Part-time NFC (Near Field Communication) intelligent card punching method adaptive to multiple scenes

Abstract

The invention discloses a part-time job NFC (Near Field Communication) intelligent card punching method adaptive to multiple scenes. The method comprises the following steps: S1, configuring an NFC card punching voucher uniquely associated with the identity of a part-time job for the part-time job; s2, reading the NFC card punching voucher through an NFC interaction terminal deployed in different physical or logic scenes, and triggering a card punching event corresponding to the scene based on the scene deployed by the NFC interaction terminal; s3, verifying the read NFC card punching voucher information, and generating and uploading a card punching record containing scene information, time information and identity information after the verification is passed; and S4, according to a preset rule, carrying out isolated storage on the man-hour data in the card punching record according to dimensions, and according to a query condition, carrying out aggregation calculation on the man-hour data stored in different dimensions. Through fusion of the NFC technology and a multi-scene adaptation mechanism, the problems of scene adaptation, precise man-hour statistics and the like in part-time job attendance management are solved, and the method has the advantages of being low in cost, high in credibility and easy to operate.

Description

A part-time NFC smart check-in method adaptable to multiple scenarios Technical Field

[0001] This invention relates to the field of human resource management technology for part-time positions, specifically to a part-time NFC smart check-in method adaptable to multiple scenarios. Background Technology

[0002] With the booming development of the sharing economy and gig economy, part-time work has become an important part of the labor market. Compared with full-time work, part-time work has a series of distinct characteristics, such as fragmented working hours, highly dispersed work locations, high staff mobility, and frequent project switching. These characteristics make traditional attendance management models designed for full-time, fixed positions incompatible with the part-time field. Specifically, existing mainstream attendance methods have significant drawbacks in part-time scenarios: 1. Poor scenario adaptability: Fixed attendance machines (such as fingerprint and facial recognition machines) cannot meet the needs of mobile or temporary part-time scenarios such as exhibitions, promotions, and delivery. App attendance systems that rely on mobile phone location are inaccurate in indoor and densely populated areas (such as multiple counters in a shopping mall) and cannot effectively distinguish whether part-time workers are working or just passing by. 2. Complex and error-prone work hour statistics: Part-time workers often serve different employers at the same time or switch between different projects of the same employer on the same day. Traditional methods are difficult to automatically and accurately break down and attribute the specific projects or tasks corresponding to each work hour, still relying on manual recording and summarization, which is inefficient and prone to disputes. 3. Doubts about the authenticity of management: The relationship between part-time workers and employers is relatively loose, making it more difficult to supervise behaviors such as proxy clocking and "ghost employees." Simple sign-in methods lack strong identity binding and on-site verification, resulting in low credibility of attendance data and a high risk of employers' rights being violated. 4. Entry and usage barriers: Equipping temporary and highly mobile part-time workers with dedicated work cards is costly, while forcing them to install specific apps may be hindered by privacy concerns or mobile phone model restrictions. Therefore, given the inherent flexibility, dispersion, and multi-project parallelism of part-time work, the industry urgently needs a part-time NFC smart clocking-in method that is adaptable to multiple scenarios. Summary of the Invention

[0003] The purpose of this invention is to provide a part-time NFC smart attendance method adaptable to multiple scenarios. This invention solves problems such as scenario adaptation and accurate timekeeping statistics in part-time attendance management by integrating NFC technology with a multi-scenario adaptation mechanism, offering advantages such as low cost, high reliability, and ease of operation.

[0004] The technical solution provided by this invention is as follows: A part-time NFC smart check-in method adaptable to multiple scenarios, comprising the following steps:

[0005] S1. Configure NFC attendance credentials that are uniquely linked to the identity of part-time employees;

[0006] S2. Read the NFC check-in certificate through NFC interactive terminals deployed in different physical or logical scenarios, and trigger a check-in event corresponding to the scenario based on the scenario in which the NFC interactive terminal is deployed.

[0007] S3. Verify the NFC check-in voucher information read. After successful verification, generate and upload a check-in record containing scene information, time information and identity information.

[0008] S4. Based on preset rules, the work hour data in the attendance records is isolated and stored according to dimensions, and the work hour data stored under different dimensions is aggregated and calculated according to the query conditions.

[0009] In the above-mentioned part-time NFC smart check-in method adapted to multiple scenarios, in step S1, the NFC check-in credential is either NFC module information built into the mobile terminal or independent NFC card information.

[0010] In the aforementioned part-time NFC smart check-in method adapted to multiple scenarios, step S2 includes at least fixed physical scenarios, mobile physical scenarios, and online logical scenarios; the NFC interactive terminal includes: a passive NFC tag deployed in a fixed location, an active NFC terminal with active identification function, and an NFC card reader connected to the online working system.

[0011] In the aforementioned part-time NFC smart check-in method adapted to multiple scenarios, step S3 includes at least verification of the uniqueness of the NFC check-in credential and / or verification of the matching between the check-in behavior and the preset work project and preset work time period.

[0012] In the aforementioned part-time NFC smart check-in method adapted to multiple scenarios, step S3 includes the check-in record containing the geographical location information or network address information of the NFC interactive terminal.

[0013] In the aforementioned part-time NFC smart check-in method adapted to multiple scenarios, in step S4, the preset rule is to establish independent data partitions according to the dimensions of part-time personnel and work projects to isolate and store work hour data.

[0014] In the aforementioned part-time NFC smart check-in method adapted to multiple scenarios, in step S4, the query dimension on which the aggregation calculation is based includes at least one of the time dimension, project dimension, and location dimension.

[0015] In the aforementioned multi-scenario adaptable part-time NFC smart check-in method, step S3 employs a dynamic key authentication mechanism when the NFC interactive terminal communicates with the device carrying the NFC check-in credential.

[0016] The aforementioned part-time NFC smart attendance method adapted to multiple scenarios further includes step S5: synchronizing the aggregated and calculated working hour data and attendance status information to the employer's management terminal and / or the part-time worker's user terminal in real time, and providing an online processing flow for abnormal attendance.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] 1. This invention uses passive NFC tags, active NFC terminals, and online NFC card readers to match fixed physical, mobile physical, and online logical scenarios respectively, breaking through the limitations of traditional attendance tracking scenarios, meeting the attendance needs of various part-time jobs, and solving the pain points of fixed attendance machines being unable to move and mobile phone positioning attendance having low accuracy.

[0019] 2. This invention stores working hour data in a two-dimensional isolated manner according to part-time personnel and work projects, supports multi-dimensional aggregation calculation of time, project, and location, realizes automatic splitting and intelligent summarization of working hours, abandons the inefficient method of manual recording and summarization, avoids data confusion and statistical errors, and reduces working hour disputes between employers and employees.

[0020] 3. This invention establishes a two-layer identity verification system through NFC credential uniqueness verification and check-in behavior matching with project / time period verification. Combined with the dynamic key authentication mechanism in the communication process, it eliminates proxy check-in and data tampering from the source. The check-in record contains full-dimensional information such as location / network address, enabling data traceability and improving the credibility of attendance management.

[0021] 4. Work time data and attendance status can be synchronized in real time to the employer's management terminal and the part-time employee's user terminal, achieving two-way data transparency; a standardized online abnormal attendance handling process is provided to complete the online closed loop of appeals, review, and data correction, which greatly improves attendance management efficiency and reduces offline communication and processing costs. Attached Figure Description

[0022] Figure 1 is a flowchart illustrating the method of the present invention. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0024] Example: A part-time NFC smart check-in method adapted to multiple scenarios is applied to the check-in system of a part-time platform. The check-in system of the part-time platform consists of five core parts: NFC check-in voucher, multiple types of NFC interactive terminals, cloud data processing platform, employer management terminal, and part-time worker user terminal.

[0025] Among them, the NFC check-in certificate is the unique carrier of part-time workers' identity. It is divided into two types: one is the NFC module information built into mobile terminals such as smartphones and tablets, and the other is an independent NFC card (such as NFC patch or NFC card sticker). Both types of certificates are written with a unique identification code, which is bound to the part-time worker's name, ID number, part-time account and other information, so that there are no duplicates and the source is traceable.

[0026] NFC interactive terminals are matched with three types of terminals according to the scenario: passive NFC tags deployed in fixed locations (such as NFC touch stickers), active NFC terminals with active identification functions (such as handheld NFC card readers and portable NFC terminals), and NFC card reading devices connected to online working systems (such as computer-based USB NFC card readers). All types of terminals support the NFC near-field communication protocol, can read the identity information of the attendance certificate, and collect their own location / network address information.

[0027] The cloud-based data processing platform is the core of the attendance system, including a data receiving module, an identity verification module, an attendance record generation module, a work hour data storage module, an aggregation calculation module, and a data synchronization module. It is responsible for processing the attendance data uploaded by the terminal and completing the entire process of verification and data management.

[0028] The employer management platform supports desktop web pages and mobile apps / mini-programs, allowing employer administrators to perform operations such as project configuration, attendance rule settings, attendance data viewing, abnormal attendance handling, and exporting work hour reports.

[0029] The part-time worker user interface supports mobile app / mini-program, allowing part-time workers to view their personal clock-in records, work hour statistics, attendance status, submit abnormal attendance appeals, and receive notifications from employers.

[0030] Before officially launching the check-in process, three preliminary tasks need to be completed: binding personnel and credentials, deploying scenarios and terminals, and configuring cloud rules. These tasks lay the foundation for the subsequent check-in process. The specific steps are as follows:

[0031] NFC attendance credentials are linked to part-time worker identities: The employer creates a unique identity account for each part-time worker on the cloud data processing platform, entering basic information such as name, ID number, and project affiliation; if the part-time worker uses a mobile terminal NFC module as credentials, the NFC module is activated through the user terminal, and the cloud platform binds the terminal's unique NFC identifier to the worker's account; if the part-time worker uses an independent NFC card, the unique identifier of the worker's account is written into the card using the cloud-based card writing tool, completing the binding. After binding, all operations are based on this unique identifier for identity verification, and the binding relationship can be modified and unbound on the cloud (e.g., when the worker leaves or the card is lost).

[0032] Scenario-based deployment and information entry of NFC interactive terminals: Deploy corresponding NFC interactive terminals according to the scenario type of part-time work, and enter the terminal information into the cloud platform to realize the association and binding of terminals, scenarios, and projects.

[0033] For fixed physical scenarios (such as supermarkets, tea shops, and fixed offices): deploy passive NFC tags at designated locations in the work area, record the geographic location information (latitude and longitude, detailed address), the work project to which the tag belongs, and the valid check-in time period, and associate the tag with the project one by one.

[0034] In mobile physical scenarios (such as exhibition site visits, logistics delivery, and outdoor promotions): Equip employees with active NFC terminals, record the terminal device number, the work project, and the valid check-in area. The terminal supports actively scanning and recognizing surrounding NFC check-in credentials.

[0035] Online logic scenarios (such as online customer service, remote data annotation, and online live streaming assistance): Deploy NFC card reader devices on the online work computers of part-time staff, bind the devices to the online work system accounts, and enter the device network address information (IP address, MAC address), the work project to which they belong, and the valid check-in time period to realize check-in verification in online work scenarios.

[0036] The employer completes the configuration of various rules on the cloud platform through the management terminal, including:

[0037] Verification rules: Set unique verification rules for NFC attendance vouchers, matching rules between attendance behavior and work projects (e.g., only allow attendance within the project bound to the voucher), and matching rules between attendance behavior and work time period (e.g., only allow attendance within the preset work time period).

[0038] Storage rules: Establish independent data partitions based on part-time employee ID and work project ID, assign a unique storage identifier to each partition, and specify the storage fields for work hour data (including clock-in time, scene information, terminal information, identity information, etc.).

[0039] Aggregation calculation rules: Configure the aggregation calculation logic for time dimension (day / week / month / custom time period), project dimension (single project / multiple projects), and location dimension (single location / multiple locations), and clarify the calculation method for work hours statistics (e.g., clock-in end time - clock-in start time, deducting non-working time periods).

[0040] Synchronization rules: Set the real-time requirements for data synchronization (second-level synchronization), the content to be synchronized (clock-in records, work hour data, attendance status), and the synchronization targets (employer management end, part-time employee user end).

[0041] Deploy dynamic key generation and verification programs in cloud data processing platforms, NFC interactive terminals, and NFC attendance credential carriers, preset key update cycles (such as generating a temporary key once per attendance session), and adopt a two-way dynamic key authentication mode to ensure the security of the communication process between the terminal and the credential, and prevent data from being tampered with or stolen.

[0042] After the preliminary work is completed, the specific steps of the part-time NFC smart check-in method of the present invention are as follows:

[0043] S1. Configure NFC attendance credentials that are uniquely associated with the part-time workers' identities. This step is a preliminary operation and has been completed in the core preliminary configuration. This ensures that each part-time worker has a unique NFC attendance credential, and the credential is bound to the individual's identity and the work project they are assigned to. The credential information cannot be modified at will, and only the employer's administrator can make adjustments within their authorized scope on the cloud platform.

[0044] S2. Read the NFC check-in certificate through NFC interactive terminals deployed in different physical or logical scenarios, and trigger a check-in event corresponding to the scenario based on the scenario in which the NFC interactive terminal is deployed.

[0045] In this step, part-time workers arrive at the corresponding work scene and complete near-field communication with the matched NFC interactive terminal using an NFC attendance credential. After the terminal reads the credential information, it automatically triggers the attendance event corresponding to the scene (attendance at work, attendance at the end of get off work, shift change, etc.). The attendance operation methods and technical requirements for different scenes are as follows: the effective NFC communication distance is controlled within 0-5cm to ensure the on-site nature of the attendance behavior:

[0046] 1. Fixed physical scene check-in: During the preset work period, part-time staff will attach their bound NFC check-in voucher (mobile terminal / NFC card) to a passive NFC tag deployed at a fixed location. The tag will read the unique identifier of the voucher through near field communication, triggering a check-in event on site and automatically collecting the check-in time (accurate to the second).

[0047] 2. Mobile physical scene check-in: When part-time employees are in a preset work area, when an active NFC terminal scans the signal of their NFC check-in voucher, the terminal actively reads the unique identifier of the voucher, triggering a mobile check-in event. The terminal automatically collects the check-in time and its own current geographical location information.

[0048] 3. Online Logical Scenario Check-in: During the preset work period, part-time employees log in to the online work system and place their bound NFC check-in voucher close to the NFC card reader on the computer. The device reads the unique identifier of the voucher, triggering an online check-in event. The device automatically collects the check-in time and its own network address information.

[0049] If the check-in behavior exceeds the preset scenario / project / time period, the terminal will directly refuse to read the voucher information, will not trigger the check-in event, and will push prompts such as "check-in scenario does not match" and "check-in time period is invalid" to the part-time user's terminal.

[0050] S3. Verify the NFC check-in voucher information read. After successful verification, generate and upload a check-in record containing scene information, time information and identity information.

[0051] In this step, the NFC interactive terminal uploads the read check-in credential identity information, the collected check-in time / location / network information, and the triggered check-in event type to the cloud data processing platform. The platform completes multi-dimensional verification through the identity verification module. The verification is performed automatically in real time. If the verification fails, the check-in request is rejected. If the verification passes, a check-in record is generated and permanently stored. The specific details are as follows:

[0052] 1. Verification Content: Includes at least two core verifications, with the option for employers to add additional verification rules as needed.

[0053] Uniqueness verification: Verify whether the uploaded NFC check-in credential identifier is a unique identifier bound to the cloud platform, and whether there are duplicate identifiers, unbound identifiers, or deregistered identifiers;

[0054] Matching verification: Verify whether the clock-in behavior matches the preset work project and preset work time period, that is, whether the part-time personnel bound to the voucher belong to the work project corresponding to the terminal, and whether the clock-in time is within the preset valid work time period.

[0055] 2. Communication Security: When the terminal transmits data with the cloud platform, and when the NFC interactive terminal communicates with the device carrying the NFC card-swiping certificate, a dynamic key authentication mechanism is used: a unique temporary dynamic key is generated for each communication session. Data transmission is carried out only after both parties complete the key verification. The key becomes invalid immediately after the session ends, preventing identity forgery and data tampering caused by static key leakage.

[0056] 3. Check-in record generation and upload: After verification, the check-in record generation module of the cloud platform automatically generates standardized check-in records. The records include required fields and optional fields. All field information is in a traceable format. After generation, the records are immediately uploaded to the cloud database for permanent storage, and a unique record number is generated at the same time.

[0057] Required fields: Unique identifier for NFC attendance credential, part-time employee identity information, attendance event type, attendance time (timestamp), scenario type, NFC interactive terminal device number, and verification pass status;

[0058] Optional fields: Geographic location information of the NFC interactive terminal (latitude and longitude / detailed address), network address information (IP / MAC), and the ID of the work project to which it belongs.

[0059] S4. Based on preset rules, the work hour data in the attendance records is isolated and stored according to dimensions, and the work hour data stored under different dimensions is aggregated and calculated according to the query conditions.

[0060] In this step, the cloud platform isolates and stores the work hour data in the attendance records according to preset rules, and performs multi-dimensional aggregation calculations based on the query conditions of the employer / part-time worker. This enables accurate splitting and flexible statistics of work hour data, solving the pain point of work hour statistics for part-time workers working on multiple projects simultaneously. The specific operation is as follows:

[0061] 1. Time data extraction: Extract the basic data for calculating valid working hours from the clock-in records. If it is a continuous clock-in from "start work" to "end get off work", calculate the valid working hours for a single clock-in based on the clock-out timestamp minus the clock-in timestamp. If it is a clock-in for a job change, split the working hours data of different projects according to the job change node and remove invalid clock-in data (such as duplicate clock-in or incomplete clock-out).

[0062] 2. Dual-dimensional isolated storage: Based on the preset rule of "establishing independent data partitions according to the dimensions of part-time personnel and work projects", the cloud-based time data storage module will extract the valid time data and store it into the corresponding independent data partition according to the dual-dimensional identifier of part-time personnel ID and work project ID. The time data in different partitions are isolated from each other and do not mix with each other, avoiding the error of overlapping time data of multiple projects; for example, the time of part-time personnel A for project X is stored in the "ID-A-Project X" partition, and the time of project Y is stored in the "ID-A-Project Y" partition. The data in the two partitions are managed independently.

[0063] 3. Multi-dimensional Aggregation Calculation: The cloud-based aggregation calculation module supports automated aggregation calculation of work hour data from different data partitions based on query conditions. The query dimensions are selected by the employer / part-time worker and must include at least time, project, and location dimensions. Single-dimensional queries and multi-dimensional combination queries are supported, and calculation results are generated in real time.

[0064] Time dimension: Aggregate by day, week, month, quarter, or custom time period to calculate total working hours, average daily working hours, etc. within the specified time period;

[0065] Project Dimension: Aggregate by single project, multiple projects, or all projects to calculate the total working hours of a specified project and the percentage of working hours for each project;

[0066] Location dimension: Aggregate by single location or multiple locations to calculate the total working hours of a specified work location and the distribution of working hours in different locations.

[0067] During the aggregation calculation process, the platform will retain calculation logs, recording query conditions, calculation scope, and calculation results to ensure that the calculation process is traceable and verifiable.

[0068] S5: Real-time synchronization of aggregated work hour data and attendance status information to the employer's management terminal and / or part-time employee's user terminal, and provides an online processing flow for abnormal attendance.

[0069] In this step, the cloud platform's data synchronization module will synchronize the aggregated and calculated work hour data, original clock-in records, and attendance status information (normal clock-in, missed clock-in, late arrival, early departure) to the employer's management terminal and the part-time employee's user terminal in real time within seconds according to preset synchronization rules. At the same time, the system provides a standardized online process for handling abnormal attendance, realizing a closed loop in attendance management. The specific operation is as follows:

[0070] 1. Data synchronization:

[0071] Synchronize with the employer's management end: full attendance records, multi-dimensional work hour aggregation reports, team / individual attendance status, abnormal attendance list, and support administrators to filter and export data by conditions (Excel / PDF format).

[0072] Synchronize with part-time users: personal clock-in records, personal work hour statistics, and personal attendance status, and support part-time users to view details and file appeals.

[0073] 2. Online processing of abnormal attendance:

[0074] The system automatically identifies abnormal attendance types (missed clock-in, lateness, early departure, clocking in from a different location, abnormal clocking-in time, etc.) and synchronizes the abnormal list on both ends. The processing flow is online initiation - online review - online feedback - data update, and the entire process requires no offline paper materials. Specific steps:

[0075] Appeal Initiation: After viewing abnormal attendance information on the user terminal, part-time employees can submit an abnormality appeal within a preset time limit (such as 24 hours) and upload supporting materials for the appeal (such as proof of employment or leave certificate).

[0076] Review and processing: The employer's administrator receives the appeal request on the management terminal, reviews the supporting documents, makes a "review approved" or "rejected" decision, and fills in the review comments;

[0077] Results feedback: The review results are synchronized to the part-time staff's user terminal in real time, and the part-time staff can view the review comments;

[0078] Data Update: If the review is approved, the cloud platform will automatically correct the corresponding attendance status and work hour data, and update all relevant storage partitions and statistical reports; if the review is rejected, the original attendance status and data will remain unchanged.

[0079] The following section, with reference to Figure 1, provides further step-by-step instructions for the NFC check-in method for part-time staff. The steps are as follows:

[0080] 1. Check-in Trigger and NFC Interaction Phase: When part-time workers arrive at the check-in point at the project site, they trigger the NFC check-in terminal via a physical button or sensor. The terminal screen displays the prompt: "Please bring it close to the NFC carrier," guiding the part-time worker to bring their NFC card or NFC-enabled mobile device close to the terminal's sensing area, ensuring a distance of ≤10cm. The terminal reads the unique identification information of the NFC carrier through its built-in NFC module and monitors the current network connection status in real time, determining whether it is online or offline, and then proceeds to the corresponding processing branch.

[0081] 2. When the terminal detects that the network connection is normal, perform the following steps:

[0082] 2.1 Authentication Request: The terminal uploads the NFC tag it reads to the service layer via a network protocol (such as HTTP / HTTPS) to initiate an authentication request.

[0083] 2.2 Service Layer Triple Validation: After receiving a request, the service layer executes the following validation logic in sequence:

[0084] Identifier validity verification: Query the database to determine whether the NFC identifier has been registered and entered into the system.

[0085] Project attribution verification: Determine whether the part-time worker corresponding to this identifier belongs to a valid project of the current check-in point.

[0086] Time validity check: Obtain the current system time and determine whether it is within the preset valid check-in period of this project.

[0087] 2.3 Verification Result Processing:

[0088] Verification successful: The service layer generates a complete attendance record, which includes, but is not limited to, the following fields: attendance timestamp, terminal physical location information, part-time worker identity information, and project ID. After the record is generated, the service layer returns a "attendance successful" instruction to the terminal. Upon receiving the instruction, the terminal displays "attendance successful" and the record ID on the screen, and synchronizes the attendance success notification to the part-time worker's bound app via a push service (such as MQTT).

[0089] Verification Failure: The service layer returns the specific reason for the verification failure to the terminal, such as "Not a current project part-time job" or "Check-in time has expired." Upon receiving this information, the terminal displays the reason for the failure on the screen. After the part-time worker confirms the information, the terminal automatically returns to standby mode, waiting for the next check-in trigger.

[0090] 3. When the terminal detects no network connection or a network abnormality, perform the following steps:

[0091] 3.1 Local Cache Verification: The terminal verifies the NFC identifier read from the locally stored cache data: verifying whether the identifier belongs to the list of valid part-time personnel for the current project that has been pre-downloaded locally, and verifying whether the local time of the current terminal is within the preset valid check-in period of the project.

[0092] 3.2 Verification Result Processing:

[0093] Verification successful: The terminal caches a check-in record in its local database. This record includes an offline timestamp, NFC identifier, and terminal ID. Simultaneously, the terminal screen displays "Offline check-in successful." Once the terminal's network is restored, the system will automatically trigger a data synchronization task, batch uploading all locally cached offline check-in records to the service layer. The service layer will then update the records in the system database, completing the data loop.

[0094] Verification failed: The terminal screen displays "Offline check-in failed" and automatically returns to standby mode, waiting for the next check-in trigger.

[0095] Through the above implementation methods, the method of the present invention achieves the following technical effects: It can still complete the check-in operation in scenarios with poor or no network, ensuring business continuity. Offline check-in records are automatically synchronized after reconnecting to the network, ensuring the integrity and accuracy of service layer data. Through a dual online and offline verification mechanism, it effectively prevents violations such as proxy check-ins and check-ins by non-project personnel.

[0096] In summary, this implementation plan clarifies the full-process technical details and operational requirements of a part-time NFC smart attendance method adapted to multiple scenarios. Each step is interconnected and each module works collaboratively, solving the problems of poor scenario adaptability, complex work hour statistics, and unreliable identity verification in traditional attendance methods for part-time situations. Those skilled in the art can complete the development, deployment, operation, and maintenance of the system based on this plan, realizing intelligent, efficient, and highly reliable part-time attendance management.

Claims

1. A part-time NFC smart check-in method adaptable to multiple scenarios, characterized in that, Includes the following steps: S1. Configure an NFC attendance credential uniquely associated with the part-time employee's identity; S2. Read the NFC attendance credential through NFC interactive terminals deployed in different physical or logical scenarios, and trigger an attendance event corresponding to the scenario based on the scenario in which the NFC interactive terminal is deployed; S3. Verify the read NFC attendance credential information, and after successful verification, generate and upload an attendance record containing scenario information, time information, and identity information. S4. Based on preset rules, the work hour data in the attendance records is isolated and stored according to dimensions, and the work hour data stored under different dimensions is aggregated and calculated according to the query conditions.

2. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S1, the NFC card verification certificate is either NFC module information built into the mobile terminal or independent NFC card information.

3. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S2, the scenario includes at least a fixed physical scenario, a mobile physical scenario, and an online logical scenario; the NFC interactive terminal includes: a passive NFC tag deployed in a fixed location, an active NFC terminal with active identification function, and an NFC card reader connected to the online working system.

4. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S3, the verification includes at least the uniqueness verification of the NFC check-in credential and / or the matching verification of the check-in behavior with the preset work items and preset work time periods.

5. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S3, the check-in record also includes the geographical location information or network address information of the NFC interactive terminal.

6. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S4, the preset rule is to establish independent data partitions based on the dimensions of part-time personnel and work projects to isolate and store work hour data.

7. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 6, characterized in that, In step S4, the query dimensions on which the aggregation calculation is based include at least one of the time dimension, project dimension, and location dimension.

8. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, In step S3, a dynamic key authentication mechanism is used when the NFC interactive terminal communicates with the device carrying the NFC card-taking credential.

9. The part-time NFC smart check-in method adaptable to multiple scenarios according to claim 1, characterized in that, The method further includes step S5: synchronizing the aggregated working hour data and attendance status information to the employer's management terminal and / or part-time employee's user terminal in real time, and providing an online processing flow for abnormal attendance.

Images