Intelligent electronic scale security authentication cloud platform management method and system

Abstract

The invention relates to an intelligent electronic scale safety certification cloud platform management method and system, and belongs to the technical field of intelligent metering equipment safety management. The method comprises the following steps: acquiring user registration information, and performing consistency verification on identity information and biological characteristic information submitted in a user registration process to obtain qualification authentication data; controlling the opening and closing state of the downloading interface according to the authentication state, forbidding data downloading in the closing state, executing unlocking qualification authentication information comparison, and generating a corresponding unlocking personnel file; constructing an identity fusion feature evaluation model, extracting a unique feature of the unlocking personnel file, performing matching verification on an internal identifier of the electronic lock and a cloud platform data recognition library, and outputting a lock execution state record; the identity information of the maintenance personnel corresponding to the electronic lock is inquired, and when a cheating behavior is detected, an abnormity prompt is pushed to the mobile terminal; and corresponding unlocking log information is recorded on the authentication cloud platform.

Description

Technical Field

[0001] This invention belongs to the field of intelligent metering equipment safety management technology, specifically relating to a cloud platform management method and system for intelligent electronic scale safety certification. Background Technology

[0002] With the development of smart hardware and IoT technology, devices such as electronic locks and smart scales with identification and remote management capabilities are widely used in scenarios such as equipment maintenance management, operation and maintenance supervision, and data security control. In practical applications, these devices typically require operation by qualified maintenance or management personnel. The unlocking process not only affects the security of the device itself but also involves the secure management of important information such as equipment operating data, user information, and operation and maintenance logs. Therefore, how to effectively authenticate the identity of device users and manage the entire unlocking process has become a pressing issue in the current technological field.

[0003] In existing technologies, electronic locks or related smart devices mostly use passwords, IC cards, fingerprints, or single facial recognition for identity verification. These authentication methods are susceptible to risks such as password leaks, card loss, and biometric forgery during practical use. Furthermore, most authentication methods only verify the identity at the moment of unlocking, lacking a mechanism to verify the continued validity of the operator's identity. At the same time, existing systems generally suffer from a low correlation between authentication information and the user terminal / device itself; once authentication information is illegally copied or misused, it is difficult to promptly identify abnormal operating behavior.

[0004] In equipment operation and maintenance management, existing technologies typically lack fine-grained control over the validity of maintenance personnel's qualifications, operating time windows, and equipment correspondence, increasing the risk of unauthorized personnel operating equipment during unauthorized times. Although some systems have adopted cloud platforms for centralized management, their access interfaces for authentication data lack dynamic control mechanisms, making it difficult to adjust data access permissions in real time based on authentication status, thus posing a risk of abnormal data downloads or unauthorized access.

[0005] The ability to manage unlocking behavior after the fact is limited. It often only records the unlocking time and fails to form a complete unlocking file by combining personnel identification characteristics, device identification and operation results. It also lacks an automatic detection and early warning mechanism for risk events such as abnormal behavior, cheating behavior and lockout timeout. It is difficult to meet the current requirements of smart devices for security, traceability and standardized operation and maintenance management.

[0006] Therefore, there is an urgent need for a security authentication and control technology that can comprehensively manage personnel identity, biometrics, terminal information and device status, so as to improve the security and reliability of smart devices in the operation and maintenance management process. Summary of the Invention

[0007] To address the aforementioned problems in the existing technology, this invention provides a cloud platform management method for intelligent electronic scale security authentication. The objective of this invention can be achieved through the following technical solutions: S1: Obtain user registration information, construct a user identity feature association network, verify the consistency between the identity information and biometric information submitted during the user registration process, and bind the obtained authentication information to the mobile terminal used to obtain qualification authentication data; S2: Register the qualification certification data to the cloud platform data identification library, control the opening and closing status of the download interface according to the certification status, prohibit data download in the closed state, and perform lock-opening qualification certification information comparison by extracting the identity features in the cloud platform identification library to generate the corresponding lock-opening personnel file; S3: Construct an identity fusion feature evaluation model, extract the unique features of the unlocking personnel file based on the face feature embedding algorithm, and establish a communication connection between the mobile terminal Bluetooth and the electronic lock through the Bluetooth two-way authentication communication method before unlocking. Match and verify the internal identifier of the electronic lock with the cloud platform data recognition library, and output the lock execution status record. S4: Based on the unique feature, query the identity information of the maintenance personnel of the corresponding electronic lock. When cheating is detected, push an abnormal prompt to the mobile terminal. When the electronic lock is not closed within a preset time threshold, issue a lock risk reminder and record the corresponding unlocking log information on the authentication cloud platform.

[0008] Specifically, the method for obtaining the user registration information is as follows: based on the mobile terminal application corresponding to the cloud platform, the user registration process is executed, the basic identity information actively input by the user is collected, and the user's facial image information is obtained by calling the mobile terminal. The user registration information is generated by binding the structured features of the basic identity information and the facial image information.

[0009] Specifically, the method for constructing the user identity feature association network is as follows: based on user registration information and qualification authentication data, extract the user's identity information, biometric information and terminal identifier features to obtain the authentication features that make the lock-picking personnel unique, and use the authentication features as association nodes to establish a mapping relationship between the biometric information and the mobile terminal identifier information to construct the user identity feature association network.

[0010] Specifically, the method for generating the qualification authentication data is as follows: the verified user identity information is bound to the mobile terminal identifier used, and the user identity information and maintenance qualification information are matched and evaluated according to preset permission rules to determine whether they have unlocking permission. The preset permission rules include maintenance qualification and time validity. When the permission evaluation result meets the unlocking conditions, the corresponding qualification authentication data is generated.

[0011] Specifically, the consistency verification process is as follows: the identity information submitted by the user during registration is parsed to obtain the corresponding ID photo features; the facial image information collected during registration is embedded with features through the user identity feature association network to obtain a facial feature vector; the facial feature vector is then compared with the ID photo features to calculate the similarity; when the calculation result meets the preset consistency feature threshold, the user identity information is determined to be consistent with the biometric information.

[0012] Specifically, the method for controlling the open / close state of the cloud platform data identification library interface is as follows: extract the identity authentication credentials from the request based on the obtained user registration information, and match and compare them with the qualification authentication data in the cloud platform data identification library to calculate the feature similarity. When the feature similarity exceeds a preset consistency feature threshold, the interface is put into the open state, allowing data access and download; if the matching fails or abnormal access behavior is detected, the interface is put into the closed state, prohibiting data download and recording access logs.

[0013] Specifically, the method for comparing the unlocking qualification authentication information is as follows: receiving an unlocking request initiated by an electronic lock or mobile terminal, extracting the user identity identifier and timestamp information as authentication parameters to be compared, retrieving the corresponding qualification authentication data from the cloud platform data identification library based on the user identity identifier, performing consistency verification between the authentication parameters to be compared and the retrieved qualification authentication data, generating an unlocking credibility score, and determining that the unlocking qualification authentication information comparison fails when the unlocking credibility score is lower than a preset unlocking threshold.

[0014] Specifically, the method for generating the locksmith profile is as follows: the locksmith credibility score is compared with a preset locksmith threshold. When the locksmith credibility score is not lower than the preset locksmith threshold, the locksmith qualification certification information is deemed to have passed the comparison, a locksmith authorization instruction is generated, and a timestamp and a unique event identifier are added to the locksmith authorization instruction. An index association is established with the corresponding electronic lock and qualification certification data to generate the locksmith profile.

[0015] Specifically, the method for constructing the identity fusion feature evaluation model is as follows: based on the unlocker's file, the facial feature vector and identity information corresponding to the unlocker are read and encoded to obtain the identity fusion feature vector. Based on the set identity matching threshold, the identity fusion feature of the current unlocking request is compared with the identity fusion feature registered in the cloud platform data recognition library to distinguish the embedded features of different faces and establish the identity fusion feature evaluation model.

[0016] Specifically, the output process of the lock execution status record is as follows: after completing the comparison of unlocking qualification authentication information and establishing Bluetooth two-way authentication communication, the collected operating status parameters are subjected to integrity verification and formatted encapsulation to generate a lock execution status data packet. The lock execution status data packet is then sent back to the mobile terminal, which forwards it to the authentication cloud platform to extract the corresponding execution result information, determine whether the lock has completed the unlocking or locking action according to the authorized instructions, and output the lock execution status record.

[0017] Specifically, the method for querying the identity information of the maintenance personnel corresponding to the electronic lock using the unique feature is as follows: using the unique feature identifier as the query index, when the identity uniqueness score is higher than a preset confidence threshold, it is determined to be a legitimate identity, and the corresponding identity fusion feature is marked as a valid feature sample; when the identity uniqueness score is lower than the preset confidence threshold, it is determined to be an abnormal risk, and cheating behavior detection is triggered.

[0018] Specifically, a cloud platform management system for intelligent electronic scale safety authentication is characterized by comprising: Identity Authentication Module: Obtains user registration information, constructs a user identity feature association network, verifies the consistency between the identity information and biometric information submitted during the user registration process, and binds the obtained authentication information to the mobile terminal used to obtain qualification authentication data; Locksmith File Management Module: Registers the qualification certification data to the cloud platform data recognition library, controls the opening and closing status of the download interface according to the certification status, prohibits data download when the interface is closed, and performs locksmith qualification certification information comparison by extracting identity features from the cloud platform recognition library to generate corresponding locksmith files; Identity assessment communication module: Constructs an identity fusion feature assessment model, extracts the unique features of the unlocking personnel file based on the facial feature embedding algorithm, and establishes a communication connection between the mobile terminal and the electronic lock through Bluetooth two-way authentication communication method before unlocking. It matches and verifies the internal identifier of the electronic lock with the cloud platform data recognition library and outputs the lock execution status record. Risk log management module: Based on the unique feature, query the identity information of the maintenance personnel corresponding to the electronic lock. When cheating is detected, push an abnormal prompt to the mobile terminal; when the electronic lock is detected not to be closed within a preset time threshold, issue a lock risk reminder and record the corresponding unlocking log information on the authentication cloud platform.

[0019] The beneficial effects of this invention are as follows: Compared with existing technologies, the intelligent electronic scale security authentication cloud platform management method provided by this invention constructs a user identity feature association network to associate and manage user identity information, biometric information and mobile terminal identifiers, thereby achieving multi-dimensional authentication of the operator's identity, effectively reducing the risk of identity misuse caused by a single authentication method, and improving the accuracy and reliability of identity authentication.

[0020] By centrally managing qualification certification data and dynamically controlling the opening and closing status of the data download interface of the cloud platform data identification library based on the certification status, fine-grained control over access permissions to certification data can be achieved, thereby reducing the risk of abnormal access and unauthorized data download and improving the data security management capabilities of the cloud platform.

[0021] This invention constructs an identity fusion feature evaluation model and extracts the unique identity features of the person unlocking the lock based on a facial feature embedding algorithm. This enables more refined identity differentiation and consistency evaluation of unlocking requests, helping to improve the ability to identify illegal unlocking and cheating behaviors. Simultaneously, by combining a Bluetooth two-way authentication communication mechanism, two-way identity verification between the mobile terminal and the electronic lock is achieved, enhancing the security and controllability of the unlocking process.

[0022] Based on the completion of unlocking authentication, the execution status of the electronic lock is recorded in real time, and the locking behavior is monitored in combination with preset time thresholds. When abnormal operation or locking timeout is detected, risk reminders can be sent to the mobile terminal in a timely manner, and a complete unlocking log archive is formed in the cloud platform, which improves the traceability and management standardization of the equipment operation and maintenance process.

[0023] In summary, this invention can improve the overall security level of intelligent electronic scales and related equipment in terms of identity authentication, data security, and operation and maintenance management, while ensuring system feasibility. Attached Figure Description

[0024] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0025] Figure 1 This is a schematic diagram of the framework of a cloud platform management method and system for intelligent electronic scale safety certification according to the present invention.

[0026] Figure 2 This is a schematic diagram illustrating the qualification authentication and unlocking process of a cloud platform management method and system for security authentication of intelligent electronic scales according to the present invention.

[0027] Figure 3 This is a schematic diagram of the face recognition switch for a smart electronic scale security authentication cloud platform management method and system according to the present invention.

[0028] Figure 4This is a schematic diagram of the structure of a cloud platform management method and system for intelligent electronic scale safety certification according to the present invention. Detailed Implementation

[0029] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0030] Please see Figure 1 A cloud platform management method for safety certification of intelligent electronic scales: S1: Obtain user registration information, construct a user identity feature association network, verify the consistency between the identity information and biometric information submitted during the user registration process, and bind the obtained authentication information to the mobile terminal used to obtain qualification authentication data; S2: Register the qualification certification data to the cloud platform data identification library, control the opening and closing status of the download interface according to the certification status, prohibit data download in the closed state, and perform lock-opening qualification certification information comparison by extracting the identity features in the cloud platform identification library to generate the corresponding lock-opening personnel file; S3: Construct an identity fusion feature evaluation model, extract the unique features of the unlocking personnel file based on the face feature embedding algorithm, and establish a communication connection between the mobile terminal Bluetooth and the electronic lock through the Bluetooth two-way authentication communication method before unlocking. Match and verify the internal identifier of the electronic lock with the cloud platform data recognition library, and output the lock execution status record. S4: Based on the unique feature, query the identity information of the maintenance personnel of the corresponding electronic lock. When cheating is detected, push an abnormal prompt to the mobile terminal. When the electronic lock is not closed within a preset time threshold, issue a lock risk reminder and record the corresponding unlocking log information on the authentication cloud platform.

[0031] In this embodiment, the method for obtaining user registration information is as follows: based on the mobile terminal application corresponding to the cloud platform, a user registration process is executed, basic identity information actively input by the user is collected, and the mobile terminal is called to obtain the user's facial image information. By binding the structured features of the basic identity information and the facial image information, user registration information is generated.

[0032] In this embodiment, the method for constructing the user identity feature association network is as follows: based on user registration information and qualification authentication data, extract the user's identity information, biometric information and terminal identifier features to obtain the authentication features that make the lock-picking personnel unique, and use the authentication features as association nodes to establish a mapping relationship between the biometric information and the mobile terminal identifier information to construct the user identity feature association network.

[0033] In this embodiment, the identity fusion feature evaluation model is used to comprehensively evaluate the identity of the person requesting the lock, and its inputs include: Facial feature embedding vector; User identification characteristics; Mobile terminal binding features.

[0034] For ease of explanation, let's define the dimension of the facial feature embedding vector as d. f =3; Identity feature dimension d i =2; Terminal feature dimension d t =1.

[0035] The face feature embedding vector is obtained by using a face feature embedding algorithm to obtain the face feature vector of the current unlock request: f face =(0.82, 0.41, 0.40); The identity feature vector encodes the user's identity identifier (such as employee ID, certificate number), resulting in: f id =(0.90, 0.10); Normalize the encoding of the mobile terminal's unique identifier: f dev =(1.0); The identity fusion feature vector is constructed using feature concatenation: F=(0.82, 0.41, 0.40, 0.90, 0.10, 1.00).

[0036] Weighted cosine similarity is used to calculate identity fusion similarity: , The weights are set as follows: facial feature weight: w1=w2=w3=0.2, identity identifier weight: w4=w5=0.15, terminal feature weight: w6=0.1, and fusion similarity score: , Set an identity fusion matching threshold because: S fusion =0.999≥0.85, the system outputs the following evaluation results: Identity fusion feature matching successful; Uniqueness score of identity = 0.999; The current unlock request has been deemed legitimate.

[0037] The result will be written into the locksmith's file for subsequent locksmith authorization, log recording, and risk assessment.

[0038] If the similarity calculation result of the identity fusion features of another person is: S fusion =0.62, and: S fusion If ′<0.85, then the model output is: Identity fusion features do not match; Uniqueness score of identity = 0.62; The system triggers cheating detection and sends an error message to the mobile device.

[0039] In this embodiment, the method for generating the qualification authentication data is as follows: the verified user identity information is bound to the mobile terminal identifier used, and the user identity information and maintenance qualification information are matched and evaluated according to the preset permission rules to determine whether the user has the unlocking permission. The preset permission rules include maintenance qualification and time validity. When the permission evaluation result meets the unlocking conditions, the corresponding qualification authentication data is generated.

[0040] In this embodiment, the consistency verification process is as follows: the identity information submitted by the user during registration is parsed to obtain the corresponding ID photo features; the facial image information collected during registration is embedded with features through the user identity feature association network to obtain a facial feature vector; the facial feature vector and the ID photo features are then used to calculate the similarity; when the calculation result meets the preset consistency feature threshold, the user identity information is determined to be consistent with the biometric information.

[0041] In this embodiment, a smart electronic scale security authentication cloud platform management method is applied to the electronic lock operation and maintenance management scenario. The method is completed collaboratively by a mobile terminal, an electronic lock, and an authentication cloud platform.

[0042] (I) Construction and Consistency Verification of User Identity Feature Association Network Users complete the registration process via mobile device, entering basic identity information including name, ID number, and maintenance personnel number. Simultaneously, the system captures the user's current facial image. The cloud platform parses the identity information and extracts the feature vector f from the ID photo. id The collected facial images are input into a facial feature embedding model to extract facial feature vectors f. face The facial feature embedding model is an embedding model based on a deep convolutional neural network, and its output is a 128-dimensional or 256-dimensional normalized feature vector, satisfying: , Where h represents the network output feature, and the cloud platform uses cosine similarity to verify the consistency between the two types of features: , When the similarity S≥0.85, the identity information is determined to be consistent with the biometric information, qualification authentication data is generated, and it is bound to the unique identifier of the mobile terminal (such as device ID). Based on the identity information features, biometric vectors and terminal identifiers, a user identity feature association network is constructed to form a "identity-face-terminal" ternary association structure.

[0043] (ii) Cloud platform data identification database and lock-picking qualification certification The authentication data is stored in the cloud platform's data identification database, which includes an identity feature table, a terminal binding table, and an access control rule table. When an unlocking request is received, the cloud platform extracts the user's identity identifier and timestamp information, compares it with the authentication data in the data identification database, and calculates the unlocking credibility score. , Where S is the identity similarity, T is the time validity factor, α+β=1, and in this embodiment, α=0.7 and β=0.3 are taken. When C≥0.8, it is determined that the person is qualified to unlock the door, and a lock-opening personnel file is generated.

[0044] (III) Bluetooth two-way authentication communication method and lock execution status recording Before unlocking, the mobile terminal and the electronic lock establish a two-way authentication communication connection via Bluetooth. The electronic lock sends a random challenge value R containing the device's unique identifier to the mobile terminal. L The mobile terminal uses the authentication data to generate a response value: , Where H(⋅) is a hash function, UID is the user identity identifier, the electronic lock sends the response value back to the cloud platform for verification, and allows the unlocking operation after verification. After unlocking, the electronic lock collects the lock status parameters and encapsulates them into an execution status data packet, which is then uploaded to the cloud platform via the mobile terminal to generate a lock execution status record.

[0045] (iv) Anomaly detection and mobile terminal push mechanism The cloud platform continuously evaluates the identity of maintenance personnel based on their unique identity characteristics. When the uniqueness score is below 0.75, or when the same identity triggers multiple unlocking requests within a short period of time, it is judged as abnormal behavior. The cloud platform sends an abnormality prompt message to the corresponding mobile terminal through the push interface, including the abnormality type, time and device number. At the same time, if it is detected that the electronic lock has not completed the locking operation within a preset time threshold (such as 300 seconds) after unlocking, a locking risk reminder is generated and the corresponding event is recorded in the unlocking log.

[0046] In this embodiment, the method for controlling the open / close state of the cloud platform data identification library interface is as follows: extract the identity authentication credentials from the request based on the obtained user registration information, and match and compare them with the qualification authentication data in the cloud platform data identification library to calculate the feature similarity. When the feature similarity exceeds a preset consistency feature threshold, the interface is put into the open state, allowing data access and download; if the matching fails or abnormal access behavior is detected, the interface is put into the closed state, prohibiting data download and recording access logs.

[0047] In this embodiment, the method for comparing the unlocking qualification authentication information is as follows: receiving an unlocking request initiated by an electronic lock or mobile terminal, extracting the user identity identifier and timestamp information as authentication parameters to be compared, retrieving the corresponding qualification authentication data from the cloud platform data identification library according to the user identity identifier, performing consistency verification between the authentication parameters to be compared and the retrieved qualification authentication data, and generating an unlocking credibility score. When the unlocking credibility score is lower than a preset unlocking threshold, it is determined that the unlocking qualification authentication information comparison has failed.

[0048] In this embodiment, the method for generating the locksmith profile is as follows: the locksmith credibility score is compared with a preset locksmith threshold. When the locksmith credibility score is not lower than the preset locksmith threshold, the locksmith qualification certification information is determined to be verified, a locksmith authorization instruction is generated, and a timestamp and a unique event identifier are added to the locksmith authorization instruction. An index association is established with the corresponding electronic lock and qualification certification data to generate the locksmith profile.

[0049] In this embodiment, as Figure 2 Unlock qualification certification as shown 1. By downloading the Zhunlegou App through the Dahua Zhunlegou WeChat platform, you can easily use facial recognition to unlock and repair electronic scales.

[0050] 2. By recording detailed registration information, only qualified repair personnel can be approved. After uploading, the platform registers them. Once approved, a facial photo of the repairman is uploaded. If the face matches the ID card, the person is allowed to enter the locksmith personnel database. Facial recognition data, through a mathematical model, accurately confirms the uniqueness of the facial recognition. The facial recognition is characterized by precise and unique features. Password unlocking is used; if the password is leaked, the anti-cheating function becomes ineffective. The new lock is locked when it leaves the factory. Only qualified repair personnel can add the electronic lock to the scale after facial recognition authentication. The authenticated personnel must then check the scale to ensure it is up to standard, that the hardware has not been replaced, and that the software passes the checks before locking it. If software is downloaded to the electronic scale via a host computer or PC, the electronic scale must have a switch button for the transmission line. When the switch is on, data can be downloaded; when the switch is off, data cannot be downloaded. This allows for the addition of an anti-cheating electronic lock to prevent the program inside the electronic scale from being modified. The scale should not be locked unless the operating software has been downloaded.

[0051] 3. After the verification process, the backend records the identity and facial information of the person unlocking the scale. If cheating on the electronic scale is detected, the unique IP address of the electronic lock and the qualified repair personnel at that time can be found by querying the backend. If the repair personnel forgot to close the electronic lock of the scale, the ZhunLeGou platform will display a message stating "An electronic scale at a certain location and time is not closed, which may lead to cheating risks." If the electronic scale is not locked, the ZhunLeGou platform's electronic scale repair center will check the electronic lock periodically. If the repair personnel are away from the electronic scale, the message "Electronic lock of a certain electronic scale is not closed" will continue to be displayed.

[0052] like Figure 3 Face recognition unlock / lock shown 1. Facial recognition is convenient, fast, and highly secure. If the Bluetooth lock is forcibly opened, the internal automatic locking switch will be triggered, and the lock will automatically record the triggered operation.

[0053] 2. Bluetooth automatically turns off to ensure low power consumption, reduce charging frequency, and guarantee a battery life of at least 5 years. Bluetooth is normally off; it only turns on after the Bluetooth check button is pressed once. It receives the phone's Bluetooth signal and flashes the Bluetooth indicator light 10 times to notify the inspector that the Bluetooth and electronic lock are functioning correctly. If the Bluetooth lock does not receive an unlocking command within 5 minutes, it turns off. Before unlocking with a mobile phone, the phone's Bluetooth must pair with the electronic lock's Bluetooth. The pairing process mainly involves verifying the electronic lock's internal ID against the ID in the ZhunLeGou backend ID database. Only after successful verification can the lock be unlocked, preventing the electronic lock from being misused.

[0054] 3. After the lock is successfully opened, the cloud backend will generate a detailed record of the unlocking, including the unlocker's information, lock ID, unlocking time, and facial information. The lock must be manually closed. If it is not closed, the backend will record it. If it is not closed within 30 minutes, the mini-program will issue a reminder. The lead seal wire is crooked and passes through the lock cylinder. If the lead seal wire is cut directly, it cannot be restored. The lead seal wire can only pass through when the lock cylinder is open. The lock cylinder is made of transparent acrylic glass. If the lead seal wire is cut and glued to the acrylic glass lock cylinder, the cut lead seal wire can be clearly seen to ensure the electronic lock is intact and the electronic scale cannot be cheated. If the lock cylinder is forcibly pried open, there is a button switch between the lock cylinder and the electronic lock body. Opening it under abnormal circumstances will disable the electronic lock. If the top cover of the electronic lock body is forcibly pried open, there is also a button switch between the top cover and the lock base. Opening it under abnormal circumstances will also disable the electronic lock.

[0055] like Figure 4The structure of the intelligent electronic scale shown includes transparent acrylic glass, a lead seal wire for the scale body, an anti-cheating switch, an unlocking latch, an anti-cheating indicator light, a push-button switch, a battery, a USB interface, a main control board, and a waterproof cover. Specifically: Transparent acrylic glass is used to prevent the lead seal wire from being cut, ensuring that the lead seal wire passes through the transparent acrylic glass intact, thereby maintaining the airtightness and tamper-proof nature of the electronic lock.

[0056] The lead seal wire of the scale body is used to prevent unauthorized disassembly or modification of the internal structure of the scale body without opening the lock, thus achieving the anti-cheating function.

[0057] Anti-cheating switches are used to prevent the lock from being forcibly opened. They trigger alarms or locking mechanisms by detecting abnormal opening attempts, thereby enhancing the security of electronic locks.

[0058] The unlocking latch is used to automatically pop out the lock head after successful unlocking, making it easy for maintenance personnel to access the inside of the scale body, while ensuring that the lock head is firmly fixed after closing.

[0059] The anti-cheating indicator light is used to display the current status of the electronic lock. For example, flashing 10 times indicates that the Bluetooth and internal modules are working normally, or it will issue a warning signal in case of abnormality to help users check the integrity of the lock.

[0060] The push-button switch is used to turn on the Bluetooth lock and check its condition. Pressing it will trigger the indicator light to flash, ensuring that the Bluetooth module and overall functions of the electronic lock are working properly.

[0061] The battery provides power, ensuring the electronic lock operates normally for ten years and offering long-term, stable power support without the need for frequent replacements.

[0062] The USB interface is used for compatibility with the charging port, supporting battery charging or data transfer via USB, which facilitates maintenance and upgrades.

[0063] The main control board is used to control the overall operation of the electronic lock, including Bluetooth connection, face authentication, unlocking and locking logic, and anomaly detection, to achieve intelligent anti-cheating management.

[0064] Waterproof covers are used to cover key components of electronic locks to prevent moisture or dust from entering, ensuring that electronic locks operate reliably in humid environments for a long time.

[0065] In this embodiment, the method for constructing the identity fusion feature evaluation model is as follows: based on the unlocker's file, the facial feature vector and identity identification information corresponding to the unlocker are read and feature encoded to obtain the identity fusion feature vector. Based on the set identity matching threshold, the identity fusion feature of the current unlocking request is compared with the identity fusion feature registered in the cloud platform data recognition library to distinguish the embedded features of different faces and establish the identity fusion feature evaluation model.

[0066] In this embodiment, the output process of the lock execution status record is as follows: after completing the comparison of unlocking qualification authentication information and establishing Bluetooth two-way authentication communication, the collected operating status parameters are subjected to integrity verification and formatted encapsulation to generate a lock execution status data packet. The lock execution status data packet is then sent back to the mobile terminal, which forwards it to the authentication cloud platform to extract the corresponding execution result information, determine whether the lock has completed the unlocking or locking action according to the authorized instructions, and output the lock execution status record.

[0067] In this embodiment, the method for querying the identity information of the maintenance personnel corresponding to the electronic lock using the unique feature is as follows: using the unique feature identifier as the query index, when the identity uniqueness score is higher than a preset confidence threshold, it is determined to be a legitimate identity, and the corresponding identity fusion feature is marked as a valid feature sample; when the identity uniqueness score is lower than the preset confidence threshold, it is determined to be an abnormal risk, and cheating behavior detection is triggered.

[0068] This invention also provides a smart electronic scale safety authentication cloud platform management system, specifically including: Identity Authentication Module: Obtains user registration information, constructs a user identity feature association network, verifies the consistency between the identity information and biometric information submitted during the user registration process, and binds the obtained authentication information to the mobile terminal used to obtain qualification authentication data; Locksmith File Management Module: Registers the qualification certification data to the cloud platform data recognition library, controls the opening and closing status of the download interface according to the certification status, prohibits data download when the interface is closed, and performs locksmith qualification certification information comparison by extracting identity features from the cloud platform recognition library to generate corresponding locksmith files; Identity assessment communication module: Constructs an identity fusion feature assessment model, extracts the unique features of the unlocking personnel file based on the facial feature embedding algorithm, and establishes a communication connection between the mobile terminal and the electronic lock through Bluetooth two-way authentication communication method before unlocking. It matches and verifies the internal identifier of the electronic lock with the cloud platform data recognition library and outputs the lock execution status record. Risk log management module: Based on the unique feature, query the identity information of the maintenance personnel corresponding to the electronic lock. When cheating is detected, push an abnormal prompt to the mobile terminal; when the electronic lock is detected not to be closed within a preset time threshold, issue a lock risk reminder and record the corresponding unlocking log information on the authentication cloud platform.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A cloud platform management method for safety authentication of intelligent electronic scales, characterized in that, include: S1: Obtain user registration information, construct a user identity feature association network, verify the consistency between the identity information and biometric information submitted during the user registration process, and bind the obtained authentication information to the mobile terminal used to obtain qualification authentication data; S2: Register the qualification certification data to the cloud platform data identification library, control the opening and closing status of the download interface according to the certification status, prohibit data download in the closed state, and perform lock-opening qualification certification information comparison by extracting the identity features in the cloud platform identification library to generate the corresponding lock-opening personnel file; S3: Construct an identity fusion feature evaluation model, extract the unique features of the unlocking personnel file based on the face feature embedding algorithm, and establish a communication connection between the mobile terminal Bluetooth and the electronic lock through the Bluetooth two-way authentication communication method before unlocking. Match and verify the internal identifier of the electronic lock with the cloud platform data recognition library, and output the lock execution status record. S4: Based on the unique feature, query the identity information of the maintenance personnel of the corresponding electronic lock. When cheating is detected, push an abnormal prompt to the mobile terminal. When the electronic lock is not closed within a preset time threshold, issue a lock risk reminder and record the corresponding unlocking log information on the authentication cloud platform.

2. The method according to claim 1, characterized in that, The method for obtaining user registration information is as follows: based on the mobile terminal application corresponding to the cloud platform, the user registration process is executed, the basic identity information actively input by the user is collected, and the user's facial image information is obtained by calling the mobile terminal. By binding the structured features of the basic identity information and the facial image information, user registration information is generated.

3. The method according to claim 1, characterized in that, The method for constructing the user identity feature association network is as follows: based on user registration information and qualification authentication data, extract the user's identity information, biometric information and terminal identifier features to obtain the authentication features that make the lock-opening personnel unique, and use the authentication features as association nodes to establish a mapping relationship between the biometric information and the mobile terminal identifier information to construct the user identity feature association network.

4. The method according to claim 1, characterized in that, The method for generating the qualification authentication data is as follows: the verified user identity information is bound to the mobile terminal identifier used, and the user identity information and maintenance qualification information are matched and evaluated according to the preset permission rules to determine whether the user has the unlocking permission. The preset permission rules include maintenance qualification and time validity. When the permission evaluation result meets the unlocking conditions, the corresponding qualification authentication data is generated.

5. The method according to claim 2, characterized in that, The consistency verification process is as follows: the identity information submitted by the user during registration is parsed to obtain the corresponding ID photo features. The facial image information collected during registration is embedded with features through the user identity feature association network to obtain a facial feature vector. The facial feature vector and the ID photo features are then compared for similarity. When the calculation result meets the preset consistency feature threshold, the user identity information is determined to be consistent with the biometric information.

6. The method according to claim 5, characterized in that, The method for controlling the opening and closing status of the cloud platform data identification library interface is as follows: extract the identity authentication credentials from the request based on the obtained user registration information, and match and compare them with the qualification authentication data in the cloud platform data identification library to calculate the feature similarity. When the feature similarity exceeds a preset consistency feature threshold, the interface is put into the open state, allowing data access and download; if the matching fails or abnormal access behavior is detected, the interface is put into the closed state, prohibiting data download and recording access logs.

7. The method according to claim 4, characterized in that, The method for comparing unlocking qualification authentication information is as follows: receiving an unlocking request initiated by an electronic lock or mobile terminal, extracting user identity identifier and timestamp information as authentication parameters to be compared, retrieving corresponding qualification authentication data from the cloud platform data identification library based on the user identity identifier, performing consistency verification between the authentication parameters to be compared and the retrieved qualification authentication data, and generating an unlocking credibility score. When the unlocking credibility score is lower than a preset unlocking threshold, it is determined that the unlocking qualification authentication information comparison has failed.

8. The method according to claim 2, characterized in that, The method for generating the locksmith profile is as follows: the locksmith credibility score is compared with a preset locksmith threshold. When the locksmith credibility score is not lower than the preset locksmith threshold, the locksmith qualification certification information is determined to be passed, a locksmith authorization instruction is generated, and a timestamp and a unique event identifier are added to the locksmith authorization instruction. An index association is established with the corresponding electronic lock and qualification certification data to generate the locksmith profile.

9. The method according to claim 4, characterized in that, The method for constructing the identity fusion feature evaluation model is as follows: based on the unlocker's file, the facial feature vector and identity information corresponding to the unlocker are read and encoded to obtain the identity fusion feature vector. Based on the set identity matching threshold, the identity fusion feature of the current unlocking request is compared with the identity fusion feature registered in the cloud platform data recognition library to distinguish the embedded features of different faces and establish the identity fusion feature evaluation model.

10. The method according to claim 2, characterized in that, The output process of the lock execution status record is as follows: After completing the comparison of unlocking qualification authentication information and establishing Bluetooth two-way authentication communication, the collected operating status parameters are subjected to integrity verification and formatted encapsulation to generate a lock execution status data packet. The lock execution status data packet is then sent back to the mobile terminal, which forwards it to the authentication cloud platform to extract the corresponding execution result information, determine whether the lock has completed the unlocking or locking action according to the authorized instructions, and output the lock execution status record.

11. The method according to claim 7, characterized in that, The method for querying the identity information of the maintenance personnel of the corresponding electronic lock using the unique feature is as follows: using the unique feature identifier as the query index, when the identity uniqueness score is higher than the preset confidence threshold, it is determined to be a legitimate identity, and the corresponding identity fusion feature is marked as a valid feature sample; When the identity uniqueness score is lower than a preset trust threshold, it is determined that there is an abnormal risk and cheating behavior detection is triggered.

12. A cloud platform management system for intelligent electronic scale security authentication, used to execute the method as described in any one of claims 1-11, characterized in that, include: Identity Authentication Module: Obtains user registration information, constructs a user identity feature association network, verifies the consistency between the identity information and biometric information submitted during the user registration process, and binds the obtained authentication information to the mobile terminal used to obtain qualification authentication data; Locksmith File Management Module: Registers the qualification certification data to the cloud platform data recognition library, controls the opening and closing status of the download interface according to the certification status, prohibits data download when the interface is closed, and performs locksmith qualification certification information comparison by extracting identity features from the cloud platform recognition library to generate corresponding locksmith files; Identity assessment communication module: Constructs an identity fusion feature assessment model, extracts the unique features of the unlocking personnel file based on the facial feature embedding algorithm, and establishes a communication connection between the mobile terminal and the electronic lock through Bluetooth two-way authentication communication method before unlocking. It matches and verifies the internal identifier of the electronic lock with the cloud platform data recognition library and outputs the lock execution status record. Risk log management module: Based on the unique feature, query the identity information of the maintenance personnel corresponding to the electronic lock, and push an abnormal prompt to the mobile terminal when cheating behavior is detected; When it is detected that the electronic lock is not closed within a preset time threshold, a lock risk warning is issued, and the corresponding unlocking log information is recorded on the authentication cloud platform.

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