Electronic timing patrol system based on NFC

Abstract

The invention belongs to the field of electronic patrol, and particularly relates to an electronic timing patrol system based on NFC. The system is composed of an NFC tag array, an NFC handheld terminal, a cloud server and a user terminal, and the NFC tag array is preset at a key position on a patrol route and is used for recording patrol point information; the NFC hand-held terminal is carried by patrol personnel to generate patrol data; the cloud server is responsible for storing and processing the patrol data and issuing an instruction; the user terminal is used for a manager to remotely monitor the patrol condition, a patrol route, time requirements and task contents are preset through the cloud server before the patrol is started and are synchronized to the NFC handheld terminal, and in the patrol process, the patrol personnel use the NFC handheld terminal to get close to the NFC label, automatically complete sign-in and upload patrol data to the cloud server; and the cloud server performs deep mining on the patrol data by using a big data analysis technology, and analyzes the behavior pattern of the patrol personnel, patrol efficiency evaluation and potential safety risk early warning.

Description

Technical Field

[0001] The invention belongs to the field of electronic patrol, and in particular relates to an electronic timed patrol system based on NFC. Background Art

[0002] In the current security management system, the patrol system is a key link in maintaining security and is widely used in various scenarios such as property communities, industrial plants and cultural museums. Traditional patrol methods, whether relying on manual records or combining electronic patrol sticks with RFID tags, have improved work efficiency but exposed obvious shortcomings. Although the wireless recognition function of RFID technology is convenient, its communication range is limited and it is easily affected by environmental factors such as electromagnetic interference and obstacles, resulting in reduced recognition accuracy. At the same time, due to the lack of real-time data transmission capabilities in traditional patrol systems, managers find it difficult to grasp the real-time location and task progress of patrol personnel in a timely manner, and supervision efficiency is limited. In addition, the data recording and integration process is complex and lengthy, which is not only time-consuming and labor-intensive, but also prone to errors due to human factors, which brings challenges to the subsequent in-depth analysis and strategy adjustment of security data, and it is difficult to meet the modern security management requirements for efficiency, accuracy and real-time. Therefore, the present invention provides an NFC-based electronic timed patrol system, which realizes the automation, real-time and efficient management of the patrol process. Summary of the invention

[0003] The present invention provides an NFC-based electronic timed patrol system, which is used to solve the technical problems that the traditional patrol system has low recognition accuracy and lacks real-time data transmission capability, making it difficult for managers to timely grasp the real-time location and task progress of patrol personnel, and thus limiting the supervision efficiency.

[0004] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present invention is as follows: an NFC-based electronic timed patrol system, which consists of four parts: an NFC tag array, an NFC handheld terminal, a cloud server and a user terminal. The NFC tag array is pre-placed at a key position on the patrol route to record patrol point information; the NFC handheld terminal is carried by the patrol personnel, has NFC reading and writing functions and GPS positioning capabilities, and will generate patrol data; the cloud server is responsible for the storage, processing and instruction issuance of the patrol data; the user terminal is used for management personnel to remotely monitor the patrol situation. Before the patrol begins, the patrol route, time requirements and task content are preset through the cloud server and synchronized to the NFC handheld terminal. During the patrol, the patrol personnel use the NFC handheld terminal to approach the NFC tag, automatically complete the sign-in and upload the patrol data to the cloud server. The cloud server uses big data analysis technology to deeply mine the patrol data, analyze the behavior patterns of the patrol personnel, patrol efficiency evaluation and potential safety risk warning.

[0005] Furthermore, the NFC tag array is used to record the information of the patrol points, including the location and number, and also has a built-in unique identification code to ensure the security and uniqueness of the patrol data.

[0006] Furthermore, the NFC handheld terminal integrates an NFC reading and writing module, a GPS positioning module, a wireless communication module and an intelligent processing chip, which not only supports fast reading and writing of NFC tag arrays, realizes the automation of patrol check-in, but also uploads the location information of patrol personnel to the cloud server in real time.

[0007] Furthermore, the user terminal supports receiving abnormal reminders and alarm information issued by the patrol system, ensuring that management personnel can promptly discover and handle problems that arise during the patrol process.

[0008] Furthermore, the patrol data includes sign-in data, preset patrol routes, abnormal data and statistical data. The sign-in data includes timestamp, location information and NFC tag array ID. The patrol route data includes preset patrol routes and actual patrol routes. The abnormal data includes late records and missed sign-in records. The statistical data includes patrol completion events, sign-in rate and moving speed.

[0009] Furthermore, the big data analysis technology includes patrol data preprocessing and behavior pattern analysis, wherein the data preprocessing includes data cleaning to remove noise, data conversion to convert timestamps into date and time format, and data standardization to enable comparison of data of different dimensions.

[0010] Furthermore, the patrol data standardization adopts improved Z-score standardization, and the patrol data normalization adopts minimum-maximum normalization.

[0011] Furthermore, the patrol efficiency evaluation evaluates the patrol efficiency by calculating the time required for the patrol personnel to complete the preset tasks, the completeness of the sign-in records, and the frequency of abnormal situations.

[0012] Compared with the prior art, the present invention has the following beneficial effects:

[0013] (1) The present invention realizes real-time monitoring of the patrol process through NFC instant check-in and GPS positioning, ensuring the effective execution of the patrol task.

[0014] (2) The present invention uses NFC handheld terminals to reduce manual recording and aggregation steps, improve work efficiency, reduce human errors, and use big data analysis technology to provide scientific decision-making support for security management. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a structural diagram of the electronic timed patrol system of the present invention. DETAILED DESCRIPTION

[0016] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0017] By the attached Figure 1 As shown, an NFC-based electronic timed patrol system consists of four parts: an NFC tag array, an NFC handheld terminal, a cloud server and a user terminal. The NFC tag array is pre-placed at a key position on the patrol route to record patrol point information; the NFC handheld terminal is carried by the patrol personnel, has NFC reading and writing functions and GPS positioning capabilities, and will generate patrol data; the cloud server is responsible for the storage, processing and instruction issuance of the patrol data; the user terminal is used for management personnel to remotely monitor the patrol situation. Before the patrol begins, the patrol route, time requirements and task content are preset through the cloud server and synchronized to the NFC handheld terminal. During the patrol, the patrol personnel use the NFC handheld terminal to approach the NFC tag, automatically complete the sign-in and upload the patrol data to the cloud server. The cloud server uses big data analysis technology to deeply mine the patrol data, analyze the behavior patterns of the patrol personnel, patrol efficiency evaluation and potential safety risk warning.

[0018] NFC tag array: As the key information carrier on the patrol route, NFC tags are placed at every key location that needs to be patrolled. These tags are used to record basic information such as the location and number of the patrol point, and also have a built-in unique identification code to ensure the security and uniqueness of the patrol data. Through the short-range wireless communication capability of NFC technology, patrol personnel can easily interact with these tags to complete operations such as sign-in.

[0019] NFC handheld terminal: As a portable tool for patrol personnel, the NFC handheld terminal integrates NFC reading and writing modules, GPS positioning modules, wireless communication modules and intelligent processing chip components. The terminal not only supports fast reading and writing of NFC tags to realize the automation of patrol check-in, but also has accurate positioning capabilities and can upload the location information of patrol personnel to the cloud server in real time.

[0020] Cloud server: As the core processing center of the entire system, the cloud server is responsible for patrol data storage, processing and command issuance. Through high-performance server clusters and advanced database management systems, the cloud server can receive and process patrol data from NFC handheld terminals in real time, including sign-in information and location information. At the same time, the server also has powerful data analysis capabilities and can use big data analysis technology to conduct in-depth mining of patrol data to provide a scientific basis for security management. In addition, the cloud server also provides a wealth of interfaces and API support to facilitate seamless docking and data sharing with other security systems or management platforms.

[0021] Patrol data includes check-in data, preset patrol routes, abnormal data, and statistical data.

[0022] (1) Attendance data:

[0023] Timestamp: Every time a patrol officer signs in by using an NFC handheld terminal close to an NFC tag, the system records an accurate timestamp. This timestamp is used to determine the time when the patrol officer arrived at the patrol point.

[0024] Location information: If the NFC handheld terminal has GPS positioning capability, the check-in data will also include the geographical location information (latitude and longitude) at the time of check-in, which helps to further verify whether the patrol personnel have actually arrived at the designated patrol point.

[0025] NFC tag ID: Each NFC tag has a unique identification code (ID). The check-in data will record the ID of the checked-in NFC tag so that the system knows at which patrol point the patrol personnel checked in.

[0026] (2) Patrol route data:

[0027] Preset patrol route: Before the patrol begins, the manager will preset the patrol route through the cloud server, including the order of patrol points, the time to arrive at each patrol point, etc. These data are used for subsequent comparison with the actual patrol data.

[0028] Actual patrol routes: Based on the check-in data, the system can generate actual patrol routes, including the order and time of patrol points that patrol personnel actually arrive at.

[0029] (3) Abnormal data:

[0030] Late record: If the patrol personnel arrive at a patrol point later than the preset time requirement, the system will record it as late.

[0031] Missed sign-in record: If the patrol personnel fails to sign in at a patrol point where they should sign in, the system will record it as a missed sign-in.

[0032] (4) Statistical data:

[0033] Patrol completion time: the total time from the start to the end of the patrol.

[0034] Attendance rate: The ratio of the actual number of check-ins to the number of expected check-ins, used to evaluate the attendance of patrol personnel.

[0035] Movement speed: Based on the check-in time and location information, the movement speed of the patrol personnel between two patrol points can be calculated to evaluate the patrol efficiency.

[0036] Big data analysis technology includes patrol data preprocessing and behavior pattern analysis.

[0037] (1) Data preprocessing:

[0038] The collected patrol data is preprocessed, including data cleaning (removing noise, outliers, etc.), data conversion (such as converting timestamps to date and time format) and data standardization (enabling data of different dimensions to be compared).

[0039] 1) Data cleaning: patrol data uses sign-in data S i , patrol route data P i , abnormal data D i , Statistical data i ,

[0040] x i =ω S ·S i +ω P ·P i +ω D ·D i +ω T ·T i , i∈{1,2,3...,N},), where ω xx is the normalized weight value. Calculate its average value The difference χ i =x i -u, and with standard deviation If the difference χ i If the value of -s exceeds the threshold m=3s (3 times the standard deviation), the data point is considered an outlier and is removed or replaced.

[0041] 2) Data standardization: Standardize data from different sources and units so that they can be compared and analyzed on the same scale, using improved Z-score standardization:

[0042]

[0043] Among them, x is the patrol data after data cleaning, μ is the mean of the data, and σ is the standard deviation of the data. After standardization, the mean of the data is 0 and the standard deviation is 1.

[0044] 3) Data normalization: Through the normalization algorithm, the data is converted into a dimensionless value between 0 and 1, which is convenient for subsequent algorithm processing and analysis.

[0045] Minimum-maximum normalization formula:

[0046] Among them, x is the patrol data after data cleaning and standardization, x min and x max are the minimum and maximum values ​​in the data respectively. After normalization, the value range of the data is between 0 and 1.

[0047] 4) Missing value filling: Use linear interpolation to fill in missing values ​​x m , whose two non-missing values ​​are x a and x b , and a<m<b, then

[0048] (2) Behavioral pattern analysis:

[0049] The specific process is as follows:

[0050] 1) Time series data preparation: patrol data x i , convert it into a time series form {X i (t),x i (t)∈X i (t)}, where X i (t) represents the patrol data of the tth time unit;

[0051] 2) Stationarity test: Use the ADF test method to test the stationarity of the time series;

[0052] 3) ARMA model analysis: ARMA (p, q), where p is the order of the autoregressive term and q is the order of the moving average term; the mathematical expression of the ARMA (p, q) model is:

[0053] X i (t) = λ1X i (t-1)+λ2X i (t-2)+...+λ p X i (tp)+ξ i (t)+θ1ξ i (t-1)+θ2ξ i (t-2)+…+θ q ξ i(tq) where λ1,…λ p are the autoregressive coefficients, θ1,…θ p is the moving average coefficient, ξ i (t) is a white noise sequence;

[0054] 4) Model identification and parameter estimation

[0055] Model identification: By observing the graphical characteristics of the time series autocorrelation function ACF and partial autocorrelation function PACF, the order p and q of the model can be preliminarily determined.

[0056] For the time series Xt, its autocorrelation function at lag k is defined as: Autocorrelation function (ACF) calculation formula:

[0057] Among them, X i (t) = X t μ is the mean of the time series, and n is the length of the time series. Note that the formula assumes that the time series is stationary and μ is known. In practice, μ is estimated by the sample mean.

[0058] Parameter estimation: Use the least squares method to estimate the parameters λ1,…λ p ,θ1,…θ p .

[0059] Model testing: Verify the applicability of the model through residual analysis;

[0060] 5) Prediction

[0061] Given historical data X1, X2, …, Xn, predict future check-in times Xn+1, Xn+2, ….

[0062] 6) Apply to patrol data

[0063] Define Xt as the patrol data of the tth day or hour. By analyzing the time series, we can find out the working habits of patrol personnel and predict future behavior trends based on the dynamic changes of patrol personnel's check-in time. This helps managers better understand the working status and efficiency level of patrol personnel and provide a scientific basis for optimizing patrol routes and task arrangements.

[0064] User terminal: By accessing the web interface or mobile application provided by the cloud server, managers can view key information such as the patrol personnel's check-in status, location trajectory, and task execution status in real time. At the same time, the user terminal also supports receiving abnormal reminders and alarm information issued by the system, ensuring that managers can promptly discover and handle problems that arise during the patrol process.

[0065] Patrol efficiency evaluation: The system also supports quantitative evaluation of patrol efficiency. By calculating the time required for patrol personnel to complete preset tasks, the completeness of sign-in records, and the frequency of abnormal situations, the efficiency of patrol can be objectively evaluated. Patrol completion time: directly calculate the total time from the start to the end of the patrol; Sign-in rate: the ratio of the number of sign-ins to the number of sign-ins that should be signed, that is, sign-in rate = actual number of sign-ins / should be signed × 100%

[0066] Potential safety risk warning: When a patrol point frequently misses a sign or is late, it may mean that there are safety hazards in the area or the patrol staff has a problem with their work attitude. At this time, the system will send a warning message to the management staff through the user terminal so that timely measures can be taken to eliminate safety hazards or improve patrol work.

[0067] Patrol report generation: By selecting a specific time period and patrol route, the system can automatically generate a detailed patrol report including check-in records, location tracks, task completion status, abnormal reminders and other information.

[0068] In addition, the electronic timed patrol system of the present invention adopts security measures, including encrypted communication protocol, unique identification code verification, authority management and access control.

[0069] The encrypted communication protocol is used to encrypt the transmitted data. Even if the data is intercepted during transmission, it cannot be decrypted and viewed by unauthorized personnel, thus ensuring the security and privacy of the data.

[0070] To prevent NFC tags from being forged or tampered with, the system assigns a unique identification code to each NFC tag and performs strict verification during the reading and writing process. The check-in operation can only be completed when the identification code read by the handheld terminal matches the identification code stored in the cloud database, thus ensuring the authenticity and accuracy of the check-in information.

[0071] By assigning different permissions and roles to different users, the system can achieve refined management and control of system resources, thereby reducing security risks and improving the overall security of the system.

[0072] The electronic patrol system of the present invention realizes the automation, real-time and efficient management of the patrol process by integrating NFC technology, Internet of Things technology and intelligent algorithms.

[0073] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An electronic timed patrol system based on NFC, characterized in that: It consists of four parts: NFC tag array, NFC handheld terminal, cloud server and user terminal. The NFC tag array is pre-placed at key positions on the patrol route to record patrol point information; the NFC handheld terminal is carried by patrol personnel, has NFC reading and writing functions and GPS positioning capabilities, and will generate patrol data; the cloud server is responsible for the storage, processing and instruction issuance of the patrol data; the user terminal is used for management personnel to remotely monitor the patrol situation. Before the patrol begins, the patrol route, time requirements and task content are preset through the cloud server and synchronized to the NFC handheld terminal. During the patrol, the patrol personnel use the NFC handheld terminal to approach the NFC tag, automatically complete the sign-in and upload the patrol data to the cloud server. The cloud server uses big data analysis technology to conduct in-depth mining of patrol data, analyze the behavior patterns of patrol personnel, patrol efficiency evaluation and potential safety risk warning.

2. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The NFC tag array is used to record the information of the patrol points, including the location and number, and also has a built-in unique identification code to ensure the security and uniqueness of the patrol data.

3. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The NFC handheld terminal integrates an NFC reading and writing module, a GPS positioning module, a wireless communication module and an intelligent processing chip, which not only supports the fast reading and writing of the NFC tag array, realizes the automation of patrol check-in, but also uploads the location information of patrol personnel to the cloud server in real time.

4. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The user terminal supports receiving abnormal reminders and alarm information issued by the patrol system, ensuring that managers can promptly discover and handle problems that arise during the patrol process.

5. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The patrol data includes sign-in data, preset patrol routes, abnormal data and statistical data. The sign-in data includes timestamp, location information and NFC tag array ID. The patrol route data includes preset patrol routes and actual patrol routes. The abnormal data includes late records and missed sign-in records. The statistical data includes patrol completion events, sign-in rate and moving speed.

6. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The big data analysis technology includes patrol data preprocessing and behavior pattern analysis. The data preprocessing includes data cleaning to remove noise, data conversion to convert timestamps into date and time format, and data standardization to enable comparison of data of different dimensions.

7. The NFC-based electronic timed patrol system according to claim 6, characterized in that: The patrol data standardization adopts improved Z-score standardization, and the patrol data normalization adopts minimum-maximum normalization.

8. The NFC-based electronic timed patrol system according to claim 1, characterized in that: The patrol efficiency evaluation evaluates the patrol efficiency by calculating the time required for the patrol personnel to complete the preset tasks, the completeness of the sign-in records, and the frequency of abnormal situations.

Images