A smart security patrol management system and method

Abstract

The present invention discloses a smart security patrol management system and method, which relates to the field of smart security. The system includes: a data acquisition module, which is used to obtain real-time data and information in the security monitoring area; an automatic patrol module, which is used to plan the patrol route, perform patrol tasks in the security monitoring area, and record the patrol results. The present invention can realize the recognition and analysis of the received data by setting an intelligent analysis module, judge whether there are abnormal problems in the security area, determine the specific location, type and danger level of the abnormal problem, and reasonably select manual patrol, patrol robot patrol or manual and robot collaborative patrol mode to deal with the abnormal problem in a targeted manner according to the final determination result, realize the function of coordinated cooperation between manual patrol and robot patrol, and can quickly respond and patrol the location where the abnormal problem occurs.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent security patrol inspection management system, and more specifically, to an intelligent security patrol inspection management system and method. Background Art

[0002] Smart security refers to the use of modern information technology, such as artificial intelligence, the Internet of Things, big data, etc., to achieve intelligent, efficient and refined security. Smart security involves multiple fields, including video surveillance, access control systems, alarm systems, etc., which can provide people with a safer and more convenient living environment.

[0003] At present, the smart security inspection and management system used in buildings generally only uses robots to perform daily inspections on planned routes. For areas that robots cannot reach, manual inspections are used. However, there is no coordination and cooperation between manual inspections and robot inspections, and they lack specificity, which not only easily leads to abnormal problems but also wastes human and material resources. Summary of the invention

[0004] In view of the deficiencies in the prior art, the object of the present invention is to provide a smart security patrol management system and method.

[0005] To achieve the above object, the present invention provides the following technical solutions, including:

[0006] Data acquisition module, which is used to obtain real-time data and information within the security monitoring area;

[0007] Automatic inspection module, which is used to plan inspection routes, perform inspection tasks in the security monitoring area, and record inspection results;

[0008] A security management platform, which is used to receive the collected real-time data and information, and analyze and process it to determine whether there is any abnormality in the security monitoring area, wherein the security management platform includes an intelligent analysis module, an alarm module, a security and privacy protection module, and a data storage module;

[0009] The intelligent analysis module is used to identify and analyze the received data, determine whether there are abnormal problems in the security area, determine the specific location of the abnormal problem, determine the type of the abnormal problem is an abnormal environmental state or abnormal human activity, determine the danger level of the abnormal environmental state problem, and reasonably select manual inspection, inspection robot inspection, or manual and robot collaborative inspection methods to deal with the abnormal problem in a targeted manner according to the final determined specific location, abnormal problem type and danger level;

[0010] The alarm module is used to automatically trigger an alarm and notify relevant personnel based on the intelligent analysis results;

[0011] The security and privacy protection module is used to encrypt and protect data transmission and storage, and to control and manage access rights;

[0012] The data storage module is used to store the received monitoring data and analysis results.

[0013] Preferably, the data and information collected by the acquisition module include environmental parameter data and video image data. When the intelligent analysis module analyzes the environmental parameter data, the acquired environmental parameters are compared with preset standard environmental parameters. If the acquired environmental parameters exceed the threshold of the preset standard environmental parameters, the environmental parameters are considered to be abnormal.

[0014] Preferably, when the intelligent analysis module analyzes the video image data, it compares the acquired video image data with a pre-built normal behavior model or normal environmental state model. If it is found that the data exceeds the range of normal behavior or normal environmental state or does not conform to the pattern of normal behavior, it is judged to be abnormal.

[0015] Preferably, when calculating the danger level of the abnormal environment, the formula , calculate the danger level Gk, compare Gk with the preset danger level judgment range G0, if the danger level Gk is less than the minimum value of the danger level judgment range G0, then the current environmental status level is considered to be low risk, and the intelligent analysis module sends an inspection instruction to the inspection robot. If the danger level Gk is within the danger level judgment range G0, then the current environmental status level is considered to be medium risk, and the intelligent analysis module sends an inspection instruction to the inspection personnel closest to the abnormal problem location. If the danger level Gk is greater than the maximum value of the danger level judgment range G0, then the current environmental status level is considered to be high risk, and the intelligent analysis module sends inspection instructions to the inspection robot and the inspection personnel in turn, and sends an alarm instruction to the alarm and notification module. The inspection robot first conducts an on-site survey, and then sends the survey results to the inspection personnel so that they can make corresponding strategies in time.

[0016] Preferably, when it is determined to be an abnormal problem caused by human activity, the formula , calculate the danger level Hk, compare Hk with the preset danger level judgment range H0, if the danger level Hk is less than the minimum value of the danger level judgment range H0, it is considered that the current environmental status level is low risk, and the intelligent analysis module sends an inspection instruction to the inspector who is closest to the abnormal problem location; if the danger level Hk is within the danger level judgment range H0, it is considered that the current environmental status level is medium risk, and the intelligent analysis module sends inspection instructions to 2-3 inspectors who are closest to the abnormal problem location; if the danger level Hk is greater than the maximum value of the danger level judgment range H0, it is considered that the current environmental status level is high risk, and the intelligent analysis module sends inspection instructions to more than 3 inspectors who are closest to the abnormal problem location.

[0017] Preferably, the data acquisition module acquires data in the following ways: video monitoring, environmental sensor detection, motion detection, and audio acquisition, which are respectively installed at monitoring points in the security monitoring area.

[0018] Preferably, the security and privacy protection module uses the Advanced Encryption Standard (AES) to encrypt data transmitted between nodes in the system during transmission encryption, ensuring that even if the data is intercepted during transmission, it cannot be easily decrypted; when performing storage encryption, the data stored in the database, hard disk or other storage media is directly encrypted, and the data can only be read and used with the correct key or verification.

[0019] A method for intelligent security inspection includes the following steps:

[0020] S1. Obtain real-time monitoring data information of the security monitoring area;

[0021] S2. Conduct intelligent analysis on the acquired real-time monitoring data to determine whether there are any abnormal problems in the security monitoring area;

[0022] S3. Determine the specific type of abnormal problem, the corresponding specific location and the danger level;

[0023] S4. Generate inspection instructions and alarm signals based on the determined results, and reasonably select robot inspection, manual inspection, or robot and manual collaborative inspection;

[0024] S5. After the inspection is completed, the actual abnormal status information and processing results are received from manual or robot feedback.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] By setting up an intelligent analysis module, the present invention can identify and analyze the received data, judge whether there are abnormal problems in the security area, determine the specific location, type and danger level of the abnormal problem, and according to the final determination result, reasonably select manual inspection, inspection robot inspection or manual and robot collaborative inspection mode to carry out targeted processing of abnormal problems, thereby realizing the function of coordinated cooperation between manual inspection and robot inspection, and being able to quickly respond and inspect the locations where abnormal problems occur, which is more targeted and conducive to improving the accuracy of abnormal problem detection, making full and reasonable use of robot and manual inspection resources, reducing inspection costs and improving inspection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A structural block diagram of a smart security inspection management system provided by the present invention;

[0028] Figure 2 A flow chart of a smart security inspection provided by the present invention. DETAILED DESCRIPTION

[0029] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0030] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0031] Reference Figure 1 to Figure 2 The present invention further describes an intelligent security patrol management system and method embodiment.

[0032] A smart security patrol management system includes: a data acquisition module, an automatic patrol module, and a security management platform. The data acquisition module and the automatic patrol module can select wireless transmission protocols such as Wi-Fi, ZigBee, LoRa, etc. to transmit data with the security management platform to ensure stable data transmission.

[0033] The data acquisition module is used to obtain real-time data and information in the security monitoring area; the data and information collected by the acquisition module include environmental parameter data and video image data. The data acquisition module collects data in the following ways: video monitoring, environmental sensor detection, motion detection, and audio acquisition, which are installed at the monitoring points in the security monitoring area respectively. Among them, video monitoring can use surveillance cameras.

[0034] Environmental sensor detection can include infrared sensors, temperature sensors, humidity sensors, smoke sensors, wind speed sensors, air pressure sensors, etc.

[0035] The automatic inspection module is used to plan inspection routes, perform inspection tasks within the security monitoring area, and record inspection results. The automatic inspection module is connected to the inspection robots on each floor through wireless signals. By obtaining the indoor map of each floor and using advanced SLAM and AI technologies, the inspection robots can plan inspection routes more intelligently and effectively avoid obstacles. They can also dynamically adjust and optimize the priority and schedule of inspection tasks based on historical data and real-time information.

[0036] The security management platform is used to receive the collected real-time data and information, and analyze and process them to determine whether there are any abnormalities in the security monitoring area. The security management platform includes an intelligent analysis module, an alarm module, a security and privacy protection module, and a data storage module; the intelligent analysis module is used to identify and analyze the received data, determine whether there are any abnormal problems in the security area, determine the specific location of the abnormal problem, determine the type of the abnormal problem as an abnormal environmental state or an abnormal human activity, determine the danger level of the abnormal environmental state problem, and reasonably select manual inspection, inspection robot inspection, or manual and robot collaborative inspection methods to deal with the abnormal problem in a targeted manner according to the final determined specific location, abnormal problem type, and danger level;

[0037] When the intelligent analysis module analyzes the environmental parameter data, it compares the obtained environmental parameters with the preset standard environmental parameters. If the obtained environmental parameters exceed the threshold of the preset standard environmental parameters, the environmental parameters are considered to be abnormal. For example, the monitoring data of point A in the detection area is: temperature 30°C, humidity 40%, and smoke concentration 0. The preset standard environmental parameters are temperature 10-25°C, humidity 30%-60, and smoke concentration 0-5%. At this time, the actual temperature at point A in the monitoring area exceeds the standard temperature range, then it is considered that there may be an abnormality at point A in the monitoring area.

[0038] When the intelligent analysis module analyzes the video image data, it compares the acquired video image data with the pre-built normal behavior model or normal environmental state model. If it is found that the data exceeds the range of normal behavior or normal environmental state or does not conform to the pattern of normal behavior, it is judged as abnormal; for example, through video surveillance and face recognition functions, it is identified that a man suddenly kicked the door in the corridor of the monitoring area, and the duration lasted for more than 10 seconds. This behavior exceeds the normal human behavior, and the behavior is determined to be abnormal human activity.

[0039] The above-mentioned normal behavior model and normal environment state model are obtained through model training in advance. They are mainly based on historical data and labeled abnormal samples. The trained classification model or machine learning model can automatically distinguish between normal and abnormal data. This model will learn the characteristic distribution of normal data and detect anomalies based on the difference between the newly received data and the normal data distribution.

[0040] The specific process of the intelligent analysis module to analyze video data is as follows: when new data enters the system, the classification model will compare it with normal data. If the characteristics of the new data are significantly different from the distribution of normal data, or exceed the preset normal range, it will be marked as abnormal. Then, features that can represent the abnormality are extracted from the original data. For video data, this may include the speed, direction, size, shape, color, etc. of the moving object. The type of abnormality is further determined by the extracted features.

[0041] In addition, since the environment and conditions may change over time, the intelligent analysis module provided in the present invention also has the function of continuous monitoring and updating. For example, if there were few human activities in a certain area in the past, but suddenly it becomes frequent, the system should be able to recognize this change and adjust its judgment criteria accordingly; at the same time, the intelligent analysis module can also realize the fusion of multiple data sources. For example, by combining the video analysis results and the changes in environmental parameters, the nature and severity of the anomaly can be more comprehensively understood; and the feature extraction method adopted can include any one of principal component analysis (PCA), wavelet transform (Wavelet Transform), local binary pattern (LBP), convolutional neural network (CNN), or multiple combinations thereof, which can adapt to different types of features and realize efficient and accurate extraction operations.

[0042] When calculating the danger level of abnormal environmental conditions, the formula , calculate the danger level Gk, compare Gk with the preset danger level judgment range G0, if the danger level Gk is less than the minimum value of the danger level judgment range G0, then the current environmental state level is considered to be low risk, the intelligent analysis module sends an inspection instruction to the inspection robot, if the danger level Gk is within the danger level judgment range G0, then the current environmental state level is considered to be medium risk, the intelligent analysis module sends an inspection instruction to the inspection personnel closest to the location of the abnormal problem, if the danger level Gk is greater than the maximum value of the danger level judgment range G0, then the current environmental state level is considered to be high risk, the intelligent analysis module sends inspection instructions to the inspection robot and the inspection personnel in turn, and sends an alarm instruction to the alarm and notification module, the inspection robot first conducts a field survey, and then sends the survey results to the inspection personnel, so that they can make corresponding strategies in time; because there are many situations of abnormal environmental states, such as gas leakage, water leakage, fire, etc., and each abnormal problem is matched with an independent factor specific value table, for example, a fire is detected at point B in the security monitoring area, where the specific value table of each factor corresponding to the fire is:

[0043] Severity Pi: Based on factors such as fire size and burning speed, it can be divided into several levels, such as 1 (low), 2 (medium), and 3 (high);

[0044] Duration Tc: in seconds, such as 1 (less than 5 seconds), 2 (5-20 seconds), 3 (more than 20 seconds);

[0045] Impact range Qm: evaluated based on the size of the affected area and the number of important facilities, such as 1 (small), 2 (medium), 3 (large);

[0046] Reference values ​​for determining the danger level: low danger level: 0-10 points, medium danger level: 11-20 points, high danger level: 21 points and above;

[0047] According to the application scenario and requirements, set appropriate weights for the above three factors. For example, assuming that duration is more important than impact scope, you can assign higher weights to them.

[0048] Assume that the fire at point B is determined to be of low severity, lasting for 5 seconds, and has a small impact range. Now substitute the formula for calculation: Gk (hazard level) = (1 × 1 × 1) / 10 = 0.1. Since 0.1 is in the range of 0-10, the fire hazard level at point B is determined to be low. The intelligent analysis module sends an inspection instruction to the inspection robot, notifying the robot to handle it first. If the abnormal problem expands after the robot arrives at the abnormal position B and cannot be handled, the robot will feedback to the security management platform, and the inspection personnel can be notified in time to handle it.

[0049] When it is judged to be an abnormal problem caused by human activities, the formula is used , calculate the danger level Hk, compare Hk with the preset danger level judgment range H0, if the danger level Hk is less than the minimum value of the danger level judgment range H0, it is considered that the current environmental status level is low risk, and the intelligent analysis module sends an inspection instruction to the one inspection personnel closest to the abnormal problem location; if the danger level Hk is within the danger level judgment range H0, it is considered that the current environmental status level is medium risk, and the intelligent analysis module sends an inspection instruction to the 2-3 inspection personnel closest to the abnormal problem location; if the danger level Hk is greater than the maximum value of the danger level judgment range H0, it is considered that the current environmental status level is high risk, and the intelligent analysis module sends an inspection instruction to more than 3 inspection personnel closest to the abnormal problem location;

[0050] Assume that the reference value of abnormal human activities is:

[0051] Ys (abnormal behavior severity): 200 samples of normal and abnormal behavior types are collected through big data statistics, and the abnormal behavior types are graded according to the number of occurrences. The fewer the number of occurrences, the higher the abnormal behavior value, and vice versa. The number of occurrences exceeding 100 is low level, with a value of 1, the number of occurrences between 50-100 is medium level, with a value of 2, and the number of occurrences less than 50 or 0 is high level, with a value of 3;

[0052] Fx (Focus): Evaluated based on the size of the affected area and the number of important facilities, such as 1 (small), 2 (medium), 3 (large);

[0053] Rn (number of people): the actual number of people identified by face recognition in video surveillance. For 1-2 people, the value is 1; for 3-4 people, the value is 2; for more than 4 people, the value is 3;

[0054] Danger level reference range: 0-10 is low level, 11-20 is medium level, and above 20 is high level;

[0055] Assume that a man appears at point C in the security monitoring area and hits the wall panel with a tool. The intelligent analysis module determines that the severity of the abnormal behavior is high and the impact range is high. Now substitute the above formula: Danger level = (3×3×1) / 10=0.9. Since 0.9 is within the range of 0-10, the abnormal behavior problem is considered to be a low-level risk. The intelligent analysis module sends an inspection instruction to the inspection personnel closest to the location of the abnormal problem.

[0056] The alarm module is used to automatically trigger an alarm and notify relevant personnel based on the results of intelligent analysis. When the intelligent analysis module determines that the danger level of the abnormal problem is medium or high or above, it sends an alarm instruction to the alarm module at the same time. At this time, the alarm module sends an alarm signal to the control end of the security management personnel through a wireless signal, and sends an alarm signal to the relevant patrol personnel at the same time.

[0057] The security and privacy protection module is used to encrypt and protect data transmission and storage, and to control and manage access rights; the data storage module is used to store the received monitoring data and analysis results. When encrypting transmission, the security and privacy protection module uses the Advanced Encryption Standard (AES) to encrypt the data transmitted between the nodes of the system, ensuring that even if it is intercepted during the data transmission process, it cannot be easily decrypted; when encrypting storage, the data stored in the database, hard disk or other storage media is directly encrypted, and the data can only be read and used with the correct key or verification.

[0058] In addition, as an embodiment of the present invention, a smart security patrol method is applied to a smart security patrol management system, comprising the following steps:

[0059] S1. Obtain real-time monitoring data information of the security monitoring area;

[0060] S2. Conduct intelligent analysis on the acquired real-time monitoring data to determine whether there are any abnormal problems in the security monitoring area;

[0061] S3. Determine the specific type of abnormal problem, the corresponding specific location and the danger level;

[0062] S4. Generate inspection instructions and alarm signals based on the determined results, and reasonably select robot inspection, manual inspection, or robot and manual collaborative inspection;

[0063] S5. After the inspection is completed, the actual abnormal status information and processing results are received from manual or robot feedback.

[0064] The above are only preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A smart security inspection management system, characterized in that: include: Data acquisition module, which is used to obtain real-time data and information within the security monitoring area; Automatic inspection module, which is used to plan inspection routes, perform inspection tasks in the security monitoring area, and record inspection results; A security management platform, which is used to receive the collected real-time data and information, and analyze and process it to determine whether there is any abnormality in the security monitoring area, wherein the security management platform includes an intelligent analysis module, an alarm module, a security and privacy protection module, and a data storage module; The intelligent analysis module is used to identify and analyze the received data, determine whether there are abnormal problems in the security area, determine the specific location of the abnormal problem, determine the type of the abnormal problem is an abnormal environmental state or abnormal human activity, determine the danger level of the abnormal environmental state problem, and reasonably select manual inspection, inspection robot inspection, or manual and robot collaborative inspection methods to deal with the abnormal problem in a targeted manner according to the final determined specific location, abnormal problem type and danger level; The alarm module is used to automatically trigger an alarm and notify relevant personnel based on the intelligent analysis results; The security and privacy protection module is used to encrypt and protect data transmission and storage, and to control and manage access rights; The data storage module is used to store the received monitoring data and analysis results; The data and information collected by the acquisition module include environmental parameter data and video image data. When the intelligent analysis module analyzes the environmental parameter data, the acquired environmental parameter is compared with the preset standard environmental parameter. If the acquired environmental parameter exceeds the threshold of the preset standard environmental parameter, the environmental parameter is considered to be abnormal. When the intelligent analysis module analyzes the video image data, the acquired video image data is compared with a pre-built normal behavior model or normal environment state model. If the data is found to be beyond the range of normal behavior or normal environment state or does not conform to the pattern of normal behavior, it is judged as abnormal; When calculating the danger level of abnormal environmental conditions, the formula , calculate the danger level Gk, compare Gk with the preset danger level judgment range G0, if the danger level Gk is less than the minimum value of the danger level judgment range G0, then the current environmental status level is considered to be low risk, and the intelligent analysis module sends an inspection instruction to the inspection robot. If the danger level Gk is within the danger level judgment range G0, then the current environmental status level is considered to be medium risk, and the intelligent analysis module sends an inspection instruction to the inspection personnel closest to the abnormal problem location. If the danger level Gk is greater than the maximum value of the danger level judgment range G0, then the current environmental status level is considered to be high risk, and the intelligent analysis module sends inspection instructions to the inspection robot and the inspection personnel in turn, and sends an alarm instruction to the alarm module. The inspection robot first conducts an on-site survey, and then sends the survey results to the inspection personnel so that they can make corresponding strategies in time.

2. The intelligent security inspection management system according to claim 1 is characterized in that: When it is judged to be an abnormal problem caused by human activities, the formula is used , calculate the danger level Hk, compare Hk with the preset danger level judgment range H0, if the danger level Hk is less than the minimum value of the danger level judgment range H0, it is considered that the current environmental status level is low risk, and the intelligent analysis module sends an inspection instruction to the inspector who is closest to the abnormal problem location; if the danger level Hk is within the danger level judgment range H0, it is considered that the current environmental status level is medium risk, and the intelligent analysis module sends an inspection instruction to the 2 to 3 inspectors who are closest to the abnormal problem location; if the danger level Hk is greater than the maximum value of the danger level judgment range H0, it is considered that the current environmental status level is high risk, and the intelligent analysis module sends an inspection instruction to more than 3 inspectors who are closest to the abnormal problem location.

3. The intelligent security inspection management system according to claim 2 is characterized in that: The data acquisition module collects data in the following ways: video monitoring, environmental sensor detection, motion detection, and audio acquisition, which are respectively installed at monitoring points in the security monitoring area.

4. The intelligent security inspection management system according to claim 3 is characterized in that: When performing transmission encryption, the security and privacy protection module uses the Advanced Encryption Standard (AES) to encrypt data transmitted between nodes in the system, ensuring that even if the data is intercepted during the data transmission process, it cannot be easily decrypted; when performing storage encryption, the data stored in the database, hard disk or other storage media is directly encrypted. The data can only be read and used with the correct key or verification.

5. A method for intelligent security patrol inspection, applied to the intelligent security patrol inspection management system as described in any one of claims 1 to 4, characterized in that: The following steps are involved: S1. Obtain real-time monitoring data information of the security monitoring area; S2. Conduct intelligent analysis on the acquired real-time monitoring data to determine whether there are any abnormal problems in the security monitoring area; S3. Determine the specific type of abnormal problem, the corresponding specific location and the danger level; S4. Generate inspection instructions and alarm signals based on the determined results, and reasonably select robot inspection, manual inspection, or robot and manual collaborative inspection; S5. After the inspection is completed, the actual abnormal status information and processing results are received from manual or robot feedback.

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