to perform step S5: the smart doorplate terminal captures the radio frequency modulation signal in the periodic wake-up state, and performs signal demodulation and cyclic redundancy check processing on it through the communication module to parse out the display rendering data; The electrophoretic display update module is used to perform step S6: using display rendering data to drive the electronic ink screen controller to perform electrophoretic display update to form visible human-readable information, and after the update is completed, cutting off the power supply to the communication module and the drive circuit to automatically switch back to deep sleep mode.

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