Self-service printing method based on internet of things cloud platform

Abstract

This invention discloses a self-service printing method based on an IoT cloud platform. The method includes the following steps: User authentication and dynamic authorization: Through the IoT cloud platform, users complete identity authentication and print permission allocation using dynamic QR codes or one-time passwords; Lightweight cloudification of printing tasks: User devices segment and compress files, uploading only the encrypted task description containing printing parameters to the cloud platform; Cloud platform task scheduling: The cloud platform monitors the status of IoT printing devices in real time and allocates printing tasks to the optimal device based on device load and geographical location; Distributed data transmission and edge resolution: The cloud platform transmits task segments to edge nodes via IoT protocols, where edge devices reassemble and parse the files. By introducing zero-knowledge encryption technology, edge computing, and dynamic task scheduling, this method solves the problems of insufficient data privacy protection, low efficiency, poor security, and resource waste in existing technologies.

Description

Technical Field

[0001] This invention belongs to the fields of Internet of Things (IoT) technology and cloud computing technology, and specifically relates to a self-service printing method based on an IoT cloud platform. Background Technology

[0002] With the rapid development of IoT and cloud computing technologies, self-service printing technology based on IoT cloud platforms has seen limited application in fields such as offices, education, and healthcare. These platforms typically manage users' print jobs centrally in the cloud, enabling remote printing and resource sharing. However, existing technologies still face some challenges in practical applications, hindering widespread adoption. These challenges mainly manifest in the following aspects:

[0003] 1. Insufficient data privacy protection

[0004] Existing cloud-based printing services typically require users to upload complete documents to the cloud for processing. There is a significant risk of document leakage during transmission and storage, especially in the absence of strict encryption and access controls. Cloud platforms or third parties could potentially access user file content without authorization. Furthermore, sensitive data (such as medical documents and financial reports) may become targets of potential attacks while stored in the cloud.

[0005] 2. Low task processing efficiency

[0006] In existing technologies, uploading files in their entirety to a cloud platform consumes significant bandwidth resources, especially when the files are large or the workload is heavy, leading to noticeable transmission latency. Furthermore, cloud-based task scheduling typically employs static or simplistic rules, failing to adequately consider device load, geographical location, and consumable status. This irrational resource allocation can result in low device utilization, long user wait times, and severely impact service efficiency.

[0007] 3. Inadequate system security and data integrity.

[0008] Files lacking robust encryption and verification mechanisms during transmission are vulnerable to data tampering and man-in-the-middle attacks. Furthermore, task descriptions may contain sensitive user information, and unencrypted or anonymized task descriptions further increase the risk of data leakage. Therefore, existing systems are poorly suited for high-security scenarios such as healthcare and finance.

[0009] 4. High computing pressure in the cloud and unreasonable resource allocation.

[0010] Traditional cloud printing systems typically centralize computational tasks such as file processing and format parsing in the cloud. As the number of users and printing volume increases, the performance bottleneck of cloud servers becomes apparent, and task latency and failure rates can rise significantly under high concurrency. Furthermore, the centralized processing model easily leads to resource waste and equipment overload, further reducing the overall efficiency and flexibility of the system.

[0011] 5. Lack of multi-scenario support and offline capabilities

[0012] Existing technologies generally rely on stable network connections. When the network environment is poor or the system is offline, it cannot function properly, limiting its application in specific scenarios. Furthermore, existing technologies lack sufficient support for edge computing and offline printing, failing to meet the needs of use in complex network environments (such as disaster relief and military applications).

[0013] 6. Low energy efficiency and low resource utilization.

[0014] Cloud printing devices are typically in standby mode when not in use, and their prolonged high-energy-consumption operation remains uncontrolled. Furthermore, inadequate consumable status monitoring and replenishment mechanisms can lead to consumable shortages during operation, negatively impacting user experience. The existing system's task scheduling mechanism also fails to effectively balance task allocation and energy efficiency optimization, easily resulting in resource waste.

[0015] 7. Insufficient user experience and flexibility

[0016] Traditional printing systems are complex to operate on the user side. For example, users must wait for the entire file to be uploaded before they can execute a print job, and they usually cannot obtain real-time information on job progress or device status. In addition, existing technologies lack flexible job configuration and real-time feedback mechanisms, preventing users from dynamically adjusting job settings according to actual needs, thus affecting the overall user experience. Summary of the Invention

[0017] Therefore, the purpose of this invention is to provide a self-service printing method based on an IoT cloud platform. By introducing zero-knowledge encryption technology, edge computing, and dynamic task scheduling, it solves the problems of insufficient data privacy protection, low efficiency, poor security, and resource waste in existing technologies. Compared with existing technologies, this invention has significant advantages in privacy protection, system performance, resource optimization, and user experience, and has extremely high application value and commercial potential.

[0018] To address the aforementioned technical problems, according to one aspect of the present invention, the present invention provides the following technical solution:

[0019] A self-service printing method based on an IoT cloud platform, the method comprising the following steps:

[0020] User authentication and dynamic authorization: Through the IoT cloud platform, users complete identity authentication and print permission allocation using dynamic QR codes or one-time passwords;

[0021] Lightweight cloudification of print jobs: User devices segment and compress files, and only upload an encrypted job description containing print parameters to the cloud platform;

[0022] Cloud platform task scheduling: The cloud platform monitors the status of IoT printing devices in real time and allocates printing tasks to the optimal devices based on device load and geographical location;

[0023] Distributed data transmission and edge parsing: The cloud platform transmits task fragments to edge nodes via IoT protocols, where edge devices complete file reassembly and parsing;

[0024] Privacy-preserving printing: Edge nodes encrypt fragmented data in real time, and the printing device clears the cache immediately after completing the task;

[0025] Print feedback and recording: After printing is completed, the cloud platform records the printing task metadata through blockchain and provides feedback on the printing results through the user's device.

[0026] The task description uses zero-knowledge encryption technology, so the cloud platform cannot obtain the original content of the file and only processes the fragmented metadata of the printing task.

[0027] The cloud platform monitors the status of IoT printing devices, including remaining consumables, device load, and network connectivity. Distributed data transmission is achieved via MQTT, CoAP, or Bluetooth protocols, and dynamic encryption and verification technologies are used during transmission to ensure data integrity.

[0028] The cloud platform dynamically adjusts the order of printing task allocation based on user task priority, printing device performance, and geographical location.

[0029] The following device priority calculation formula is used in cloud platform task scheduling:

[0030]

[0031] Wherein: S j The priority of the j-th device; L j The current load percentage of the j-th device, with a value ranging from 0 to L. j ≤100%; C j The remaining consumables for the j-th device, in pages; C max d is the maximum consumable capacity of the equipment; u,j The distance between the user equipment and the j-th device is expressed in meters, and its value ranges from 0 to d. u,j≤1000; Through this formula, the cloud platform dynamically adjusts the task allocation order to optimize device utilization and improve user experience.

[0032] The edge device includes:

[0033] Built-in edge computing module for parsing encrypted fragmented data;

[0034] The local caching module is used for temporary storage and reorganization of file content;

[0035] The data clearing module is used to delete cached data immediately after the task is completed.

[0036] The printing device supports offline printing mode, allowing users to submit printing tasks directly through short-range communication between the user device and the printing device, and synchronize the task status to the cloud platform after the network is restored.

[0037] The cloud platform records printing task metadata via blockchain, including:

[0038] Task number;

[0039] User identification;

[0040] Printing equipment identification;

[0041] Task execution time;

[0042] Device status information.

[0043] The cloud platform supports multi-device collaborative printing, which can distribute large batches of tasks to multiple printing devices and intelligently merge the task results. The cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users in evaluating print quality and service.

[0044] The task scheduling function of the IoT cloud platform can analyze users' historical usage data based on artificial intelligence to provide users with personalized printing device recommendations and printing parameter optimization suggestions.

[0045] Compared with existing technologies, it has the following significant advantages:

[0046] 1. Improve user data privacy protection

[0047] Most existing cloud-based printing technologies require uploading complete documents to the cloud for processing, which may expose user data to the risk of leakage during transmission and storage. Cloud platforms or third parties may access document content without user authorization.

[0048] This invention employs zero-knowledge encryption technology, where the cloud platform only processes the metadata describing the task and cannot decrypt or access the original file content. Data fragments are transmitted in an encrypted state, and decryption is performed only at edge nodes, further reducing the risk of data leakage.

[0049] 2. Improve task processing efficiency

[0050] In existing technologies, uploading complete files to a cloud platform can lead to transmission delays and wasted bandwidth, especially in large file processing scenarios. Simple task scheduling algorithms do not adequately consider device load, geographical location, and consumable status, potentially resulting in low device resource utilization.

[0051] This invention uploads files to the cloud platform after fragmented compression, reducing the amount of data transmitted in a single transmission and improving upload speed. It also proposes a dynamic priority scheduling algorithm based on device load, consumable reserves, and user distance, enabling tasks to be allocated to the optimal device. This reduces file transfer bandwidth and time costs, making it particularly suitable for large files or high-concurrency printing scenarios. Dynamic scheduling improves device utilization and shortens user waiting time.

[0052] 3. Enhance system security and data integrity

[0053] Existing technologies lack robust encryption and integrity verification mechanisms during file transmission, making them vulnerable to data tampering or man-in-the-middle attacks. Furthermore, task descriptions may contain sensitive user information, posing a risk of leakage.

[0054] The file fragmentation and task description of this invention employ encryption and zero-knowledge proof technologies to ensure that file content is fully protected during transmission and processing. A hash verification mechanism is used to verify the integrity of fragmented data, preventing data loss or tampering during transmission. The security of file transmission and task processing is significantly improved, preventing data leakage and tampering. Furthermore, the system's resistance to potential attacks is enhanced, making it suitable for applications with high security requirements (such as in the medical and financial fields).

[0055] 4. Reduce cloud computing pressure and optimize resource allocation

[0056] Existing cloud printing systems typically centralize file processing and format parsing in the cloud, which can lead to excessive pressure on cloud servers. Under high concurrency, server performance bottlenecks may reduce the overall efficiency of the system.

[0057] This invention decentralizes file fragment decryption and processing to edge nodes, with the cloud platform only responsible for task scheduling and metadata parsing, thus distributing the computational burden. The task priority algorithm dynamically allocates tasks based on device status, avoiding device overload issues. This significantly reduces the load on the cloud server, making it suitable for high-concurrency and large-scale user scenarios, and improving the overall elasticity and scalability of the system.

[0058] 5. Provides applicability to multiple scenarios and offline support.

[0059] Existing technologies rely on a stable connection to the cloud platform and cannot function properly in poor network conditions or offline environments. Insufficient support for offline printing and edge computing limits the system's applicability.

[0060] This invention supports offline printing mode. The task description can be transmitted to the edge node via Bluetooth or other short-range communication methods, and printing is executed after offline decryption. The edge node supports complete print task processing in offline mode and synchronizes with the cloud platform after network recovery. Therefore, the system has stronger applicability and supports self-service printing needs in complex network environments. It has significant advantages in special scenarios (such as military and disaster relief).

[0061] 6. It conforms to the concept of green computing and reduces resource waste.

[0062] The current cloud-based centralized computing model may lead to resource waste, and the prediction and management of equipment consumables are not intelligent enough. Long-term standby of equipment or unreasonable resource allocation may increase energy consumption.

[0063] This invention's optimized task scheduling algorithm allocates tasks based on device status and consumable reserves, avoiding unnecessary resource consumption. It supports dynamic energy efficiency management, allowing the printing device to enter a low-power mode when not in use. This improves resource utilization and reduces consumable waste and energy consumption. System operating costs are reduced, supporting sustainable development goals.

[0064] 7. Enhanced user experience and system flexibility

[0065] Existing technologies involve complex client-side operations, requiring waiting for file uploads and cloud parsing, resulting in a poor overall user experience. They also lack flexible print job configuration and real-time feedback mechanisms.

[0066] The zero-knowledge encryption technology of this invention is completely transparent to the user. File encryption, fragmentation, and task generation are automatically completed on the user's end without any additional configuration. Real-time feedback on task status (such as queue position and printing progress) allows users to flexibly adjust or cancel tasks. This makes user operation more convenient and task response faster. The real-time feedback mechanism enhances the user's sense of control and satisfaction.

[0067] In summary, this invention addresses the problems of insufficient data privacy protection, low efficiency, poor security, and resource waste in existing technologies by introducing zero-knowledge encryption, edge computing, and dynamic task scheduling. Compared to existing technologies, this invention offers significant advantages in privacy protection, system performance, resource optimization, and user experience, demonstrating high application value and commercial potential. Attached Figure Description

[0068] To more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0069] Figure 1 This is a flowchart illustrating the self-service printing method of the present invention. Detailed Implementation

[0070] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0071] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the present invention will be described in detail with reference to the schematic diagrams. When describing the embodiments of the present invention, for ease of explanation, the cross-sectional views illustrating the device structure will be partially enlarged, not according to the usual scale. Furthermore, the schematic diagrams are merely examples and should not limit the scope of protection of the present invention. In addition, actual fabrication should include the three-dimensional spatial dimensions of length, width, and depth.

[0073] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0074] See Figure 1 A self-service printing method based on an IoT cloud platform, the method comprising the following steps:

[0075] User authentication and dynamic authorization: Through the IoT cloud platform, users complete identity authentication and print permission allocation using dynamic QR codes or one-time passwords;

[0076] Lightweight cloudification of print jobs: User devices segment and compress files, and only upload an encrypted job description containing print parameters to the cloud platform;

[0077] Cloud platform task scheduling: The cloud platform monitors the status of IoT printing devices in real time and allocates printing tasks to the optimal devices based on device load and geographical location;

[0078] Distributed data transmission and edge parsing: The cloud platform transmits task fragments to edge nodes via IoT protocols, where edge devices complete file reassembly and parsing;

[0079] Privacy-preserving printing: Edge nodes encrypt fragmented data in real time, and the printing device clears the cache immediately after completing the task;

[0080] Print feedback and recording: After printing is completed, the cloud platform records the printing task metadata through blockchain and provides feedback on the printing results through the user's device.

[0081] Furthermore, the task description employs zero-knowledge encryption technology, preventing the cloud platform from accessing the original file content and allowing it to process only the fragmented metadata of the printing task.

[0082] The specific process is as follows:

[0083] 1. Zero-knowledge encryption task description generation

[0084] 1.1 Operation Process

[0085] Users select files through the client.

[0086] The client segments the file and extracts the printing parameters.

[0087] Each slice and its corresponding printing parameters are generated using zero-knowledge encryption to produce ciphertext.

[0088] Upload the encrypted data and task metadata to the cloud platform.

[0089] 1.2 Formula

[0090] ①. File fragmentation:

[0091] F i =Extract(File, P) i );F i : The i-th data segment; Extract(x, y): Extracts the data block with page number range y from file x; File: The file to be printed; P i Page range or specified content.

[0092] ②. Zero-knowledge encryption:

[0093] C i =E ZK (F i P i K); C i E: The encrypted ciphertext of the i-th segment; ZK (x, y, z): Zero-knowledge encryption function that encrypts fragment x and metadata y with key z; K: Private key generated by the user.

[0094] ③. Task description generation:

[0095] T = {C1, C2, ..., C} n}∪Meta; T: Task description; {C1, C2, ..., C n}: A collection of encrypted file fragments; Meta: Metadata, containing printing parameters (paper type, page range, etc.).

[0096] 1.3 Conditions

[0097] Slice size F i ≤10MB.

[0098] The key K is 256 bits long.

[0099] Metadata ≤ 2KB.

[0100] Furthermore, the cloud platform's status monitoring of IoT printing devices includes monitoring remaining consumables, device load status, and network connection status; the distributed data transmission is implemented through MQTT, CoAP, or Bluetooth protocols, and dynamic encryption and verification technology is used during transmission to ensure data integrity.

[0101] The specific operation process is as follows:

[0102] Remaining consumables monitoring: The cloud platform obtains the remaining paper and ink / toner levels of the printing equipment in real time through IoT connection with the printing equipment.

[0103] Device load status monitoring: The cloud platform obtains the current task queue length, the time of the task being executed, etc. through the device interface to assess the device load.

[0104] Network connectivity status monitoring: The cloud platform monitors the network connectivity status of the devices to ensure stable communication between the devices and the cloud platform.

[0105] Furthermore, the cloud platform dynamically adjusts the allocation order of printing tasks based on user task priority, printing device performance, and geographical location;

[0106] The following device priority calculation formula is used in cloud platform task scheduling:

[0107]

[0108] Wherein: S j The priority of the j-th device; L j The current load percentage of the j-th device, with a value ranging from 0 to L. j ≤100%; C j The remaining consumables for the j-th device, in pages; C max d is the maximum consumable capacity of the equipment; u,j The distance between the user equipment and the j-th device is expressed in meters, and its value ranges from 0 to d. u,j≤1000; Through this formula, the cloud platform dynamically adjusts the task allocation order to optimize device utilization and improve user experience.

[0109] Furthermore, the edge device includes:

[0110] Built-in edge computing module for parsing encrypted fragmented data;

[0111] The local caching module is used for temporary storage and reorganization of file content;

[0112] The data clearing module is used to delete cached data immediately after the task is completed.

[0113] The operation process of the edge computing module is as follows:

[0114] Edge devices receive task descriptions and encrypted fragmented data.

[0115] Decrypt the fragmented data using the user-provided key.

[0116] The decrypted data is parsed and processed according to the task description.

[0117] The operation process of the local cache module is as follows:

[0118] The decrypted data fragments and parsing results are stored in the cache module of the edge device.

[0119] The fragmented data is reassembled sequentially into a complete file for printing or subsequent processing.

[0120] The file content is only retained during task execution.

[0121] The data clearing module operates as follows:

[0122] Once the edge device completes the printing task, it immediately initiates a cleanup operation.

[0123] Clear all task data in the local cache module, including fragmented data, reassembled files, and parsed content.

[0124] Ensure the safety and integrity of the cleanup operation to avoid data residue.

[0125] Furthermore, the printing device supports offline printing mode, allowing users to submit printing tasks directly through short-range communication between the user device and the printing device, and synchronize the task status to the cloud platform after the network is restored.

[0126] The specific operation process for offline printing tasks is as follows:

[0127] Short-range communication establishment: User equipment and printing equipment establish short-range communication connections via Bluetooth, NFC, or Wi-Fi Direct.

[0128] Task generation: The user device generates an offline task description, including fragmented data and printing parameters.

[0129] Task transmission: The task description is sent to the printing device via short-range communication.

[0130] Task Confirmation: The printing device verifies the integrity of the task data, returns confirmation information, and begins executing the printing task.

[0131] The print job execution process is as follows:

[0132] Task parsing: The printing device receives and decrypts the task data, and parses the fragment content and printing parameters.

[0133] Task execution: Print the document page by page according to the task description.

[0134] Task status recording: The printing device locally records the task execution status (number of pages completed, consumable consumption, etc.).

[0135] The task status synchronization process after network recovery is as follows:

[0136] Network status monitoring: The printing device periodically checks the network connection status.

[0137] Status synchronization: After the network is restored, the printing device will synchronize the locally recorded task status to the cloud platform.

[0138] Cloud platform update: The cloud platform receives the task status and updates the task records.

[0139] Furthermore, the cloud platform records printing task metadata via blockchain, including:

[0140] Task number;

[0141] User identification;

[0142] Printing equipment identification;

[0143] Task execution time;

[0144] Device status information.

[0145] Furthermore, the cloud platform supports multi-device collaborative printing, which can distribute large batches of tasks to multiple printing devices and intelligently merge the task results; the cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users in evaluating print quality and service.

[0146] Specifically, the operation process is as follows:

[0147] Task decomposition: After receiving a large number of tasks, the cloud platform will split the files or pages into segments to generate multiple sub-tasks.

[0148] Task fragmentation: T total Original print job; T i : The i-th subtask, which contains a partial slice or page; n: The number of subtasks.

[0149] Device status monitoring: The cloud platform monitors the status of available devices in real time (including load, consumables, etc.) and selects suitable devices to assign sub-tasks.

[0150] Task allocation: The cloud platform allocates subtasks to multiple printing devices and monitors task execution in real time.

[0151] Result Merging: After the subtasks are completed, the cloud platform intelligently merges the printed results and updates the task status. Result Merging: R final The final printed result after merging; R i The result of the i-th subtask.

[0152] The process of automatically generating electronic bills and detailed records is as follows:

[0153] Task logging: The cloud platform records information such as the number of pages printed, the amount of consumables used, and the equipment used in real time during task execution.

[0154] Bill generation: After the task is completed, the cloud platform generates an electronic bill, which includes cost details (number of pages, unit price, total price) and equipment information.

[0155] User feedback: The cloud platform displays task records to users through an app or web page and provides an evaluation function.

[0156] Furthermore, the task scheduling function of the IoT cloud platform can analyze users' historical usage data based on artificial intelligence to provide users with personalized printing device recommendations and printing parameter optimization suggestions.

[0157] Specifically, including:

[0158] Data collection: The cloud platform records key information for each user's print job, including file type, number of pages to print, device selection, and printing time.

[0159] Data storage: The collected data is stored in a user-specific historical data database.

[0160] Data analysis: Use artificial intelligence models (collaborative filtering, cluster analysis) to mine user historical data and extract user behavior patterns and device preferences.

[0161] User historical data is recorded in the following way:

[0162] Du ={(T i ,P i D i ,R i )|i=1,2,…,n};D u : Collection of user historical task records; T i : The identifier for the i-th task; P i : Number of pages to print; D i :Identifier of the printing device used; R i Print quality score.

[0163] The user preference model is as follows:

[0164] Pref u User preference model; W i : Weight, representing the relative importance of tasks (the most recent task has a higher weight); F(x): Feature extraction function, which maps task record x to a specific preference dimension.

[0165] The process of recommending personalized printing devices is as follows:

[0166] Device selection: Based on user preference model (Pref) u Based on the current equipment status, the optimal set of candidate devices is selected.

[0167] Device ranking: Candidate devices are ranked using a priority formula, and the highest priority device is recommended.

[0168] The method for calculating device priority is as follows:

[0169] S j =α·P j +β·A j +γ·H j S j Priority score for the j-th device; P j : The preference score of the user preference model for device j; A j : Current availability of the equipment (load, consumables, etc.); H j : The overall score of device j in the historical usage record; α, β, γ: weighting coefficients, satisfying α+β+γ=1.

[0170] Recommended equipment:

[0171] ReCDevice: Recommended printing device; S j : Priority score of the j-th device; j: j-th device.

[0172] The process for providing print parameter optimization suggestions is as follows:

[0173] Parameter analysis: The cloud platform uses AI models to analyze the user's historical printing parameters (paper type, single / double-sided selection, etc.).

[0174] Recommended parameters: Based on the analysis results and current task requirements, we provide suggestions for optimized parameter settings.

[0175] The parameter recommendation model is as follows:

[0176] Param opt Recommended set of optimized printing parameters; F(P, Pref) u (T): Parameter optimization function, taking into account user preferences (Pref) u The priority of the parameters is calculated for the current task T; P: a set of optional parameters.

[0177] In this embodiment, the self-service printing method is summarized as follows:

[0178] 1. User authentication and dynamic authorization

[0179] ① Users can access the IoT cloud platform via a mobile app or webpage and select the "self-service printing" function.

[0180] ② Enter your identity credentials (username and password) or log in directly using biometrics (fingerprint or facial recognition).

[0181] ③ The cloud platform generates a dynamic QR code or one-time password (OTP): If it's a QR code, the user scans it using the app. If it's an OTP, the user manually enters the password, and login is complete after successful verification.

[0182] ④ The cloud platform assigns permissions to users, including supported print types (black and white / color), task priorities, and file size limits.

[0183] 2. File Segmentation and Task Upload

[0184] ① Users select the file to be printed within the APP (supports PDF, DOCX, image and other formats).

[0185] ② The system performs file segmentation and compression as follows: Files are segmented into pages, with each segment not exceeding 10MB in size. The LZ4 or Zstandard compression algorithm is used to compress the file.

[0186] ③ The system generates a print job description, including the following: File metadata: number of pages, page range, paper size, print orientation. User job ID (generated from user ID and timestamp). Encrypted file fragments (using AES-256 encryption algorithm).

[0187] ④ Upload the generated task description to the cloud platform: Data is transmitted via the MQTT protocol, and the task size must not exceed 32MB.

[0188] 3. Cloud platform task scheduling

[0189] ① The cloud platform monitors the status of IoT printing devices in real time and collects the following information:

[0190] The current load (task queue length or processing time) of each device.

[0191] Remaining consumables (paper and ink).

[0192] The geographical location of each device.

[0193] ② Calculate the device allocation weight using the priority formula described above.

[0194] ③ Select the optimal device to assign tasks according to priority and notify the user.

[0195] 4. Edge Node Resolution and Distributed Transmission

[0196] ① The cloud platform sends the encrypted task description and file fragments to the edge node of the target printing device via the MQTT protocol.

[0197] ② Edge nodes decrypt fragmented data and reassemble files:

[0198] Decrypt each fragment using AES-256.

[0199] Reorganize the files according to the page number order of the task description.

[0200] Verify file integrity (using CRC16 checksum algorithm).

[0201] ③ Edge nodes generate printing instructions (such as paper size, orientation, and page number range) and send them to the printing device.

[0202] 5. Print execution

[0203] ① After receiving the instruction, the printing device begins to execute the printing task:

[0204] The printing equipment monitors the task progress in real time and reports the current status to the edge nodes.

[0205] If insufficient consumables or equipment failure are detected, the cloud platform will be notified immediately to reschedule the task.

[0206] ②After printing is complete, the device immediately clears the local cache:

[0207] Delete the task description and decrypted file data to ensure privacy and security.

[0208] 6. Task Feedback and Recording

[0209] ① After printing is complete, the edge node submits the task completion status to the cloud platform, including the following:

[0210] User ID.

[0211] Device ID.

[0212] Number of pages printed, time taken, and consumable consumption.

[0213] ② The cloud platform records task completion information and stores the metadata on the blockchain:

[0214] The recorded information includes the task number, completion time, and equipment status.

[0215] Blockchain records ensure that task data cannot be tampered with.

[0216] ③ The user's app receives a task completion notification and can view the following information:

[0217] Print job details: file name, number of pages, cost.

[0218] Equipment status: Whether it completes normally, and whether consumables need to be replaced.

[0219] The task ID is recorded on the blockchain for users to verify.

[0220] 7. User pickup and feedback

[0221] ① The user goes to the printing device according to the notification and verifies their identity to collect the item using any of the following methods:

[0222] Scan to pick up your package: Scan the QR code on the printing device.

[0223] Password retrieval: Enter the task ID and dynamic password.

[0224] ②After the system completes the pickup confirmation, the device is updated to an available status.

[0225] ③ Users can rate print quality and equipment service in the app, and the evaluation results are used by the cloud platform to optimize equipment allocation strategies.

[0226] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A self-service printing method based on an Internet of Things (IoT) cloud platform, characterized in that, The method includes the following steps: User authentication and dynamic authorization: Through the IoT cloud platform, users complete identity authentication and print permission allocation using dynamic QR codes or one-time passwords; Lightweight cloudification of print jobs: User devices segment and compress files, and only upload an encrypted job description containing print parameters to the cloud platform; Cloud platform task scheduling: The cloud platform monitors the status of IoT printing devices in real time and allocates printing tasks to the optimal devices based on device load and geographical location; Distributed data transmission and edge parsing: The cloud platform transmits task fragments to edge nodes via IoT protocols, where edge devices complete file reassembly and parsing; Privacy-preserving printing: Edge nodes encrypt fragmented data in real time, and the printing device clears the cache immediately after completing the task; Print feedback and recording: After printing is completed, the cloud platform records the printing task metadata through blockchain and provides feedback on the printing results through the user's device.

2. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The task description uses zero-knowledge encryption technology, so the cloud platform cannot obtain the original content of the file and only processes the fragmented metadata of the printing task.

3. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The cloud platform monitors the status of IoT printing devices, including remaining consumables, device load, and network connectivity. Distributed data transmission is achieved via MQTT, CoAP, or Bluetooth protocols, and dynamic encryption and verification technologies are used during transmission to ensure data integrity.

4. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The cloud platform dynamically adjusts the order of printing task allocation based on user task priority, printing device performance, and geographical location. The following device priority calculation formula is used in cloud platform task scheduling: Wherein: S j Let L be the priority of the j-th device; j The current load percentage of the j-th device, with a value ranging from 0 to L. j ≤100%; C j C represents the remaining consumables for the j-th device, in pages. max The maximum consumable capacity of the equipment; d u,j The distance between the user equipment and the j-th device is expressed in meters, and its value ranges from 0 to d. u,j ≤1000; Through this formula, the cloud platform dynamically adjusts the task allocation order to optimize device utilization and improve user experience.

5. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The edge device includes: Built-in edge computing module for parsing encrypted fragmented data; The local caching module is used for temporary storage and reorganization of file content; The data clearing module is used to delete cached data immediately after the task is completed.

6. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The printing device supports offline printing mode, allowing users to submit printing tasks directly through short-range communication between the user device and the printing device, and synchronize the task status to the cloud platform after the network is restored.

7. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The cloud platform records printing task metadata via blockchain, including: Task number; User identification; Printing equipment identification; Task execution time; Device status information.

8. The self-service printing method based on an IoT cloud platform according to claim 1, characterized in that, The cloud platform supports multi-device collaborative printing, which can distribute large batches of tasks to multiple printing devices and intelligently merge the task results. The cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users in evaluating print quality and service.

9. The self-service printing method based on an Internet of Things cloud platform according to claim 1, characterized in that, The task scheduling function of the IoT cloud platform can analyze users' historical usage data based on artificial intelligence to provide users with personalized printing device recommendations and printing parameter optimization suggestions.

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