Self-service printing method based on Internet of Things cloud platform

Abstract

The invention discloses a self-service printing method based on an Internet of Things cloud platform, and the method comprises the following steps: user identity authentication and dynamic authorization: enabling a user to use a dynamic two-dimensional code or a one-time password to complete identity authentication and printing authority distribution through the Internet of Things cloud platform; lightweight cloudization of the printing task: user equipment fragments and compresses a file, and only uploads an encryption task description containing printing parameters to a cloud platform; cloud platform task scheduling: the cloud platform detects the state of the Internet of Things printing device in real time, and distributes the printing task to the optimal device according to the device load and the geographic position; distributed data transmission and edge analysis: the cloud platform transmits task fragments to an edge node through an Internet of Things protocol, and the edge device completes file recombination and analysis; by introducing a zero-knowledge encryption technology, edge calculation and dynamic task scheduling, the problems of insufficient data privacy protection, low efficiency, poor security, resource waste and the like in the prior art are solved.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Things technology and cloud computing technology, and specifically relates to a self-service printing method based on an Internet of Things cloud platform. Background Art

[0002] With the rapid development of the Internet of Things and cloud computing technologies, self-service printing technologies based on the Internet of Things cloud platform have been used in a small number of fields such as office, education, and medical care. These platforms usually manage users' printing tasks in a unified manner through the cloud to achieve remote printing and resource sharing. However, there are still some problems in the actual application of existing technologies, which restrict their wide-ranging application, mainly in the following aspects:

[0003] 1. Insufficient data privacy protection

[0004] Existing cloud-based printing services usually require users to upload complete files to the cloud for processing. There is a high risk of file content leakage during transmission and storage, especially in the absence of strict encryption and access control, the cloud platform or a third party may access the user's file content without the user's authorization. In addition, sensitive data (such as medical documents and financial reports) may become a target of potential attacks during cloud storage.

[0005] 2. Low task processing efficiency

[0006] In the prior art, uploading a complete file to the cloud platform will occupy a large amount of bandwidth resources. Especially when the file is large or the task volume is large, the transmission delay problem is particularly obvious. At the same time, cloud task scheduling usually adopts static or simple rules, without fully considering the equipment load, geographical location and consumable status. This irrational resource allocation may lead to low equipment utilization and long user waiting time, seriously affecting service efficiency.

[0007] 3. Lack of system security and data integrity

[0008] If there is no strong encryption mechanism and verification technology during the file transmission process, it is vulnerable to data tampering or man-in-the-middle attacks. In addition, the task description may contain sensitive information of the user, and the task description that has not been encrypted or desensitized will further increase the risk of data leakage. Therefore, the existing system is less applicable in scenarios with high security requirements (such as medical and financial fields).

[0009] 4. Cloud computing pressure is high and resource allocation is unreasonable

[0010] Traditional cloud printing systems usually complete computing tasks such as file processing and format parsing in the cloud. As the number of users and the amount of printing tasks increase, the performance bottleneck of the cloud server becomes apparent, and task delays and failure rates may increase significantly under high concurrency conditions. In addition, the centralized processing model is prone to waste of resources 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 offline, the system cannot work properly, limiting its application in special scenarios. In addition, existing technologies do not provide sufficient support for edge computing and offline printing, and cannot meet the needs of use in complex network environments (such as disaster relief and military purposes).

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

[0014] Cloud printing devices are usually in standby mode when not in a task state, and long-term high-energy consumption operation is not effectively controlled. At the same time, the status monitoring and replenishment mechanism of consumables is insufficient, which may lead to insufficient consumables during device operation, thus affecting the user experience. The task scheduling mechanism of the existing system also fails to effectively balance task allocation and energy efficiency optimization, which easily leads to waste of resources.

[0015] 7. Insufficient user experience and flexibility

[0016] The user-side operation of traditional printing systems is relatively complicated. For example, users need to wait for the file to be fully uploaded before executing the printing task, and they usually cannot know the task progress or device status in real time. In addition, the existing technology lacks flexible task configuration and real-time feedback mechanism. Users cannot dynamically adjust task settings according to actual needs, which affects the overall experience. Summary of the invention

[0017] Therefore, the purpose of the present invention is to provide a self-service printing method based on the Internet of Things cloud platform, which solves the problems of insufficient data privacy protection, low efficiency, poor security and waste of resources in the prior art by introducing zero-knowledge encryption technology, edge computing and dynamic task scheduling. Compared with the prior art, the present 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 solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

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

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

[0021] Lightweight cloud printing: The user device segments and compresses the file, and only uploads the encrypted task description containing the printing parameters to the cloud platform;

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

[0023] Distributed data transmission and edge analysis: The cloud platform transmits task slices to edge nodes through the IoT protocol, and the edge devices complete the file reorganization and analysis;

[0024] Privacy-preserving printing: The edge node encrypts the shard data in real time, and the printing device clears the cache immediately after completing the task;

[0025] Printing feedback and records: After printing is completed, the cloud platform records the printing task metadata through the blockchain and feedbacks the printing results through the user’s device.

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

[0027] Among them, the cloud platform's status detection of IoT printing equipment includes monitoring of remaining consumables, equipment load status and network connection status; the distributed data transmission is implemented through MQTT, CoAP or Bluetooth protocol, and dynamic encryption verification technology is used during the transmission process 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] Where: S j is the priority of the jth device; L j is the current load percentage of the jth device, and its value range is 0≤L j ≤100%; C j is the remaining consumables of the jth device, in pages; C max is the maximum consumable capacity of the equipment; d u,j is the distance between the user device and the jth device, in meters, with a value range of 0≤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] Wherein, the edge device includes:

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

[0034] Local cache module, used for temporary storage and reorganization of file contents;

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

[0036] The printing device supports an offline printing mode, directly submits a printing task through short-distance communication between the user device and the printing device, and synchronizes the task status to the cloud platform after the network is restored.

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

[0038] Task number;

[0039] User identification;

[0040] Print device identification;

[0041] Task execution time;

[0042] Device status information.

[0043] Among them, the cloud platform supports multi-device collaborative printing function, distributes large-volume tasks to multiple printing devices, and intelligently merges task results; the cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users to evaluate printing quality and services.

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

[0045] Compared with the prior art, it has the following significant beneficial effects:

[0046] 1. Improve user data privacy protection

[0047] Most existing cloud-based printing technologies require that the complete file be uploaded to the cloud for processing, and user data may be at risk of being leaked during transmission and storage. The cloud platform or a third party may access the file content without the user's authorization.

[0048] The present invention adopts zero-knowledge encryption technology. The cloud platform only processes the metadata of the task description and cannot decrypt or access the original content of the file. The fragmented data is transmitted in an encrypted state, and the decryption is only completed at the edge node, further reducing the risk of data leakage.

[0049] 2. Improve task processing efficiency

[0050] In the existing technology, uploading the entire file to the cloud platform may cause transmission delays and bandwidth waste, especially in large file processing scenarios. The task scheduling algorithm is simple and does not fully consider the equipment load, geographical location and consumable status, which may lead to low equipment resource utilization.

[0051] The files of the present invention are uploaded to the cloud platform after being compressed in pieces, which reduces the amount of data transmitted at a single time and improves the upload speed. At the same time, a dynamic priority scheduling algorithm based on device load, consumables remaining and user distance is proposed, so that tasks can be assigned to the optimal device. The file transmission bandwidth and time cost are reduced, which is particularly suitable for large files or high concurrent printing scenarios. Dynamic scheduling improves device utilization and shortens user waiting time.

[0052] 3. Enhance system security and data integrity

[0053] In the existing technology, files lack strong encryption and integrity verification mechanisms during transmission, which makes them vulnerable to data tampering or man-in-the-middle attacks. In addition, the task description may contain user sensitive information, which poses a risk of leakage.

[0054] The file sharding and task description of the present invention adopt encryption and zero-knowledge proof technology to ensure that the file content is fully protected during transmission and processing. The hash check mechanism is used to verify the integrity of the sharded data to prevent data loss or tampering during transmission. The security of file transmission and task processing is significantly improved to prevent data leakage and tampering. In addition, the system has enhanced resistance to potential attacks and is suitable for application scenarios with high security requirements (such as medical and financial fields).

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

[0056] Existing cloud printing systems usually concentrate file processing and format parsing in the cloud, which may cause excessive pressure on the cloud server. In high concurrency situations, server performance bottlenecks may reduce the overall efficiency of the system.

[0057] The present invention delegates the decryption and processing of file segments to edge nodes, and the cloud platform is only responsible for task scheduling and metadata analysis, which disperses the computing pressure. The task priority algorithm dynamically allocates tasks according to the device status to avoid the problem of device overload. As a result, the cloud server load is significantly reduced, adapting to high concurrency and large-scale user scenarios, and improving the overall elasticity and scalability of the system.

[0058] 5. Provide multi-scenario applicability and offline support

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

[0060] The present invention supports offline printing mode. The task description can be transmitted to the edge node via Bluetooth or other short-distance communication methods, and printing is performed after offline decryption. The edge node supports complete printing task processing in offline mode and synchronizes with the cloud platform after the network is restored. Therefore, the system is more applicable 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. Comply with the concept of green computing and reduce resource waste

[0062] The existing 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] The optimized task scheduling algorithm of the present invention allocates tasks according to the device status and the remaining consumables to avoid unnecessary resource consumption. It supports dynamic energy efficiency management, and the printing device enters a low-power mode when not in a task state. This improves resource utilization, reduces consumable waste and energy consumption, reduces system operating costs, and supports sustainable development goals.

[0064] 7. Better user experience and system flexibility

[0065] The existing technology is complex to operate on the user side, requiring waiting for file upload and cloud parsing, resulting in a poor overall experience. It lacks flexible printing task configuration and real-time feedback mechanism.

[0066] The zero-knowledge encryption technology of the present invention is completely transparent to users. File encryption, sharding and task generation are automatically completed on the user side without additional configuration. Real-time feedback of task status (such as queue position, 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 general, the present invention solves the problems of insufficient data privacy protection, low efficiency, poor security and waste of resources in the prior art by introducing zero-knowledge encryption technology, edge computing and dynamic task scheduling. Compared with the prior art, the present invention has significant advantages in privacy protection, system performance, resource optimization and user experience, and has extremely high application value and commercial potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below in combination with the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0069] Figure 1 It is a schematic diagram of the process of the self-service printing method of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagram showing the device structure will not be partially enlarged according to the general scale, and the schematic diagram is only an example, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional space dimensions of length, width and depth should be included.

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

[0074] See also Figure 1 , a self-service printing method based on the Internet of Things cloud platform, the method comprising the following steps:

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

[0076] Lightweight cloud printing: The user device segments and compresses the file, and only uploads the encrypted task description containing the printing parameters to the cloud platform;

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

[0078] Distributed data transmission and edge analysis: The cloud platform transmits task slices to edge nodes through the IoT protocol, and the edge devices complete the file reorganization and analysis;

[0079] Privacy-preserving printing: The edge node encrypts the shard data in real time, and the printing device clears the cache immediately after completing the task;

[0080] Printing feedback and records: After printing is completed, the cloud platform records the printing task metadata through the blockchain and feedbacks the printing results through the user’s device.

[0081] Furthermore, the task description uses zero-knowledge encryption technology, so the cloud platform cannot obtain the original content of the file and only processes the segmented metadata of the printing task.

[0082] The specific process is:

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

[0084] 1.1 Operation process

[0085] The user selects the file through the client.

[0086] The client splits the file into slices and extracts the printing parameters.

[0087] Each slice and the corresponding printing parameters are encrypted using zero-knowledge encryption to generate ciphertext.

[0088] Upload the ciphertext 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 fragment data; Extract(x, y): extract the data block of page range y in 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 : The encrypted ciphertext of the i-th fragment; E ZK (x, y, z): zero-knowledge encryption function, encrypting shard 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}: Encrypted file fragment ciphertext collection; Meta: Metadata, including printing parameters (paper type, page range, etc.).

[0096] 1.3 Conditions

[0097] Fragment size F i ≤10MB.

[0098] The key K is 256 bits long.

[0099] Metadata Meta≤2KB.

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

[0101] The specific operation process is as follows:

[0102] Monitoring of remaining consumables: The cloud platform obtains the remaining paper amount and ink / toner level of the device in real time through the IoT connection with the printing device.

[0103] Equipment 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 evaluate the equipment load.

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

[0105] Furthermore, the cloud platform dynamically adjusts the order of distributing 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] Where: S j is the priority of the jth device; L j is the current load percentage of the jth device, and its value range is 0≤L j ≤100%; C j is the remaining consumables of the jth device, in pages; C max is the maximum consumable capacity of the equipment; d u,j is the distance between the user device and the jth device, in meters, with a value range of 0≤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 shard data;

[0111] Local cache module, used for temporary storage and reorganization of file contents;

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

[0113] Among them, the operation process of the edge computing module is:

[0114] The edge device receives the task description and encrypted shard data.

[0115] Decrypt the shard 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 segments and parsing results are stored in the cache module of the edge device.

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

[0120] The file contents are retained only during the execution of the task.

[0121] Among them, the operation process of the data clearing module is:

[0122] Once the edge device completes the print job, it immediately initiates the purge operation.

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

[0124] Ensure the security and integrity of the clearing operation to avoid data residue.

[0125] Furthermore, the printing device supports an offline printing mode, directly submitting a printing task through short-distance communication between the user device and the printing device, and synchronizing the task status to the cloud platform after the network is restored.

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

[0127] Short-distance communication establishment: The user device and the printing device establish a short-distance communication connection through Bluetooth, NFC, or Wi-Fi Direct.

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

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

[0130] Task confirmation: The printing device verifies the integrity of the task data, returns a confirmation message, and starts executing the printing task.

[0131] The printing task execution process is as follows:

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

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

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

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

[0136] Network status detection: The printing device periodically detects the network connection status.

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

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

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

[0140] Task number;

[0141] User identification;

[0142] Print device identification;

[0143] Task execution time;

[0144] Device status information.

[0145] Furthermore, the cloud platform supports multi-device collaborative printing function, distributes large-volume tasks to multiple printing devices, and intelligently merges task results; the cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users to evaluate printing quality and services.

[0146] Specifically, the operation process is:

[0147] Task decomposition: After receiving a large number of tasks, the cloud platform divides the files into pieces or pages to generate multiple subtasks.

[0148] Task Sharding: T total : Original print task; T i : The i-th subtask, including some slices or pages; n: the number of subtasks.

[0149] Equipment status detection: The cloud platform detects the status of available equipment (including load, consumables, etc.) in real time and selects appropriate equipment to assign subtasks.

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

[0151] Result merging: After the subtask is completed, the cloud platform intelligently merges the printing results and updates the task status. Result merging: R final : Final print 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 record: The cloud platform records information such as the number of printed pages, consumables usage, and execution equipment in real time during task execution.

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

[0155] User feedback: The cloud platform displays task records to users through the APP or web page, and provides evaluation functions.

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

[0157] Specifically, they include:

[0158] Data collection: The cloud platform records key information of each user's printing task, including file type, number of printed pages, device selection, printing time, etc.

[0159] Data storage: The collected data is stored in a user-specific historical record 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] The user history data is recorded as follows:

[0162] Du ={(T i ,P i ,D i ,R i )|i=1,2,…,n};D u : User historical task record collection; T i : The i-th task identifier; P i : Number of pages printed; D i : Printing device identifier used; R i : Print result quality rating.

[0163] The user preference model is:

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

[0165] The recommended process for personalized printing equipment is:

[0166] Device filtering: Based on user preference model Pref u ,Combined with the current device status, filter the optimal device candidate set.

[0167] Device sorting: Sort candidate devices by priority formula and recommend the highest priority device.

[0168] The device priority calculation method is:

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

[0170] Recommended equipment:

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

[0172] The process of printing parameter optimization suggestions is:

[0173] Parameter analysis: The cloud platform uses AI models to analyze users’ historical printing parameters (paper type, single-sided or double-sided selection, etc.).

[0174] Parameter recommendation: Provide optimized parameter setting suggestions based on the analysis results and current task requirements.

[0175] Among them, the parameter recommendation model is:

[0176] Param opt : Recommended optimized printing parameter set; F(P, Pref u , T): parameter optimization function, comprehensive user preference Pref u and the current task T to calculate the parameter priority; P: optional parameter set.

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

[0178] 1. User authentication and dynamic authorization

[0179] ① Users access the IoT cloud platform through the mobile APP or web page and select the "Self-service Printing" function.

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

[0181] ③ The cloud platform generates a dynamic QR code (QR Code) or one-time password (OTP): If it is a QR code: the user uses the APP to scan. If it is an OTP: the user manually enters the password and completes the login after verification.

[0182] ④The 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] ①The user selects the file to be printed in the APP (supports PDF, DOCX, pictures and other formats).

[0185] ② The system fragments and compresses the file as follows: Fragment the file in units of pages, and the size of a single fragment must not exceed 10MB. Use LZ4 or Zstandard compression algorithm to compress the file.

[0186] ③ The system generates a print task description, including the following: File metadata: number of pages, page range, paper size, printing direction. User task ID (generated by user ID and timestamp). File encryption fragmentation (using AES-256 encryption algorithm).

[0187] ④Upload 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] ①The cloud platform detects 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 supplies (paper and ink levels).

[0192] The geographic location of each device.

[0193] ② Use the above priority formula to calculate the device allocation weight.

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

[0195] 4. Edge node analysis 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 through the MQTT protocol.

[0197] ②The edge node decrypts the shard data and reassembles the file:

[0198] Perform AES-256 decryption on each shard.

[0199] Reorganize the document in the order of the pages describing the tasks.

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

[0201] ③ The edge node generates printing instructions (such as paper size, orientation, page range) and sends them to the printing device.

[0202] 5. Print execution

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

[0204] The printing device monitors the task progress in real time and feeds back the current status to the edge node.

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

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

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

[0208] 6.Task feedback and records

[0209] ① After printing is completed, 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 supplies consumed.

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

[0214] The record content includes task number, completion time, and equipment status.

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

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

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

[0218] Equipment status: whether the work is completed normally and whether consumables need to be replaced.

[0219] The task ID recorded in the blockchain is for users to check.

[0220] 7. User Pickup and Evaluation

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

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

[0223] Password pickup: 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 evaluate the printing quality and device services in the APP, and the evaluation results are used by the cloud platform to optimize the device allocation strategy.

[0226] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. 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 the Internet of Things cloud platform, characterized in that: The method comprises the following steps: User identity authentication and dynamic authorization: Through the IoT cloud platform, users use dynamic QR codes or one-time passwords to complete identity authentication and print permission allocation; Lightweight cloud printing: The user device segments and compresses the file, and only uploads the encrypted task description containing the printing parameters to the cloud platform; Cloud platform task scheduling: The cloud platform detects the status of IoT printing devices in real time and allocates printing tasks to the optimal device based on device load and geographic location; Distributed data transmission and edge analysis: The cloud platform transmits task slices to edge nodes through the IoT protocol, and the edge devices complete the file reorganization and analysis; Privacy-preserving printing: The edge node encrypts the shard data in real time, and the printing device clears the cache immediately after completing the task; Printing feedback and records: After printing is completed, the cloud platform records the printing task metadata through the blockchain and feedbacks the printing results through the user’s device.

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

3. The self-service printing method based on the Internet of Things cloud platform according to claim 1 is characterized in that: The cloud platform's status detection of IoT printing devices includes monitoring of the remaining consumables, device load status, and network connection status; the distributed data transmission is implemented through MQTT, CoAP, or Bluetooth protocol, and dynamic encryption verification technology is used during the transmission process to ensure data integrity.

4. The self-service printing method based on the Internet of Things 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: Where: S j is the priority of the jth device; L j is the current load percentage of the jth device, and its value range is 0≤L j ≤100%; C j is the remaining consumables of the jth device, in pages; C max is the maximum consumable capacity of the equipment; d u,j is the distance between the user device and the jth device, in meters, with a value range of 0≤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 the Internet of Things cloud platform according to claim 1, characterized in that: The edge device includes: Built-in edge computing module for parsing encrypted shard data; Local cache module, used for temporary storage and reorganization of file contents; The data clearing module is used to delete cached data immediately after the task is completed.

6. The self-service printing method based on the Internet of Things cloud platform according to claim 1, characterized in that: The printing device supports an offline printing mode, directly submits printing tasks through short-distance communication between the user device and the printing device, and synchronizes the task status to the cloud platform after the network is restored.

7. The self-service printing method based on the Internet of Things cloud platform according to claim 1, characterized in that: The cloud platform records printing task metadata through blockchain, including: Task number; User identification; Print device identification; Task execution time; Device status information.

8. The self-service printing method based on the Internet of Things cloud platform according to claim 1, characterized in that: The cloud platform supports multi-device collaborative printing, distributes large-volume tasks to multiple printing devices, and intelligently merges task results; the cloud platform automatically provides users with electronic bills and detailed records of printing tasks, and supports users to evaluate printing quality and services.

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

Images