Operation authenticity verification method and device, equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of medical health, financial science and technology, leasing and the like, and discloses an operation authenticity verification method, which comprises the following steps: executing operator identity verification, and generating a verification record; starting a countdown mechanism, and monitoring terminal position information; when the initial verification distance accords with a first preset distance threshold value, generating a job permission instruction and receiving task data; acquiring real-time position information of the terminal, and determining a submission verification distance; when the submitted verification distance accords with a second preset distance threshold value, a verification passing timestamp is extracted, and a time effectiveness state is generated; and when the state is valid, storing the task data and the space-time verification information. According to the invention, identity verification and position verification are combined to ensure that an operator executes a task at a target location; the countdown mechanism limits the operable time after identity verification, so that the equipment is prevented from being transferred to others for use; the timeliness verification mechanism ensures that the data submission time is reasonable, and the authenticity and safety of task execution are improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and storage medium for verifying the authenticity of an operation. Background Art

[0002] In the large-scale equipment leasing industry, leasing companies typically act as lessors, sign lease contracts with lessees, and purchase equipment through equipment suppliers, who are responsible for delivering the equipment to the lessee's designated location. However, in actual operations, leasing companies face numerous risks, particularly during equipment delivery and acceptance. There are cases of collusion between equipment suppliers and lessees, using tactics such as false shipments, overdue shipments, or submission of false equipment acceptance documents to circumvent their obligations under the lease contract and thereby defraud the leasing company of its funds. Furthermore, due to the widespread distribution of equipment, leasing companies often entrust crowdsourced personnel to conduct on-site inspections to verify the arrival and operational status of equipment, but this approach also presents significant vulnerabilities.

[0003] Under the existing crowdsourced survey model, leasing companies typically rely on manually uploaded survey data for review. However, crowdsourced personnel may upload historical survey data, have unauthorized personnel perform tasks on their behalf, or even collude with suppliers to submit false equipment information, making it difficult for leasing companies to accurately determine whether the equipment has actually arrived at its destination and is in normal operating condition. While existing technologies can provide on-site evidence through images such as photos and videos, they cannot guarantee the authenticity of uploaded data and are difficult to prevent fraudulent activities such as operator identity fraud and falsified work locations. Therefore, how to improve the credibility of survey data during the leasing survey process and ensure that survey tasks are performed by authorized personnel at the target site remains an unresolved technical challenge.

[0004] The healthcare industry also faces the challenge of verifying the authenticity of remote operations in scenarios such as telemedicine, clinical trials, and medical equipment distribution. For example, during telemedicine, doctors rely on patient-submitted images, test data, and descriptions of their condition to make a diagnosis. However, patients or their agents may provide outdated or inaccurate medical data due to operational errors or subjective factors, thus affecting the diagnosis and treatment results. Furthermore, during the leasing and distribution of medical equipment, hospitals or patients may submit false equipment acceptance reports due to management negligence or malicious behavior, making it impossible for leasing agencies or medical suppliers to confirm whether the equipment has actually been delivered and is in use.

[0005] Existing authentication technologies primarily rely on account logins or simple biometrics, such as fingerprint or facial recognition. However, these technologies are not integrated with location information or real-time operational behavior, leading to vulnerabilities in the verification process. For example, some medical trials require subjects to undergo testing at specific locations, but existing technologies cannot effectively verify whether subjects completed the experimental procedures at the specified location, which may affect the validity of the trial data. The lack of strict identity verification and location verification methods leads to risks such as data falsification and identity theft in telemedicine and medical device management, affecting the authenticity and reliability of medical data.

[0006] In the financial industry, business scenarios such as loan review, insurance claims, and asset appraisal all involve verifying the authenticity of remotely submitted information. For example, during the loan review process, financial institutions often require borrowers to provide proof of assets or information on collateral. Some borrowers may defraud loan funds by forging equipment photos, fabricating asset appraisals, and so on. Similarly, in the insurance industry, some policyholders may defraud insurance compensation by submitting evidence of property damage or medical certificates that do not conform to actual circumstances when applying for insurance claims. In addition, when financial institutions conduct on-site due diligence (due diligence), due diligence personnel may not actually visit the target location due to cost or time constraints, but instead conduct assessments based on historical data or remote imaging data, resulting in distorted due diligence results.

[0007] Existing identity verification methods in the financial industry primarily rely on electronic signatures, video authentication, or offline audits. However, in remote business scenarios, relying solely on electronic authentication methods is insufficient to effectively verify data authenticity. For example, during a mortgage loan review, a financial institution may receive images of real estate or equipment submitted by a borrower, but cannot confirm whether the images were taken or submitted by the borrower. Due to the lack of effective identity authentication and location verification mechanisms, financial institutions struggle to effectively prevent fraudulent activities such as data falsification and identity theft during loan approvals, insurance claims, and due diligence, leading to increased financial risks. Summary of the Invention

[0008] The main purpose of the present invention is to provide a method, device, equipment and storage medium for verifying the authenticity of an operation, aiming to solve the technical problem that the existing technology lacks a linkage mechanism for identity verification and location verification during the execution of remote tasks, cannot effectively ensure the authenticity of the operator and the accuracy of the operation location, and leads to the risk of forgery, tampering or proxy execution of remotely submitted data.

[0009] To achieve the above object, the present invention provides a method for verifying the authenticity of an operation, comprising:

[0010] Responding to a job start instruction and triggering a biometric identification module, performing an operator identity verification operation through the biometric identification module and generating a verification record including a verification pass timestamp;

[0011] Initiating a countdown mechanism based on the verification record, and monitoring the terminal location information during the countdown period of the countdown mechanism;

[0012] When it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp;

[0013] activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0014] Responding to a task submission instruction and obtaining the real-time location information of the terminal, and determining a submission verification distance between the real-time location information of the terminal and the task destination;

[0015] When the submitted verification distance does not exceed a second preset distance threshold, extracting a verification pass timestamp in the verification record;

[0016] Determine the time difference between the verification pass timestamp and the current time, and generate a time validity status based on the time difference and a preset time condition;

[0017] When the time validity status is valid, the on-site task execution data is stored in association with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance.

[0018] Furthermore, to achieve the above-mentioned purpose, the present invention provides an operation authenticity verification device, comprising:

[0019] A biometric identification module, configured to respond to a job start instruction and trigger the biometric identification module, perform an operator identity verification operation through the biometric identification module and generate a verification record including a verification pass timestamp;

[0020] A countdown control module, configured to start a countdown mechanism based on the verification record and monitor the terminal location information during the countdown period of the countdown mechanism;

[0021] a location monitoring module, configured to generate a work permission instruction including a timestamp when it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold;

[0022] a task execution module, configured to activate a task execution interface according to the work permit instruction, and receive on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0023] The terminal positioning module is used to respond to the task submission instruction and obtain the real-time location information of the terminal, and determine the submission verification distance between the real-time location information of the terminal and the task destination;

[0024] A data verification module, configured to extract a verification pass timestamp from the verification record when the submitted verification distance does not exceed a second preset distance threshold;

[0025] A time validity verification module is used to determine the time validity difference between the verification pass timestamp and the current time, and generate a time validity status based on the time validity difference and a preset time validity condition;

[0026] The data storage module is used to associate and store the on-site task execution data with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance and the submitted verification distance when the time validity status is valid.

[0027] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer device, which includes a memory, a processor, and a job authenticity verification program stored in the memory and runnable on the processor, and when the job authenticity verification program is executed by the processor, the steps of the job authenticity verification method described above are implemented.

[0028] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a job authenticity verification program is stored, and when the job authenticity verification program is executed by a processor, the steps of the job authenticity verification method as described above are implemented.

[0029] Beneficial effects: The present invention relates to the field of artificial intelligence technology and can be applied to business scenarios such as healthcare, financial technology, and leasing. It discloses a method for verifying the authenticity of an operation, including: performing operator identity verification and generating a verification record containing a verification pass timestamp; starting a countdown mechanism to monitor the terminal location information during the countdown period; when the initial verification distance between the terminal location information and the task destination meets the first preset distance threshold, generating an operation permit instruction; receiving on-site task execution data containing equipment feature data and geo-tagged images according to the operation permit instruction. In response to the task submission instruction, the terminal's real-time location information is obtained and the submission verification distance is determined; when the submission verification distance meets the second preset distance threshold, the verification pass timestamp in the verification record is extracted; based on the time difference between the verification pass timestamp and the current time, a time validity status is generated, and when the status is valid, the on-site task execution data and the spatiotemporal verification information are stored in data association. The present invention realizes dual verification of the operator's identity and the authenticity of the work location by combining identity verification and location verification; limits the effective operation time after identity verification through a countdown mechanism to prevent the risk of the equipment being handed over to others to perform the task after identity verification; ensures that the operator is actually performing the task at the target location by comparing the initial verification distance with the submitted verification distance, and prevents historical data from impersonating existing survey data; and combines with the time verification mechanism to further prevent anomalies between the work permission time and the actual submission time, thereby ensuring the real-time and traceability of task execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0031] Figure 1 A schematic diagram of an application environment of a method for verifying the authenticity of an operation according to an embodiment of the present invention;

[0032] Figure 2 This is a flow chart of an embodiment of a method for verifying the authenticity of an operation according to the present invention;

[0033] Figure 3 This is a functional module diagram of a preferred embodiment of the operation authenticity verification device of the present invention;

[0034] Figure 4 A schematic diagram of the structure of a computer device according to an embodiment of the present invention;

[0035] Figure 5 FIG. 2 is another structural diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0037] The operation authenticity verification method provided by the embodiment of the present invention can be applied in Figure 1 In an application environment, the user terminal communicates with the server terminal through a network. The server terminal can perform operator identity verification through the user terminal and generate a verification record containing a verification pass timestamp; start the countdown mechanism to monitor the terminal location information during the countdown period; when the initial verification distance between the terminal location information and the task destination meets the first preset distance threshold, generate a work permit instruction; receive on-site task execution data containing equipment feature data and geo-tagged images according to the work permit instruction. In response to the task submission instruction, obtain the real-time location information of the terminal and determine the submission verification distance; when the submission verification distance meets the second preset distance threshold, extract the verification pass timestamp in the verification record; based on the time difference between the verification pass timestamp and the current time, generate a time validity status, and when the status is valid, store the on-site task execution data and the spatiotemporal verification information in data association. The present invention realizes dual verification of the operator's identity and the authenticity of the work location by combining identity verification and location verification; limits the effective operation time after identity verification through a countdown mechanism to prevent the risk of the equipment being handed over to others to perform the task after identity verification; ensures that the operator is actually performing the task at the target location by comparing the initial verification distance with the submitted verification distance, and prevents historical data from impersonating existing survey data; combines the time verification mechanism to further prevent anomalies between the work permission time and the actual submission time, and ensures the real-time and traceability of task execution. Among them, the user end can be but is not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server end can be implemented with an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0038] See also Figure 2 , Figure 2 It should be noted that although the flowchart shows a logical order, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0039] like Figure 2 As shown, the operation authenticity verification method proposed by the present invention includes the following steps:

[0040] S10, responding to the job start instruction and triggering the biometric recognition module, performing an operator identity verification operation through the biometric recognition module and generating a verification record including a verification pass timestamp;

[0041] In this embodiment, the response to the job start instruction and the triggering of the biometric recognition module are the starting point of the entire task authenticity verification process. The purpose is to ensure that the person performing the job is authorized and to establish a traceable identity verification record. The job start instruction can be triggered proactively by the operator, for example, by selecting "Start Job" on the task management interface of the mobile terminal, or it can be automatically triggered by the system based on the task allocation rules. For example, when the task reaches the execution time, a job start request is pushed to the operator, requiring them to complete identity verification within a limited time.

[0042] After the job is initiated, the system invokes the biometric recognition module to verify the operator's identity. This module can include facial recognition, fingerprint recognition, iris recognition, and palm vein recognition. A single method can be used for low-risk tasks, while high-security tasks can employ multimodal fusion recognition to improve the security and accuracy of identity verification. For example, on mobile devices, facial recognition can capture the operator's facial image through the terminal camera and combine it with a liveness detection algorithm, such as requiring the operator to perform random movements such as blinking and opening their mouth to prevent attacks using static photos or videos.

[0043] The biometric recognition module can be executed using either a local storage comparison or a cloud-based authentication method. Local authentication is suitable for scenarios where biometric data is already stored on the device, offering fast recognition speeds and adaptability to weak network conditions. However, for scenarios requiring higher security, cloud-based authentication can be used. This encrypts the collected biometric data and transmits it to a server for remote authentication, enhancing authentication security.

[0044] During identity verification, the system not only collects biometric information but also combines it with device fingerprint information, including the device's unique identifier, IP address, network environment, and other parameters, to form a multi-factor authentication mechanism. For example, the system can record device identification codes such as the terminal's IMEI and MAC address and bind them to the biometric matching results to prevent identity theft after the device is replaced.

[0045] After identity verification is successful, the system generates a verification record with a timestamp indicating the verification is successful and binds it to the current job. The timestamp provides a time basis for identity verification, ensuring a sequential relationship between identity verification and job execution. For example, if a job is not executed for a long time after identity verification, there is a risk that the equipment may be transferred to someone else for operation. Therefore, the system can implement a time limit mechanism, such as requiring subsequent job steps to be completed within a specified time after identity verification, otherwise identity verification must be repeated.

[0046] Verification records can be stored locally, encrypted, or in the cloud. Local storage is suitable for low-latency, high-real-time scenarios, while cloud storage offers greater data integrity and security. To ensure the immutability of verification data, blockchain technology can be used to hash authentication records and store them on-chain to prevent tampering. Alternatively, digital signature technology can be used to encrypt and store timestamps and identity information to ensure data integrity.

[0047] Facial feature images can be captured using the terminal camera and used for identity verification using a deep learning model. This model can be a facial recognition algorithm based on a convolutional neural network (CNN) or a traditional computer vision algorithm that incorporates feature point comparison. For example, the system can first locate the facial area using an object detection network, then extract a 128-dimensional or higher-dimensional feature vector and calculate cosine similarity with registered feature templates in a database. If the similarity exceeds a preset threshold, identity verification is successful; otherwise, re-verification is required.

[0048] During liveness detection, various technologies can be used to improve anti-spoofing capabilities, such as infrared light-based detection of subcutaneous blood flow characteristics or structured light cameras to detect three-dimensional facial contours. Dynamic verification actions, such as random blinking and head rotation, can also be introduced to prevent photo or video spoofing.

[0049] Another method is fingerprint recognition-based authentication. After a job is started, the terminal's fingerprint recognition module is invoked to collect fingerprint data and compare it with a pre-stored feature template. If the fingerprint match exceeds a set threshold, authentication is successful; otherwise, the job is rejected. This method is suitable for terminal devices that support fingerprint recognition, such as smartphones, tablets, or dedicated authentication devices.

[0050] For tasks requiring high security, iris recognition technology can be used. This technology uses an infrared camera to capture the operator's iris image and then uses an iris feature extraction algorithm to perform a match. Iris recognition offers high accuracy and is suitable for scenarios requiring high-precision identity verification.

[0051] Authentication records can be stored locally in a cache or in the cloud. Local storage is suitable for weak network environments. Authentication data is encrypted and stored on the terminal, then synchronized to the server after the network is restored. Cloud storage is suitable for high-security scenarios. Authentication records are uploaded to the server via an encrypted transmission protocol and bound to the task data to ensure data immutability.

[0052] Furthermore, authentication data can be protected against tampering using digital signature technology. For example, when storing authentication results, the system can digitally sign the authentication record using a private key and perform public key verification during task execution to ensure that the authentication data has not been tampered with.

[0053] For example, in the case of large equipment leasing, a leasing company may entrust crowdsourced personnel to perform equipment arrival verification. However, the existing model makes it difficult to ensure that the personnel performing the task are authorized, nor can it confirm that they have actually arrived at the target site. Through an identity verification mechanism, crowdsourced personnel must complete biometric identification, such as facial recognition or fingerprint recognition, before performing the task, and record the identity verification timestamp to ensure that the task is completed by the intended performer. Combined with location verification, this can effectively prevent crowdsourced personnel from falsifying work records, such as uploading historical inspection photos or having unauthorized personnel perform tasks on behalf of others. This improves the authenticity of leasing equipment verification data and reduces the risk of collusion and fraud between equipment suppliers and lessees.

[0054] In the healthcare sector, telemedicine and equipment leasing also face identity authenticity issues. For example, during remote diagnosis and treatment, doctors need to confirm the patient's identity to provide accurate diagnosis and treatment recommendations. Or in the case of telemedicine equipment leasing, hospitals or individual users need to authenticate their identities to ensure the authenticity of equipment delivery and use. Existing technologies typically rely on account passwords or single biometric identification methods, lacking timestamp and geolocation verification. This may result in some patients uploading non-real-time medical records, affecting doctors' judgments. By combining biometric identification with a timestamp mechanism, it is ensured that patients or medical staff submit data within a specific time, thereby improving the authenticity of telemedicine data. In addition, in medical equipment leasing and distribution scenarios, leasing companies can require operators to complete identity verification and record location information before equipment delivery or acceptance to ensure that the equipment is delivered to the correct user and prevent equipment loss or impersonation by others.

[0055] In the financial sector, identity verification technology can be used in scenarios such as loan approval, insurance claims, and asset appraisal. For example, in loan transactions, when a borrower submits an application for equipment or asset mortgage, financial institutions typically need to verify the authenticity of the assets. However, existing technologies make it difficult to verify the authenticity of the submitted images and the identity of the submitter. Before submitting device images, borrowers must complete biometric verification and bind timestamps and location information to ensure the authenticity of the image data and prevent the submission of historical images or non-site footage. Furthermore, in insurance claims scenarios, claims surveyors can use facial recognition combined with timestamps and geolocation records to ensure that the survey is performed by authorized personnel at designated locations, preventing false claims or collusion with policyholders to commit fraud, thereby improving the insurance industry's risk control capabilities.

[0056] Accurately verify the operator's identity through multiple biometric recognition methods. Combining liveness detection with dynamic feature matching effectively prevents identity theft and photo and video spoofing, improving the reliability of identity verification. Generating an identity verification timestamp ensures that the verification time matches the job execution time, preventing the device from being transferred to others after identity verification and enhancing task authenticity. Encrypted storage and secure transmission mechanisms enhance the integrity and immutability of authentication data, improving data security.

[0057] S20, starting a countdown mechanism based on the verification record, and monitoring the terminal location information during the countdown period of the countdown mechanism;

[0058] In this embodiment, a countdown mechanism is activated based on the verification record to ensure that the operator arrives at the target location and performs the task within the specified time after identity verification. This prevents the device from being handed over to others after identity verification, or the operator from performing work at a different location. The verification record includes information such as the identity verification timestamp, operator information, device identification, and task identifier. This serves as the trigger condition for the countdown mechanism and provides data support for subsequent task execution. The countdown period can be dynamically adjusted based on factors such as task type, execution environment, and business security level.

[0059] The countdown mechanism can be triggered in two ways: active and passive. Active triggering means that the system starts the countdown immediately after the operator completes identity verification; passive triggering means that according to the task scheduling rules, the system automatically starts the countdown when specific conditions are met (such as approaching the task execution time). For example, in a telemedicine scenario, after the doctor's identity verification is passed, the system can automatically activate the countdown before the consultation begins to ensure that the doctor completes the consultation task within the specified time and does not submit the diagnosis report too early or too late.

[0060] During the countdown period, the system continuously monitors the terminal location information to ensure that the operator's real-time location meets the task execution requirements. The methods for obtaining terminal location information include but are not limited to:

[0061] Satellite navigation positioning (GPS / Beidou): Suitable for outdoor environments, with high positioning accuracy, generally with errors within the meter range, and suitable for scenarios such as rental equipment inspections and outdoor financial due diligence.

[0062] Cellular network positioning (base station positioning): Based on the mobile communication network, the terminal location is obtained through base station triangulation, and it can still provide high positioning accuracy in environments with limited GPS signals (such as high-rise buildings and underground garages).

[0063] Wi-Fi signal positioning: The positioning is estimated through the BSSID (Basic Service Set Identifier) and signal strength information of surrounding Wi-Fi hotspots. It is suitable for indoor environments and can be used for positioning in scenarios such as hospitals, banks, and office buildings.

[0064] Inertial Measurement Unit (IMU): This system estimates position based on the terminal's internal accelerometer and gyroscope. It is suitable for environments with weak GPS signals, such as tunnels and underground spaces, and calculates trajectory by combining historical position information.

[0065] Geomagnetic field positioning: Based on the comparison of geomagnetic field distribution characteristics at different locations, it is suitable for precise positioning in specific environments, such as large factories, warehouses, hospitals and other indoor environments.

[0066] The location information monitoring method within the countdown period can be flexibly adjusted based on mission requirements and device performance. For example, for missions requiring high-precision location verification, the location sampling frequency can be increased, such as collecting location information once per second, combined with trajectory analysis to ensure that the person is indeed in the target area. For missions with low power requirements, such as long-term field monitoring missions, the sampling frequency can be appropriately reduced to once per minute or longer intervals to reduce device power consumption.

[0067] The countdown can be terminated in the following ways:

[0068] Geographic location-based triggering: When the distance between the terminal's location information and the mission target reaches the preset threshold, the countdown automatically ends and the next task process begins.

[0069] Task operation triggering: When the operator performs a specific operation within the countdown period, such as scanning a code, taking a photo, or filling out an inspection report, the system determines that the task has entered the execution phase and the countdown ends.

[0070] Time expiration-based triggering: If the mission requirements are not met after the countdown period, for example, the operator does not arrive at the mission location, the system can require re-authentication and restart the countdown.

[0071] Data security and storage methods also affect the stability and reliability of the countdown mechanism. Location information can be stored in local cache, remote server, or blockchain:

[0072] Local cache storage: Suitable for short-term tasks. Location information is stored in the terminal device and uploaded to the server after the task is completed. It is suitable for weak network environments.

[0073] Remote server storage: Location information is uploaded to the cloud in real time, ensuring data accessibility and security. This is suitable for high-security tasks such as due diligence in the financial industry.

[0074] Blockchain storage: For tasks that require high data immutability, such as financial claims investigations, location information can use blockchain evidence storage technology to ensure data authenticity and tamper-proof capabilities.

[0075] By combining identity verification with a countdown mechanism, tasks are ensured to execute within a short time after identity verification, preventing the device from being transferred to others after successful authentication. By combining different positioning methods, positioning accuracy is improved in various environments, ensuring that operators complete tasks in the target area. Setting the terminal location monitoring frequency based on task requirements can both improve data accuracy and reduce device energy consumption.

[0076] S30, when it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp;

[0077] In this embodiment, to ensure that the operator has actually arrived at the task execution location, the terminal's location information is compared with the task destination. If the initial verification distance between the two does not exceed a first preset distance threshold, a work permit instruction is generated. This instruction serves as key authorization information for task execution, ensuring that the task operation is carried out by the operator who has actually arrived at the task execution location, and preventing remote operation or unauthorized personnel from executing the task.

[0078] The coordinate information of the task destination can be stored by the server when the task is released, and synchronized to the terminal device after the operator accepts the order for subsequent location comparison.

[0079] The initial verification distance is the straight-line distance or path distance between the terminal's location and the mission destination. Different calculation methods can be used depending on different scenarios:

[0080] Straight-line distance calculation: Calculates the shortest path between two longitude and latitude coordinate points using spherical geometry algorithms. Suitable for tasks requiring high precision, such as equipment acceptance and on-site inspections.

[0081] Path distance calculation: Calculates the shortest driving path from the terminal's current location to the task location based on the map API. Suitable for vehicle scheduling or task management in urban environments.

[0082] Electronic fence judgment: Set a certain range of geographical fence for the task location. If the terminal location falls within the fence, it is determined to meet the initial verification distance requirements.

[0083] When the initial verification distance meets the first preset distance threshold, the system generates a work permit instruction and records the current timestamp. The work permit instruction includes:

[0084] Operator identity information (such as user ID, device identification code)

[0085] Task identifier (a code that uniquely identifies a task)

[0086] Location information (current latitude and longitude coordinates)

[0087] Timestamp (used to verify the validity of the work permit)

[0088] The operation permission instructions can be stored locally on the terminal or uploaded to the server in encrypted form for subsequent operation process verification.

[0089] By combining location verification with task authorization, operators can only execute tasks after they have physically arrived at the task location, preventing remote operation or unauthorized personnel from taking over. Multiple positioning methods adapt to different environments, improving positioning accuracy and ensuring the authenticity of task execution. Different storage methods ensure the security and traceability of work permit instructions, improving the safety and compliance of task management.

[0090] S40, activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0091] In this embodiment, the task execution interface is activated based on the work permission instruction, and the equipment feature data and geo-tagged images are received through the interface to ensure that the task is executed by the designated personnel after authorization. At the same time, the equipment information and geographic location are recorded to improve the authenticity and traceability of the task data.

[0092] The work permit instruction contains operator identity information, task identifier, location verification information, and a timestamp. The task execution interface can be used as an API or as part of the local task management module. Through this interface, operators can upload task execution data, including equipment characteristics and image data, and ensure the integrity of data collection.

[0093] Activation method of task execution interface:

[0094] Directly call the terminal task management module: suitable for local task execution, driven by the operation permission instruction, activates the task execution component on the terminal, and allows the operator to start data collection.

[0095] Remote request for task execution permission: Applicable to cloud-based task management mode. The terminal requests the remote server to verify the operation permission instruction. After passing, the task data can be uploaded.

[0096] Blockchain-based authorization mechanism: Suitable for high-security scenarios. Work permit instructions can be stored on the chain. The task execution interface can only be activated after confirmation from the blockchain network, ensuring that authorization cannot be tampered with.

[0097] Equipment characteristic data collection: Sensors read device identification information (such as RFID, barcodes, and QR codes) and analyze the device model, serial number, and manufacturer information. Combined with OCR (optical character recognition) technology, this automatically identifies device information on nameplates, reducing manual entry errors. For networked devices, remote interfaces are used to read device operating status, sensor data, or log information to ensure accurate and verifiable device operation.

[0098] Geotagged Image Capture: Use the terminal camera to capture panoramic images of the device and, combined with GPS coordinates or Wi-Fi location information, embed geographic location information into the image metadata. Image files can store capture time, device ID, and task identifier, and support watermarking to ensure the authenticity and immutability of the image data. Use panoramic or multi-angle shooting modes to capture multiple perspectives of the device, enhancing image integrity.

[0099] The collected device feature data and geo-tagged images form a task execution data package, which can be stored in the terminal device or uploaded to the remote server through the task execution interface for subsequent verification and archiving.

[0100] Authorization control of the task execution interface ensures that the task execution process matches the authorization record, improving the security and traceability of task data. Combining device feature data and geo-tagged imagery enhances the authenticity of task execution data and prevents remote forgery or data tampering. Multiple data storage methods are used to adapt to different task scenarios, ensuring data integrity and long-term availability.

[0101] S50, responding to the task submission instruction and obtaining the real-time location information of the terminal, and determining the submission verification distance between the real-time location information of the terminal and the task destination;

[0102] In this embodiment, after completing a task and submitting the task data, the system needs to verify that the operator's current location meets the task requirements, thereby ensuring that the data collected is authentic and valid. The terminal's real-time location information can be obtained by calling the system's positioning module. The collected data includes latitude and longitude, altitude, and signal accuracy. After obtaining the terminal's location information, it is compared with the coordinates of the task destination to calculate the submitted verification distance and determine whether it meets the preset requirements.

[0103] The calculation method for submitting verification distances can be adapted to different business needs. For example, in the case of leased equipment inspections, high-precision satellite positioning combined with geofencing technology can be used to ensure that submitted data originates from the equipment's location. In scenarios like financial due diligence or insurance claims, road network path calculation can be incorporated to ensure that surveyors arrive at the site via a reasonable route, rather than submitting tasks far from the task location.

[0104] In signal-restricted environments, the submission verification distance calculation can be combined with inertial navigation and geomagnetic positioning. Sensors such as gyroscopes and accelerometers track the terminal's displacement trajectory and, combined with existing historical location information, infer the terminal's current location. If the terminal's location information deviates significantly, the system can prompt the operator to adjust the position or resubmit the task to ensure the authenticity and reliability of the task data.

[0105] During the task submission process, the system can perform additional data consistency checks. For example, the location information track recorded during task execution should be reasonably consistent with the terminal's real-time location information at the time of submission. If the operator's location information deviates significantly during task execution, or if the location at the time of task submission is abnormally close to the task execution point, the system may mark the task as suspicious and trigger manual review or additional supplementary verification.

[0106] Determining the submission verification distance is not only used to verify task compliance, but can also be used to analyze task execution efficiency. For example, on a crowdsourcing platform, the accuracy of task execution can be assessed by analyzing the degree of deviation between the submission verification distance and the task location of different operators. Highly accurate task performers can then be given higher credit ratings or priority in task allocation.

[0107] When a task is submitted, the task management server automatically calls the terminal device's positioning module to obtain real-time location information and compare it with the coordinates of the task destination. This comparison can be performed using spherical geometry algorithms to calculate straight-line distances, or by integrating electronic map services to obtain actual road distances. If the calculated submission verification distance falls within a preset range, the task is submitted. Otherwise, the operator is prompted to adjust their location and resubmit.

[0108] Another implementation method is based on dynamic location tracking, which continuously records the operator's location information during task execution and compares the trajectory with historical location information when the task is submitted. If the trajectory matches the task execution process, the submission is considered valid. If there is a significant deviation between the submitted location and the execution trajectory, the system can trigger additional verification procedures, such as requiring the operator to upload additional video evidence or undergo secondary identity verification.

[0109] For indoor scenarios, such as medical equipment maintenance and laboratory testing, Wi-Fi and Bluetooth beacon technology can be combined to ensure that operators submit tasks at the designated location. For example, in a hospital environment, the system can detect the Wi-Fi hotspot information when the operator submits the task and compare it with the hotspot list at the task location to determine whether it is within the legal task range.

[0110] The verification distance calculation ensures the authenticity of task data, preventing operators from submitting historical data or falsifying task execution records while far from the task location. Combined with location information consistency verification, this improves task data reliability and reduces the risk of remote fraud. Furthermore, dynamic location tracking and indoor positioning technologies can be expanded to various application scenarios, enhancing task execution monitoring capabilities.

[0111] S60, when the submitted verification distance does not exceed a second preset distance threshold, extracting a verification pass timestamp in the verification record;

[0112] In this embodiment, when the distance submitted for verification does not exceed the second preset distance threshold, the verification pass timestamp in the verification record is extracted to ensure that the operator submitting the task is the same operator who initially completed identity verification and obtained the work permit, and to ensure the integrity of the task execution process. Extracting the verification pass timestamp can be used to determine whether the interval between task executions meets preset requirements and provide a time basis for the review and storage of subsequent task data.

[0113] The submission verification distance is the distance between the operator's real-time location at the time of submission and the task destination. This distance can be calculated using straight-line distance, path distance, or geo-fence detection. If the comparison result meets the second preset distance threshold, confirming that the operator is within the reasonable submission range, the verification pass timestamp is extracted for time consistency verification.

[0114] The storage method of timestamp can be based on local storage, cloud database storage or blockchain evidence.

[0115] Local storage: When the terminal completes identity verification, the verification pass timestamp is stored internally on the device. This is then read and uploaded to the server when the task is submitted. This is suitable for situations where the network is unstable or tasks are being executed offline.

[0116] Cloud database storage: After identity verification is complete, the system stores the timestamp in a remote database. When a task is submitted, the timestamp is retrieved from the database and compared to ensure data consistency. This is suitable for business scenarios requiring remote management, such as telemedicine or financial audits.

[0117] Blockchain evidence storage: Timestamps are stored on the chain to ensure that data cannot be tampered with. It is suitable for scenarios with high security requirements, such as financial transaction audits or insurance claims verification.

[0118] Timestamp extraction is not only used for time consistency verification, but can also be used to calculate task execution duration and match it to the task type. For example, in medical equipment maintenance tasks, the actual operation duration can be calculated based on the verified timestamp to determine whether the maintenance operation is reasonable. In insurance inspection tasks, the timestamp can be used to determine whether the inspector completed the task within a reasonable time frame, preventing the remote submission of historical data from falsifying on-site operations.

[0119] After extracting the timestamp, the system can further compare the task execution trajectory to confirm whether the operator maintained a reasonable movement trajectory during the task execution. For example, in the rental equipment verification scenario, the system can analyze the location information points during the task execution and calculate the overall execution trajectory based on the verification timestamp. If the trajectory data is abnormal or the task submission time is too short, the system can mark the task as suspicious and trigger manual review or additional secondary verification mechanism.

[0120] By extracting and verifying the timestamp, we ensure that the operator submitting the task is the same as the operator at the time of authentication, preventing the risk of data falsification caused by equipment transfer or remote operation during task execution. Combined with timestamp comparison, we can calculate the task execution duration, ensuring that task completion time is within a reasonable range and improving the credibility of task data.

[0121] S70, determining a time difference between the verification pass timestamp and the current time, and generating a time validity status based on the time difference and a preset time validity condition;

[0122] In this embodiment, the time difference between the timestamp and the current time is used to assess the time validity of task execution, ensuring that the task is completed within a reasonable timeframe. The time validity of a task affects the authenticity of task data. If the execution time is too short or exceeds the preset range, there may be a risk that the task was not executed at the scheduled site or that the data is falsified. By calculating the time difference and comparing it with the preset time limit, the task validity status can be dynamically adjusted to ensure task compliance.

[0123] The time difference is the time interval between the current time and the verification pass timestamp. This time difference can be calculated by obtaining the current time from the system clock and comparing it with the stored timestamp. Preset time conditions can be set based on factors such as the task type, operating environment, and business rules. For example, in an equipment acceptance task, the preset time condition might be to complete the task within 30 minutes of verification passing. In a financial investigation task, the inspection report might be submitted within 2 hours, otherwise re-authentication is required.

[0124] The calculation of the validity status may include:

[0125] Fixed time threshold: Set a fixed time range. If the time difference is less than the threshold, the task status is valid; otherwise, it is invalid. This is suitable for standardized operating processes such as logistics delivery and insurance claims.

[0126] Dynamic Time Limit Adjustment: Adjust the time limit threshold based on task complexity, environmental factors, etc. For example, in a telemedicine diagnosis task, the time it takes for a doctor to submit a diagnosis can be dynamically adjusted based on the complexity of the image, improving flexibility.

[0127] Task execution trajectory verification: This optimizes the timeliness of the task by combining the location information track during the task execution. If the task trajectory shows that the operator has completed the task within a reasonable time, even if it exceeds the standard time limit, it will still be considered valid.

[0128] When the time difference meets the preset time condition, the task status is marked as valid and the task data can be stored and used normally; if it exceeds the time range, the task status is marked as invalid and the system can trigger a supplementary verification process, such as requiring re-identity verification or re-execution of the task.

[0129] Based on the terminal device's system clock, the current time can be obtained when the task is submitted, and the time interval between the current time and the verification timestamp can be calculated. If the calculated time difference is less than the set time threshold, the task status is set to valid, otherwise it is set to invalid.

[0130] Another approach is to analyze timeliness differences based on task execution logs. For example, during task execution, location information tracks are recorded at regular intervals. Upon task submission, the total task execution time is calculated and combined with the track data to determine whether the task was completed within the scheduled time. If the track data is reasonable, the task can still be considered valid even if it exceeds the standard timeliness threshold.

[0131] For scenarios where task execution time is affected by external factors, such as equipment inspections or medical examinations, a dynamic adjustment strategy can be implemented. This strategy calculates the distribution of task completion times based on historical task data and dynamically optimizes the timeliness threshold. For example, if historical task data indicates that a certain type of task typically takes longer to complete, the effective time range for the task can be automatically extended, improving the system's adaptability.

[0132] By calculating the time difference between the verified timestamp and the current time and combining it with preset time conditions to determine the validity of the task, the credibility of task execution data is improved. Dynamic time adjustment is combined with optimized time judgment criteria for different task types, reducing misjudgments and increasing task management flexibility. Trajectory analysis combined with time verification enhances the authenticity of task execution times, prevents tasks from being submitted remotely within unreasonable timeframes, and improves the compliance of task data.

[0133] S80: When the time validity status is valid, the on-site task execution data is stored in association with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance.

[0134] In this embodiment, when the time validity status is valid, on-site task execution data is stored in a data-associated manner with spatiotemporal verification information to ensure the integrity and traceability of task data. This spatiotemporal verification information includes the verification pass timestamp, initial verification distance, and submission verification distance, and is used to verify the temporal consistency, spatial consistency, and operational authenticity of task execution. This associated storage ensures consistency between task execution data and operational records, enhancing the credibility of task data.

[0135] On-site task execution data includes equipment feature data, geo-tagged images, task execution logs, etc. This data can be collected by terminal devices and uploaded to the server for storage. After being associated with spatiotemporal verification information, it can serve as the basis for subsequent task review, query, or data analysis.

[0136] Data association storage methods may include:

[0137] Relational database storage: Task execution data and spatiotemporal verification information are stored in the database and associated based on task identifiers, which is suitable for standardized task management systems.

[0138] Distributed file storage: Task execution data (such as images and videos) is stored in the file system, and spatiotemporal verification information is stored in the database and associated through an indexing mechanism. It is suitable for large-scale data storage scenarios.

[0139] Blockchain evidence storage: For scenarios with high security requirements, such as financial transaction audits or judicial evidence collection, spatiotemporal verification information can be written into the blockchain to ensure the data is tamper-proof and associated with task execution data through a unique hash value to improve data credibility.

[0140] The data storage and association process may include the following steps:

[0141] Data indexing: Generate a task identifier index table to ensure that task execution data can be quickly retrieved and matched with the corresponding spatiotemporal verification information.

[0142] Data consistency check: Before data is stored, check whether the task execution data matches the time and space verification information. If there is any inconsistency in the data, such as the task submission time exceeds the preset time limit, the system can trigger an additional review mechanism.

[0143] Data compression and optimization: For image or video data with large storage volumes, intelligent compression technology can be used to ensure data storage efficiency without affecting the integrity of verification information.

[0144] Through data association and storage, task execution data can be traced, analyzed, or reviewed in subsequent business processes. For example, during the acceptance of leased equipment, equipment image data can be cross-verified with operator verification records and task execution time to ensure the authenticity of the acceptance data.

[0145] Example description:

[0146] In the large-scale rental industry, equipment rental companies need to conduct on-site inspections of equipment deliveries to ensure that the leased equipment arrives on schedule and in proper condition. Traditional inspection methods rely primarily on manual record-keeping, which can lead to situations where the inspector fails to physically arrive at the site, submits historical photos to impersonate the inspection results, or is replaced by unauthorized personnel. To enhance the authenticity and traceability of inspection tasks, the reliability of task data is ensured through identity verification, location information verification, and time validity verification. During the task execution, the inspector accepts the inspection task through a job start command and undergoes identity verification using a biometric recognition module to ensure that the person performing the task is the authorized individual. The system records the verification pass timestamp for subsequent verification. After passing identity verification, the system initiates a countdown, requiring the inspector to arrive at the equipment storage location within a specified timeframe and undergo location verification to prevent the equipment from being handed over to another person after identity verification. Upon arrival, the system monitors the terminal's location information. When the distance between the inspector and the task destination falls within a pre-set distance threshold, a work permit is generated, allowing the inspector to proceed with the equipment inspection. Through the task execution interface, the surveyor collects basic equipment information, including model, manufacturer, and serial number. They also take panoramic photos of the equipment, photos of the nameplate, and a photo of the surveyor with the equipment. The image data is geotagged to ensure the photos were taken at the equipment's location and to record the time of day to prevent falsification of historical photos. After completing the survey, the surveyor triggers the task submission command. The system obtains the surveyor's real-time terminal location information and calculates the submission verification distance between the surveyor's current location and the task destination, ensuring that the task was submitted at the equipment's location and not as a remote submission of historical data. If the submission verification distance does not exceed a second preset distance threshold, the system further extracts the verification pass timestamp, calculates the task execution time, and compares it with the preset time limit for the task type to determine whether the task execution time is within a reasonable range. If the calculated time difference meets the requirements, the system deems the task valid and stores the task data in a data-linked manner. When storing the data, the survey task execution data is linked to the verification pass timestamp, initial verification distance, and submission verification distance to ensure the integrity and traceability of the task data. The storage method can be database storage or combined with blockchain evidence to ensure that the data cannot be tampered with, so as to facilitate future review and query.

[0147] In the healthcare sector, remote imaging diagnosis tasks require ensuring that doctors review images and submit diagnostic reports at authorized locations. Traditionally, doctors may conduct remote image review at non-designated hospitals or on private equipment, compromising the credibility of diagnostic data. This system can be used to manage imaging diagnosis tasks and ensure that doctors review images within authorized medical institutions. After accepting a task, doctors must first undergo identity verification to ensure they are authorized. After successful authentication, the system initiates a countdown, requiring the doctor to enter a designated reading room within a set time. Once the doctor enters the reading room, the system monitors the terminal's location. When the initial verification distance from the reading room meets the required distance, the system generates a permission to access the image data. After the doctor completes the review, he or she submits the diagnostic report. The system obtains the terminal's real-time location information and calculates the submission verification distance to ensure that the doctor submits the diagnostic report at an authorized location, rather than remotely. Once the submission verification distance meets the required distance, the system extracts the verification pass timestamp, calculates the task execution time, and determines whether the diagnostic report was submitted within the preset time limit. If the time validity status is valid, the system will associate the task data with the time and space verification information to ensure the security and traceability of the diagnostic data.

[0148] In the financial industry, insurance claims surveys require that surveyors complete the survey at the accident scene, rather than submitting historical images remotely, to prevent fraud. This system can be used to manage insurance survey tasks, ensuring that surveyors perform their tasks at the appropriate time and location. After accepting a task, the surveyor undergoes identity verification to ensure they are authorized. Once identity verification is passed, the system initiates a countdown, requiring the surveyor to arrive at the accident scene within a specified timeframe. Upon arrival, the system monitors the surveyor's terminal location. When the initial verification distance from the accident scene meets the required distance, a work permit is generated, allowing the surveyor to collect accident images, vehicle damage data, and other data. Upon completion of the survey, the surveyor submits the task data. The system obtains the terminal's real-time location information and calculates the submission verification distance, ensuring that the surveyor submits the data at the accident scene. Once the submission verification distance meets the required distance, the system extracts the verification pass timestamp, calculates the task execution time, and compares it against pre-set time limits to ensure the task has not timed out. The system associates the survey task data with spatiotemporal verification information and can integrate blockchain evidence storage to ensure data immutability. If an anomaly occurs during a survey task, such as a submitted distance exceeding a threshold or an abnormally long execution time, the system can trigger a secondary verification mechanism, requiring the surveyor to provide additional imagery or undergo a second identity verification to ensure data authenticity and reliability. The system can incorporate supplementary verification mechanisms to address data anomalies that may arise during survey tasks. For example, if the submitted verification distance exceeds a preset range, the system can require the surveyor to reposition the task. If the task execution time is too short or exceeds the preset time range, the system can flag the task as abnormal and trigger a manual review process, requiring the surveyor to provide additional on-site images or undergo a second identity verification to ensure the authenticity of the task data.

[0149] Through data-associative storage, we ensure the integrity of task execution data and spatiotemporal verification information, improving the traceability of task execution. By combining database indexing with blockchain evidence storage, we improve the security of task data and prevent tampering or misuse. We also optimize data storage methods to ensure efficient large-scale task data storage and adapt to diverse business needs.

[0150] The present invention relates to the field of artificial intelligence technology and can be applied to business scenarios such as medical health, financial technology and leasing. It discloses a method for verifying the authenticity of an operation, including: performing operator identity verification and generating a verification record containing a verification pass timestamp; starting a countdown mechanism and monitoring the terminal location information during the countdown period; when the initial verification distance between the terminal location information and the task destination meets a first preset distance threshold, generating an operation permit instruction; receiving on-site task execution data containing equipment feature data and geo-tagged images according to the operation permit instruction. In response to the task submission instruction, the terminal real-time location information is obtained and the submission verification distance is determined; when the submission verification distance meets a second preset distance threshold, the verification pass timestamp in the verification record is extracted; based on the time difference between the verification pass timestamp and the current time, a time validity status is generated, and when the status is valid, the on-site task execution data and the spatiotemporal verification information are stored in data association. The present invention realizes dual verification of the operator's identity and the authenticity of the work location by combining identity verification and location verification; limits the effective operation time after identity verification through a countdown mechanism to prevent the risk of the equipment being handed over to others to perform the task after identity verification; ensures that the operator is actually performing the task at the target location by comparing the initial verification distance with the submitted verification distance, and prevents historical data from impersonating existing survey data; and combines with the time verification mechanism to further prevent anomalies between the work permission time and the actual submission time, thereby ensuring the real-time and traceability of task execution.

[0151] In one embodiment, the above S10 includes:

[0152] S101, receiving a job start instruction and parsing the task identifier and operator account information in the job start instruction;

[0153] S102, determining corresponding biometric verification parameters according to the task identifier, the biometric verification parameters including a liveness detection sensitivity level, a verification threshold, and a biometric modality type;

[0154] S103, based on the biometric modality type, triggering the biometric recognition module and calling the terminal image acquisition device to obtain the operator's biometric image;

[0155] S104, performing a liveness detection and verification operation on the biometric image, and adjusting a determination threshold of dynamic activity verification in the liveness detection and verification operation based on the liveness detection sensitivity level;

[0156] S105, when the liveness detection verification is passed, extracting a static feature vector from the biometric image, and performing a similarity comparison between the static feature vector and a pre-stored registration feature template corresponding to the operator account information to obtain a similarity comparison result;

[0157] S106, when the similarity comparison result exceeds the verification threshold, generating a biometric verification pass signal;

[0158] S107, binding the biometric verification pass signal with the current terminal device identification code and the task identifier, and generating a verification record including the verification pass timestamp, the current terminal device identification code and the task identifier.

[0159] In this embodiment, during the job initiation phase, to ensure the authenticity of the task executor, biometric identity verification is required, and a timestamp of successful verification is recorded. The biometric recognition module can use facial recognition, iris recognition, fingerprint recognition, or palm vein recognition, and the specific selection can be adapted based on the security requirements of the task and the equipment conditions.

[0160] When a job is started, the system receives the job start instruction and parses the task identifier and operator account information contained in it. The task identifier is used to uniquely identify the current task, while the operator account information is used to match the authorized executor.

[0161] The accuracy of identity verification depends on multiple parameter configurations, including:

[0162] The liveness detection sensitivity level determines the strictness of liveness detection, such as requiring the operator to make specific expressions or movements to prevent photos or videos from deceiving the system;

[0163] Verification threshold, which sets the minimum similarity standard for biometric matching to avoid misidentification or identity fraud;

[0164] Biometric modality type determines which biometric recognition method is used, such as face recognition, iris recognition, or fingerprint recognition, to adapt to different device capabilities and task requirements.

[0165] Based on the biometric modality type, the system triggers the biometric recognition module and uses the terminal's image acquisition device to obtain the operator's biometric image. This image acquisition can use a high-resolution camera or an infrared camera, combined with illumination compensation technology to improve recognition accuracy in low-light environments.

[0166] Liveness detection is a key step in identity verification, often requiring the user to perform dynamic actions, such as blinking, opening their mouth, or turning their head, to verify the authenticity of the image data. The system dynamically adjusts the liveness detection threshold based on the liveness detection sensitivity level, ensuring both protection against spoofing attacks and adaptability to different user habits.

[0167] Once liveness detection is passed, the system extracts static feature vectors from the biometric image, such as facial key points, iris texture, or fingerprint features, and compares them with pre-stored registered feature templates associated with the operator's account information. This comparison can be performed using a deep learning neural network to calculate a similarity score or using a feature point matching algorithm to compare feature vectors.

[0168] If the similarity comparison result exceeds the verification threshold, the system generates a biometric verification pass signal, indicating that the operator's identity has been successfully authenticated and allowing them to continue the task. To prevent identity authentication information from being tampered with, the system binds the verification pass signal to the current terminal device identification code and task identifier and generates a verification record with a verification pass timestamp to ensure that identity verification information can be traced during subsequent task execution.

[0169] Based on the biometric function of the mobile terminal, the local face recognition algorithm can be called when the task is started to complete identity verification, and the biometric template can be stored in combination with the terminal's security chip to ensure data security.

[0170] Another approach is cloud-based authentication. After the terminal collects biometric images, the data is encrypted and transmitted to a remote server. A cloud-based AI model compares the data and returns the verification results. This approach is suitable for scenarios that require high computing power, such as iris recognition or high-precision facial recognition.

[0171] For scenarios requiring offline identity authentication, local biometric templates can be preloaded, and feature comparison can be completed on the terminal device using edge computing technology to avoid identity verification affected by unstable network connections.

[0172] To improve security, two-factor authentication can be used, which combines biometrics with password input to ensure that even if the biometric features are forged, authentication cannot be bypassed.

[0173] This embodiment uses biometric recognition technology to accurately verify the operator's identity, preventing the risk of identity theft or remote manipulation during task execution. Combining liveness detection with dynamic threshold adjustment improves authentication security and prevents static image spoofing attacks. The stored verification results ensure traceability of the task execution process, enhancing the authenticity and security of task data.

[0174] In one embodiment, the above S20 includes:

[0175] S201, parsing the verification pass timestamp in the verification record and triggering a countdown mechanism start instruction;

[0176] S202, determining a countdown end time point based on the verification timestamp;

[0177] S203, calling the terminal positioning module to obtain the real-time location information of the terminal at a preset sampling frequency before the countdown ends;

[0178] S204: Bind the real-time terminal location information obtained each time with the corresponding collection timestamp to generate terminal location information including multiple real-time terminal location information and corresponding collection timestamps.

[0179] In this embodiment, to ensure that the operator arrives at the task execution location within the specified time after completing identity verification, the system activates a countdown mechanism and continuously monitors the terminal's location during the countdown period. This countdown mechanism prevents the operator from handing the device over to someone else to perform the task after passing identity verification, thereby improving the authenticity and traceability of task execution.

[0180] The system parses the verification pass timestamp in the authentication record and triggers the countdown mechanism to start. The verification pass timestamp indicates the time when the operator completed identity verification. This time is the starting time of the countdown, ensuring that subsequent location information monitoring is calculated based on the time of successful identity verification. The specific duration of the countdown mechanism can be configured based on the task type, task execution environment, and security level. For example, for a short inspection task, the countdown may be set to a few minutes, while for a longer equipment survey task, it can be extended to tens of minutes or longer.

[0181] The countdown end time is calculated by adding the verified timestamp to the countdown duration. The system continuously monitors the terminal's location during the countdown period. During this monitoring process, the system invokes the terminal positioning module and obtains the terminal's real-time location information at a preset sampling frequency. The sampling frequency can be adjusted based on task requirements. For example, the sampling frequency can be increased in scenarios requiring high accuracy, while it can be reduced in resource-constrained scenarios to reduce device energy consumption.

[0182] Each time the system acquires the terminal's real-time location information, it binds this location information to the acquisition timestamp to form complete trajectory data. This data can be used to analyze the operator's movements during the countdown period to determine whether they are moving within a reasonable range to the task execution location. If the collected location information indicates that the operator has not arrived at the reasonable task execution location within the countdown period, the system can terminate the task or require re-identification.

[0183] This embodiment monitors the terminal's location during the countdown period to ensure that the operator arrives at the task location on time after identity verification, preventing the device from being transferred to another user after identity verification. Combined with dynamic sampling frequency adjustment, this improves positioning data accuracy while reducing device energy consumption. Trajectory analysis can further identify abnormal task behavior, enhancing the credibility of task data.

[0184] In one embodiment, the above S30 includes:

[0185] S301, parsing the task identifier in the verification record, and extracting the task destination coordinate data and plane coordinate system parameters corresponding to the task identifier from the task database;

[0186] S302, establishing a plane rectangular coordinate system conversion model according to the plane coordinate system parameters;

[0187] S303, traversing multiple terminal real-time location information in the terminal location information, inputting the currently traversed terminal real-time location information into the plane rectangular coordinate system conversion model and generating a converted terminal coordinate point;

[0188] S304, inputting the task destination coordinate data into the plane rectangular coordinate system conversion model and generating a converted task coordinate point;

[0189] S305, calculating a plane projection distance value between the converted terminal coordinate point and the converted task coordinate point;

[0190] S306, associating the plane projection distance value with the acquisition timestamp of the current traversed terminal real-time location information and storing it as a distance verification record;

[0191] S307, detecting the plane projection distance values in all distance verification records and determining whether there is at least one plane projection distance value that is less than or equal to a first preset distance threshold;

[0192] S308, when there is at least one plane projection distance value that is less than or equal to the first preset distance threshold, extracting the minimum plane projection distance value and the acquisition timestamp associated with the minimum plane projection distance value from the corresponding distance verification record;

[0193] S309, verifying whether the acquisition timestamp is within the countdown period of the countdown mechanism;

[0194] S310: When the acquisition timestamp is within the countdown period of the countdown mechanism, the acquisition timestamp is marked as an initial verification timestamp and a work permission instruction is generated.

[0195] In this embodiment, when the initial verification distance between the terminal's location and the task destination is determined to be within a first preset distance threshold, a work permit is generated to confirm that the operator has arrived at the task execution area and allow them to proceed with subsequent task operations. To ensure the accuracy of location verification, the system performs a series of steps, including coordinate conversion, distance calculation, and timestamp verification, to ensure that the operator has arrived at the task destination within the specified time after identity verification.

[0196] First, the system parses the task identifier in the verification record and extracts the task destination coordinate data corresponding to the task identifier from the task database, along with the plane coordinate system parameters applicable to the task area. Different task locations may use different coordinate systems, such as geographic coordinate systems (latitude and longitude) or projected coordinate systems (such as the UTM coordinate system). Therefore, the system needs to establish a plane rectangular coordinate system conversion model based on the coordinate system of the task area to ensure the accuracy of distance calculations.

[0197] To process multiple acquisitions of terminal location information, the system iterates through all recorded real-time terminal location information and inputs each terminal location into a coordinate transformation model to generate converted terminal coordinate points. Simultaneously, the system also inputs the task destination coordinate data into the same coordinate transformation model to generate converted task coordinate points for unified calculation.

[0198] Next, the system calculates the projected distance between the converted terminal coordinates and the converted task coordinates. This distance reflects the straight-line distance between the operator's current location and the task's destination, and can be used to determine whether the operator has approached the task's execution area. The calculated projected distance is then linked to the acquisition timestamp of the terminal's real-time location information and stored as a distance verification record to ensure traceability of location verification data.

[0199] Among all recorded planar projection distance values, the system checks whether there is at least one distance value less than or equal to a first preset distance threshold. If there is a distance value that meets the condition, the system extracts the smallest planar projection distance value and its corresponding acquisition timestamp as the most reliable location information for further verification.

[0200] To prevent task performers from circumventing the countdown mechanism or forging historical location data, the system verifies that the collection timestamp falls within the countdown period. The countdown period requires operators to arrive at the task execution location within a certain timeframe after identity verification, ensuring the timeliness and authenticity of the task. If the collection timestamp falls within the countdown period, indicating that the operator arrived at the task location within the specified timeframe, the system marks the timestamp as the initial verification timestamp and formally generates a work permit, allowing the operator to proceed with subsequent task operations.

[0201] A fusion of GPS and inertial navigation can be used to improve the accuracy of terminal location information. If the mobile terminal device supports high-precision GNSS (such as RTK-GNSS), the system can directly use GPS data for coordinate conversion and calculate the distance from the terminal to the mission destination. If the terminal's location signal is interfered with or lacks accuracy, inertial navigation technology can be combined to perform trajectory calculation using accelerometer and gyroscope data to improve positioning accuracy.

[0202] Another method is verification based on cellular or Wi-Fi positioning, which is suitable for indoor environments or those with weak GPS signals. The terminal device can calculate its current location by scanning the signal strength of surrounding base stations or Wi-Fi access points, and then convert coordinates based on an existing geographic database to achieve precise positioning for indoor tasks.

[0203] To improve computational efficiency, incremental distance calculation can be used. For each new terminal location, the system only calculates the distance between the latest coordinate point and the mission destination, without recalculating all historical location information. This reduces the computational burden and improves real-time processing capabilities.

[0204] In terms of data storage, blockchain technology can be combined to store distance verification records to ensure that the timestamp and location information of task execution cannot be tampered with, thereby improving the credibility of task data.

[0205] This embodiment improves the accuracy of location verification of task executors through a combination of coordinate conversion, distance calculation, and timestamp verification, ensuring that operators arrive at the task location within the specified time and preventing the device from being handed over to others to perform the task after identity verification.

[0206] In one embodiment, the above S40 includes:

[0207] S401, parsing the task execution parameters in the operation permission instruction, wherein the task execution parameters include the device information collection strategy and the image marking requirements;

[0208] S402, activating a task execution interface based on the task execution parameters and calling a terminal data acquisition module;

[0209] S403, the terminal data acquisition module acquires characteristic data of the target device based on the device information acquisition strategy;

[0210] S404, calling the terminal image acquisition device to capture a panoramic image of the target device, and adding a geographic tag including latitude and longitude and a timestamp to the panoramic image according to the image tagging requirement;

[0211] S405, encapsulating the characteristic data of the target device and the panoramic image with the added geographical mark into a field task execution data packet;

[0212] S406: Transmit the on-site task execution data packet to the verification server through the task execution interface.

[0213] In this embodiment, after a task is approved, the system activates the task execution interface to ensure that surveyors can collect device information and image data according to the task requirements, and to ensure the authenticity and traceability of the data. Activation of the task execution interface is governed by the work permit instruction, which contains task execution parameters that regulate task collection behavior and ensure that data collection and upload for different types of tasks are performed according to pre-set rules.

[0214] First, parse the task execution parameters in the job permission instruction, which include:

[0215] Equipment information collection strategy: Define the equipment characteristic data that needs to be collected during the survey, such as equipment model, manufacturer, production date, nameplate information, etc., to ensure the integrity and standardization of task data;

[0216] Image tagging requirements: Specifies additional information that image data must contain, such as geographic location information (latitude and longitude), shooting timestamp, shooting angle, etc., to prevent the falsification of historical photos.

[0217] Based on the task execution parameters, the system activates the task execution interface and calls the terminal data acquisition module. The data acquisition module is responsible for extracting device information from the terminal's sensors, databases, or external data sources, and synchronizing with the server when necessary to ensure data integrity and real-time performance.

[0218] During the task execution, the system obtains the characteristic data of the target device through the terminal data collection module according to the device information collection strategy. The data collection methods may include:

[0219] Barcode / QR code scanning: Use the terminal camera to scan the serial number or nameplate information on the device and automatically extract the device identification;

[0220] NFC / RFID reading: For devices that support NFC or RFID, device information can be automatically identified through wireless tags to improve collection efficiency;

[0221] Manual input and database matching: If automatic recognition is not possible, the surveyor can manually input the equipment information and compare it with the pre-stored database to ensure data accuracy.

[0222] After acquiring the device feature data, the system calls the terminal image acquisition device to capture a panoramic image of the target device to ensure that the image data can fully reflect the device status. At the same time, according to the image tagging requirements, geographic tag information is added to the image, including:

[0223] Latitude and longitude data: Ensures that the image is actually taken at the device's location to prevent remote shooting or false image submission;

[0224] Timestamp: records the time when the image was taken to verify whether the image meets the timeliness requirements of the task;

[0225] Other optional tags: such as the device’s unique identification code, surveyor’s identity information, etc., to improve the credibility of the image data.

[0226] The collected data needs to be encapsulated, and the characteristic data of the target device and the image data with added geo-tags are encapsulated into a field task execution data package to ensure that all relevant information is stored and transmitted in a unified manner and improve data integrity.

[0227] After data encapsulation, the system transmits the on-site task execution data package to the verification server through the task execution interface for subsequent task review and evidence storage. During the data transmission process, encryption can be used to ensure the security and integrity of the data during transmission.

[0228] This embodiment uses a task execution interface to ensure standardized execution of survey tasks, improve the automation of data collection, reduce human intervention, and enhance task authenticity. Image tagging technology ensures the authenticity and traceability of image data, preventing false submissions. Data encapsulation and encrypted transmission improve data integrity and security, preventing data tampering or loss during transmission.

[0229] In one embodiment, the above S50 includes:

[0230] S501, receiving a task submission instruction, and calling a terminal positioning module according to the task submission instruction to obtain real-time geographic coordinate data;

[0231] S502, extracting task destination coordinate data corresponding to the task identifier in the job start instruction from a task database;

[0232] S503, determining the spatial straight-line distance between the real-time geographic coordinate data and the task destination coordinate data;

[0233] S504: Perform error correction on the spatial straight-line distance according to preset positioning error compensation parameters to generate a distance for submission verification.

[0234] In this embodiment, after the task is completed, the system needs to verify the operator's final location information to ensure that the surveyor has actually completed the task at the task location. This step compares the terminal positioning data with the task destination data and, incorporating an error correction mechanism, calculates the final submission verification distance to verify the authenticity of the task execution.

[0235] First, the system receives a task submission command, which can be triggered by the surveyor upon task completion or automatically executed by the system upon expiration of the task time. The system interprets the task submission command and invokes the terminal positioning module to obtain real-time geographic coordinate data. The terminal positioning module can obtain the current device's latitude and longitude information based on GPS, Beidou, Wi-Fi, or cellular base station data. For scenarios requiring higher precision, high-precision positioning can be achieved by combining inertial navigation or differential GPS (RTK-GNSS).

[0236] The system then extracts the task destination coordinate data corresponding to the task identifier from the task database. The task destination coordinates can include static geographic coordinates (such as fixed equipment points) or dynamic task ranges (such as the real-time location of mobile devices) to adapt to different task requirements.

[0237] After obtaining the real-time geographic coordinate data of the current device and the coordinate data of the task destination, the system calculates the spatial straight-line distance between the two. This calculation is usually based on spherical geometry formulas or plane projection transformation methods:

[0238] Spherical geometry calculation is applicable to global positioning scenarios and calculates the spherical distance between two points based on the Haversine formula;

[0239] Plane projection transformation is suitable for regional tasks. It calculates the Euclidean distance between two points by converting the coordinate projection into a plane rectangular coordinate system to improve the calculation accuracy.

[0240] Since terminal positioning technology may have certain errors in different environments, the system corrects the calculated spatial straight-line distance based on the preset positioning error compensation parameters to generate the final submission verification distance. The error compensation parameters can be based on:

[0241] GPS signal quality: When the GPS signal is weak, the system can increase a certain error compensation value to reduce the probability of misjudgment;

[0242] Indoor and outdoor environmental factors: Indoor tasks may be interfered with by Wi-Fi or Bluetooth beacons. The system can use multi-source fusion algorithms to improve positioning accuracy.

[0243] Equipment movement trajectory: Through historical trajectory analysis, the system can adjust the distance calculation of static and dynamic tasks to adapt to the actual working environment.

[0244] Ultimately, the distance submitted for verification will be used to verify the authenticity of subsequent tasks, ensuring that the final submitted position of the surveyor meets the task requirements and can serve as a basis for abnormal behavior detection.

[0245] This embodiment compares the task destination coordinates with the terminal's real-time location information to ensure the authenticity of the task submission location and prevent remote submission or falsification of task execution data. Incorporating an error correction mechanism improves positioning accuracy and adapts to positioning requirements in diverse environments. The use of multi-source positioning enhances system usability in GPS-restricted environments and ensures the credibility and traceability of task data.

[0246] In one embodiment, the above S70 includes:

[0247] S701, parsing the task identifier in the verification record, and extracting the task type code and location feature parameters corresponding to the task identifier from the task database;

[0248] S702: Match a preset time limit condition mapping table according to the task type code, and obtain a basic time limit threshold corresponding to the task type code based on the time limit condition mapping table;

[0249] S703, determining a timeliness threshold correction coefficient according to the regional positioning accuracy level in the position characteristic parameters;

[0250] S704, performing a product operation on the basic aging threshold and the aging threshold correction coefficient to generate a dynamic aging threshold;

[0251] S705, obtaining the current time and determining the absolute time difference between the current time and the verification pass timestamp;

[0252] S706, comparing the absolute time difference with the dynamic aging threshold;

[0253] S707, when the absolute time difference is less than or equal to the dynamic aging threshold, marking the aging validity status as valid;

[0254] S708, when the absolute time difference is greater than the dynamic aging threshold, marking the aging validity status as invalid;

[0255] S709: Associate the time validity status with the task identifier.

[0256] In this embodiment, a dynamic timeliness threshold is generated by calculating the time difference between the verification timestamp and the current time, taking into account factors such as task type and regional positioning accuracy. This threshold is then used to determine the validity of task execution data. This mechanism effectively addresses the issue of invalid data caused by delayed or expired task data, ensuring the authenticity and availability of task data.

[0257] The system first parses the task identifier in the verification record and extracts the task type code and location feature parameters corresponding to the identifier from the task database. The task identifier uniquely identifies each task, while the task type code is used to identify the type of task (such as equipment inspection, medical diagnosis, claims investigation, etc.), which may have different timeliness requirements. The location feature parameters describe the positioning accuracy requirements required for task execution. For example, the city center may require higher positioning accuracy, while remote areas may accept lower accuracy. These parameters are crucial for subsequent timeliness verification.

[0258] Based on the task type code, the system retrieves the corresponding basic timeliness threshold from the timeliness condition mapping table. The basic timeliness threshold defines the maximum validity period of data during task execution. Different task types may have different timeliness requirements. For example, an equipment inspection task may require data to be submitted within 2 hours, while an accident site claims settlement task may have a timeliness limit of 3 hours or longer. The timeliness condition mapping table allows flexible configuration of timeliness standards for various tasks, ensuring that the system can perform appropriate timeliness verification based on different task types.

[0259] The regional positioning accuracy level is a significant factor influencing timeliness verification, especially for tasks requiring high geolocation accuracy. For example, a hospital equipment inspection task might require accuracy within 5 meters, while an agricultural inspection task in a vast rural area might only require 100 meters of positioning accuracy. Therefore, the system calculates a timeliness threshold correction factor based on the regional positioning accuracy level in the location feature parameters, which is used to dynamically adjust the basic timeliness threshold.

[0260] The system generates a dynamic timeliness threshold by multiplying the basic timeliness threshold by the timeliness threshold correction factor. This dynamic timeliness threshold is more flexible than the basic timeliness threshold and can be adjusted based on the actual mission environment (such as the positioning accuracy of the mission location and the signal quality during mission execution). This allows the system to automatically adjust the timeliness threshold based on the specific requirements of the mission area, ensuring that each mission's timeliness verification is tailored to the actual situation.

[0261] After calculating the dynamic timeliness threshold, the system obtains the current time and compares it with the verification pass timestamp to obtain the absolute time difference. The verification pass timestamp records the time of identity verification for the task and marks the start time of the task. All subsequent operations must be compared with this time point to ensure the timeliness of the task data.

[0262] The system compares the absolute time difference with the dynamic time threshold to determine the data's validity. If the absolute time difference is less than or equal to the dynamic time threshold, the task data is considered valid; if the time difference exceeds the dynamic time threshold, the task data is marked as invalid. This process ensures that task data is accurately recorded and used within its validity period while avoiding the risk of data expiration or misuse.

[0263] Finally, the system associates the timeliness status with the task identifier. This association ensures that each task's data has been time-validated, facilitating subsequent tracking and auditing. This allows the system to monitor and record the timeliness status of tasks throughout the entire process, ensuring that task data consistently meets pre-set timeliness requirements throughout execution.

[0264] This embodiment dynamically adjusts timeliness based on task type and location characteristics, allowing the system to more flexibly handle the timeliness verification requirements of different tasks, avoiding misjudgments of timeliness due to changes in task environment or task type. The application of dynamic timeliness thresholds ensures that each task can be time-validated according to appropriate standards in different environments. By associating timeliness status tags with task data, the system ensures the traceability and reliability of task data throughout its lifecycle, preventing the misuse of expired data and improving data credibility and business transparency.

[0265] In one embodiment, a device for verifying the authenticity of an operation is provided, which corresponds one-to-one to the method for verifying the authenticity of an operation in the above embodiment. Figure 3 , Figure 3 This is a functional module diagram of a preferred embodiment of the operation authenticity verification device of the present invention. It includes a biometric recognition module 10, a countdown control module 20, a location monitoring module 30, a task execution module 40, a terminal positioning module 50, a data verification module 60, a time validity verification module 70, and a data storage module 80. Each functional module is described in detail below:

[0266] The biometric identification module 10 is configured to respond to a job start instruction and trigger the biometric identification module, perform an operator identity verification operation through the biometric identification module and generate a verification record including a verification pass timestamp;

[0267] A countdown control module 20 is configured to start a countdown mechanism based on the verification record and monitor the terminal location information during a countdown period of the countdown mechanism;

[0268] The location monitoring module 30 is configured to generate a work permission instruction including a timestamp when it is detected that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold;

[0269] a task execution module 40 for activating a task execution interface according to the work permit instruction and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0270] The terminal positioning module 50 is used to respond to the task submission instruction and obtain the real-time location information of the terminal, and determine the submission verification distance between the real-time location information of the terminal and the task destination;

[0271] A data verification module 60 is configured to extract a verification pass timestamp from the verification record when the submitted verification distance does not exceed a second preset distance threshold;

[0272] A time validity verification module 70 is used to determine the time validity difference between the verification pass timestamp and the current time, and generate a time validity status based on the time validity difference and a preset time validity condition;

[0273] The data storage module 80 is used to associate and store the on-site task execution data with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance when the time validity status is valid.

[0274] In one embodiment, the biometric recognition module 10 is specifically configured to:

[0275] Receive a job start instruction and parse the task identifier and operator account information in the job start instruction;

[0276] Determining corresponding biometric verification parameters according to the task identifier, the biometric verification parameters including a liveness detection sensitivity level, a verification threshold, and a biometric modality type;

[0277] Based on the biometric modality type, triggering the biometric recognition module and calling the terminal image acquisition device to obtain the operator's biometric image;

[0278] Performing a liveness detection and verification operation on the biometric image, and adjusting a determination threshold of dynamic activity verification in the liveness detection and verification operation based on the liveness detection sensitivity level;

[0279] When the liveness detection verification is passed, a static feature vector is extracted from the biometric image, and the static feature vector is compared with a pre-stored registration feature template corresponding to the operator account information to obtain a similarity comparison result;

[0280] When the similarity comparison result exceeds the verification threshold, generating a biometric verification pass signal;

[0281] The biometric verification pass signal is bound to the current terminal device identification code and the task identifier to generate a verification record including the verification pass timestamp, the current terminal device identification code and the task identifier.

[0282] In one embodiment, the countdown control module 20 is specifically configured to:

[0283] Parsing the verification pass timestamp in the verification record and triggering the countdown mechanism start instruction;

[0284] Determining a countdown end time point based on the verification timestamp;

[0285] Calling the terminal positioning module to obtain the real-time location information of the terminal at a preset sampling frequency before the countdown ends;

[0286] The real-time terminal location information obtained each time is bound to the corresponding collection timestamp to generate terminal location information containing multiple real-time terminal location information and corresponding collection timestamps.

[0287] In one embodiment, the location monitoring module 30 is specifically configured to:

[0288] parsing the task identifier in the verification record, and extracting the task destination coordinate data and plane coordinate system parameters corresponding to the task identifier from a task database;

[0289] Establishing a plane rectangular coordinate system conversion model according to the plane coordinate system parameters;

[0290] Traversing multiple terminal real-time location information in the terminal location information, inputting the currently traversed terminal real-time location information into the plane rectangular coordinate system conversion model and generating a converted terminal coordinate point;

[0291] Inputting the task destination coordinate data into the plane rectangular coordinate system conversion model and generating a converted task coordinate point;

[0292] Calculating a plane projection distance value between the converted terminal coordinate point and the converted task coordinate point;

[0293] The plane projection distance value is associated with the acquisition timestamp of the real-time location information of the terminal currently traversed and stored as a distance verification record;

[0294] Detecting the plane projection distance values in all distance verification records and determining whether there is at least one plane projection distance value that is less than or equal to a first preset distance threshold;

[0295] When there is at least one plane projection distance value less than or equal to the first preset distance threshold, extracting the minimum plane projection distance value and the acquisition timestamp associated with the minimum plane projection distance value from the corresponding distance verification record;

[0296] Verifying whether the acquisition timestamp is within the countdown period of the countdown mechanism;

[0297] When the acquisition timestamp is within the countdown period of the countdown mechanism, the acquisition timestamp is marked as an initial verification timestamp and a work permission instruction is generated.

[0298] In one embodiment, the task execution module 40 is specifically configured to:

[0299] Parsing the task execution parameters in the operation permission instruction, wherein the task execution parameters include device information collection strategy and image marking requirements;

[0300] Activate the task execution interface based on the task execution parameters and call the terminal data acquisition module;

[0301] The terminal data acquisition module acquires characteristic data of the target device based on the device information acquisition strategy;

[0302] Invoking a terminal image acquisition device to capture a panoramic image of the target device, and adding a geographic tag including latitude and longitude and a timestamp to the panoramic image according to the image tagging requirement;

[0303] Encapsulating the characteristic data of the target device and the panoramic image with added geographic tags into a field task execution data packet;

[0304] The on-site task execution data packet is transmitted to the verification server through the task execution interface.

[0305] In one embodiment, the terminal positioning module 50 is specifically configured to:

[0306] Receive a task submission instruction, and call a terminal positioning module to obtain real-time geographic coordinate data according to the task submission instruction;

[0307] Extracting task destination coordinate data corresponding to the task identifier in the job start instruction from a task database;

[0308] Determining the spatial straight-line distance between the real-time geographic coordinate data and the task destination coordinate data;

[0309] According to the preset positioning error compensation parameters, the spatial straight-line distance is corrected and the distance submitted for verification is generated.

[0310] In one embodiment, the time validity verification module 70 is specifically configured to:

[0311] Parsing the task identifier in the verification record, and extracting the task type code and location feature parameters corresponding to the task identifier from a task database;

[0312] Matching a preset time limit condition mapping table according to the task type code, and obtaining a basic time limit threshold corresponding to the task type code based on the time limit condition mapping table;

[0313] Determining a time-sensitive threshold correction coefficient based on the regional positioning accuracy level in the position feature parameters;

[0314] Performing a product operation on the basic aging threshold and the aging threshold correction coefficient to generate a dynamic aging threshold;

[0315] Obtaining the current time and determining the absolute time difference between the current time and the verification pass timestamp;

[0316] Comparing the absolute time difference with the dynamic aging threshold;

[0317] When the absolute time difference is less than or equal to the dynamic aging threshold, the aging validity status is marked as valid;

[0318] When the absolute time difference is greater than the dynamic aging threshold, the aging validity status is marked as invalid;

[0319] The time validity status is associated with the task identifier.

[0320] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, memory, network interface and database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external user terminal via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the server side of a method for verifying the authenticity of a job.

[0321] In one embodiment, a computer device is provided. The computer device may be a user terminal, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, memory, network interface, display screen and input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the user side of a method for verifying the authenticity of a job.

[0322] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are performed:

[0323] Responding to a job start instruction and triggering a biometric identification module, performing an operator identity verification operation through the biometric identification module and generating a verification record including a verification pass timestamp;

[0324] Initiating a countdown mechanism based on the verification record, and monitoring the terminal location information during the countdown period of the countdown mechanism;

[0325] When it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp;

[0326] activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0327] Responding to a task submission instruction and obtaining the real-time location information of the terminal, and determining a submission verification distance between the real-time location information of the terminal and the task destination;

[0328] When the submitted verification distance does not exceed a second preset distance threshold, extracting a verification pass timestamp in the verification record;

[0329] Determine the time difference between the verification pass timestamp and the current time, and generate a time validity status based on the time difference and a preset time condition;

[0330] When the time validity status is valid, the on-site task execution data is stored in association with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance.

[0331] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0332] Responding to a job start instruction and triggering a biometric identification module, performing an operator identity verification operation through the biometric identification module and generating a verification record including a verification pass timestamp;

[0333] Initiating a countdown mechanism based on the verification record, and monitoring the terminal location information during the countdown period of the countdown mechanism;

[0334] When it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp;

[0335] activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface;

[0336] Responding to a task submission instruction and obtaining the real-time location information of the terminal, and determining a submission verification distance between the real-time location information of the terminal and the task destination;

[0337] When the submitted verification distance does not exceed a second preset distance threshold, extracting a verification pass timestamp in the verification record;

[0338] Determine the time difference between the verification pass timestamp and the current time, and generate a time validity status based on the time difference and a preset time condition;

[0339] When the time validity status is valid, the on-site task execution data is stored in association with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance.

[0340] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can be found in the relevant descriptions of the server side and the user side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0341] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0342] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0343] It should be noted that if any software tools or components other than those of the Company appear in the embodiments of this application, they are merely for illustration and do not represent actual use. The above embodiments are intended only to illustrate the technical solutions of the present invention, not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some of the technical features therein with equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for verifying the authenticity of an operation, characterized in that: The following steps are involved: Responding to a job start instruction and triggering a biometric identification module, performing an operator identity verification operation through the biometric identification module and generating a verification record including a verification pass timestamp; Initiating a countdown mechanism based on the verification record, and monitoring the terminal location information during the countdown period of the countdown mechanism; When it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp; activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface; Responding to a task submission instruction and obtaining the real-time location information of the terminal, and determining a submission verification distance between the real-time location information of the terminal and the task destination; When the submitted verification distance does not exceed a second preset distance threshold, extracting a verification pass timestamp in the verification record; Determine the time difference between the verification pass timestamp and the current time, and generate a time validity status based on the time difference and a preset time condition; When the time validity status is valid, the on-site task execution data is stored in association with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance, and the submitted verification distance.

2. The operation authenticity verification method according to claim 1, characterized in that: Responding to a job start instruction and triggering a biometric identification module, performing an operator identity verification operation through the biometric identification module and generating a verification record containing a verification pass timestamp, including: Receive a job start instruction and parse the task identifier and operator account information in the job start instruction; Determining corresponding biometric verification parameters according to the task identifier, the biometric verification parameters including a liveness detection sensitivity level, a verification threshold, and a biometric modality type; Based on the biometric modality type, triggering the biometric recognition module and calling the terminal image acquisition device to obtain the operator's biometric image; Performing a liveness detection and verification operation on the biometric image, and adjusting a determination threshold of dynamic activity verification in the liveness detection and verification operation based on the liveness detection sensitivity level; When the liveness detection verification is passed, a static feature vector is extracted from the biometric image, and the static feature vector is compared with a pre-stored registration feature template corresponding to the operator account information to obtain a similarity comparison result; When the similarity comparison result exceeds the verification threshold, generating a biometric verification pass signal; The biometric verification pass signal is bound to the current terminal device identification code and the task identifier to generate a verification record including the verification pass timestamp, the current terminal device identification code and the task identifier.

3. The operation authenticity verification method according to claim 1, characterized in that: Initiating a countdown mechanism based on the verification record, and monitoring the terminal location information within a countdown period of the countdown mechanism, including: Parsing the verification pass timestamp in the verification record and triggering the countdown mechanism start instruction; Determining a countdown end time point based on the verification timestamp; Calling the terminal positioning module to obtain the real-time location information of the terminal at a preset sampling frequency before the countdown ends; The real-time terminal location information obtained each time is bound to the corresponding collection timestamp to generate terminal location information containing multiple real-time terminal location information and corresponding collection timestamps.

4. The operation authenticity verification method according to claim 1, wherein: When it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold, generating a work permission instruction including a timestamp, including: parsing the task identifier in the verification record, and extracting the task destination coordinate data and plane coordinate system parameters corresponding to the task identifier from a task database; Establishing a plane rectangular coordinate system conversion model according to the plane coordinate system parameters; Traversing multiple terminal real-time location information in the terminal location information, inputting the currently traversed terminal real-time location information into the plane rectangular coordinate system conversion model and generating a converted terminal coordinate point; Inputting the task destination coordinate data into the plane rectangular coordinate system conversion model and generating a converted task coordinate point; Calculating a plane projection distance value between the converted terminal coordinate point and the converted task coordinate point; The plane projection distance value is associated with the acquisition timestamp of the real-time location information of the terminal currently traversed and stored as a distance verification record; Detecting the plane projection distance values in all distance verification records and determining whether there is at least one plane projection distance value that is less than or equal to a first preset distance threshold; When there is at least one plane projection distance value that is less than or equal to the first preset distance threshold, extracting the minimum plane projection distance value and the acquisition timestamp associated with the minimum plane projection distance value from the corresponding distance verification record; Verifying whether the acquisition timestamp is within the countdown period of the countdown mechanism; When the acquisition timestamp is within the countdown period of the countdown mechanism, the acquisition timestamp is marked as an initial verification timestamp and a work permission instruction is generated.

5. The operation authenticity verification method according to claim 1, characterized in that: activating a task execution interface according to the work permit instruction, and receiving on-site task execution data including equipment feature data and geo-tagged images through the task execution interface, including: Parsing the task execution parameters in the operation permission instruction, wherein the task execution parameters include device information collection strategy and image marking requirements; Activate the task execution interface based on the task execution parameters and call the terminal data acquisition module; The terminal data acquisition module acquires characteristic data of the target device based on the device information acquisition strategy; Invoking a terminal image acquisition device to capture a panoramic image of the target device, and adding a geographic tag including latitude and longitude and a timestamp to the panoramic image according to the image tagging requirement; Encapsulating the characteristic data of the target device and the panoramic image with added geographic tags into a field task execution data packet; The on-site task execution data packet is transmitted to the verification server through the task execution interface.

6. The operation authenticity verification method according to claim 1, characterized in that: Responding to a task submission instruction and obtaining the real-time location information of the terminal, and determining a submission verification distance between the real-time location information of the terminal and the task destination, including: Receive a task submission instruction, and call a terminal positioning module to obtain real-time geographic coordinate data according to the task submission instruction; Extracting task destination coordinate data corresponding to the task identifier in the job start instruction from a task database; Determining the spatial straight-line distance between the real-time geographic coordinate data and the task destination coordinate data; According to the preset positioning error compensation parameters, the spatial straight-line distance is corrected and the distance submitted for verification is generated.

7. The operation authenticity verification method according to claim 1, characterized in that: Determining a time difference between the verification pass timestamp and the current time, and generating a time validity status based on the time difference and a preset time condition, including: Parsing the task identifier in the verification record, and extracting the task type code and location feature parameters corresponding to the task identifier from a task database; Matching a preset time limit condition mapping table according to the task type code, and obtaining a basic time limit threshold corresponding to the task type code based on the time limit condition mapping table; Determining a time-sensitive threshold correction coefficient based on the regional positioning accuracy level in the position feature parameters; Performing a product operation on the basic aging threshold and the aging threshold correction coefficient to generate a dynamic aging threshold; Obtaining the current time and determining the absolute time difference between the current time and the verification pass timestamp; Comparing the absolute time difference with the dynamic aging threshold; When the absolute time difference is less than or equal to the dynamic aging threshold, the aging validity status is marked as valid; When the absolute time difference is greater than the dynamic aging threshold, the aging validity status is marked as invalid; The time validity status is associated with the task identifier.

8. An operation authenticity verification device, characterized in that: The operation authenticity verification device comprises: A biometric identification module, configured to respond to a job start instruction and trigger the biometric identification module, perform an operator identity verification operation through the biometric identification module and generate a verification record including a verification pass timestamp; A countdown control module, configured to start a countdown mechanism based on the verification record and monitor the terminal location information during the countdown period of the countdown mechanism; a location monitoring module, configured to generate a work permission instruction including a timestamp when it is monitored that the initial verification distance between the terminal location information and the task destination does not exceed a first preset distance threshold; a task execution module, configured to activate a task execution interface according to the work permit instruction, and receive on-site task execution data including equipment feature data and geo-tagged images through the task execution interface; The terminal positioning module is used to respond to the task submission instruction and obtain the real-time location information of the terminal, and determine the submission verification distance between the real-time location information of the terminal and the task destination; A data verification module, configured to extract a verification pass timestamp from the verification record when the submitted verification distance does not exceed a second preset distance threshold; A time validity verification module is used to determine the time validity difference between the verification pass timestamp and the current time, and generate a time validity status based on the time validity difference and a preset time validity condition; The data storage module is used to associate and store the on-site task execution data with the spatiotemporal verification information including the verification pass timestamp, the initial verification distance and the submitted verification distance when the time validity status is valid.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a job authenticity verification program stored in the memory and capable of running on the processor. When the job authenticity verification program is executed by the processor, the steps of the job authenticity verification method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The storage medium stores a job authenticity verification program, which, when executed by a processor, implements the steps of the job authenticity verification method according to any one of claims 1 to 7.

Images