A method and system for intelligent campus environmental inspection

Abstract

This invention relates to the field of campus inspection technology, specifically disclosing an intelligent campus environment inspection method and system. The method includes periodically acquiring the location of each inspection terminal, locating a problem area on a campus map based on the location; acquiring the collected information from each inspection terminal based on the problem area; generating an inspection report based on the collected information; and during the operation of the inspection terminal, acquiring video information at a preset frequency and adjusting the movement speed in real time based on the video information. This invention acquires and recognizes video through the inspection terminal, adjusts the movement speed in real time during the recognition process, and calculates the movement speed based on the location information in the background. The problem area is then located by reverse calculation based on the movement speed, and the video acquired by each inspection terminal is read from the location result for subsequent monitoring. This invention has a clear monitoring objective, high utilization of computing resources, high flexibility, and can quickly adapt to different areas, exhibiting excellent portability.

Description

Technical Field

[0001] This invention relates to the field of campus inspection technology, specifically to an intelligent campus environment inspection method and system. Background Technology

[0002] Students are the main focus of a school environment. During the learning process, pressure from parents or teachers, jokes from classmates, and academic problems can create immense stress for students. For students whose minds are still developing, this can easily affect their emotions and lead to extreme behaviors. Therefore, it is necessary to monitor the school environment so that teachers can promptly identify student problems.

[0003] However, existing monitoring methods mostly rely on fixed cameras. While this method ensures comprehensive information, the identification process is very difficult, requires high computational resources, and has low flexibility. How to provide a more flexible monitoring architecture is the technical problem that this invention aims to solve. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent inspection method and system for campus environment to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for intelligent inspection of campus environment, the method comprising:

[0007] Obtain a campus map and determine the number of inspection terminals and their movement paths based on the campus map;

[0008] The location of each inspection terminal is obtained periodically, and the problem area is located on the campus map based on the location.

[0009] Based on the aforementioned problem range, the collected information from each inspection terminal is obtained;

[0010] A test report is generated based on the collected information;

[0011] During the operation of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information.

[0012] As a further aspect of the present invention: the step of obtaining a campus map and determining the number of inspection terminals and their movement paths based on the campus map includes:

[0013] The campus images containing temperature information are acquired periodically according to a preset aerial photography trajectory. The campus images are then identified to determine the location of personnel.

[0014] Mark access areas on the campus map with the location of personnel as the center;

[0015] The campus map is divided into sub-regions based on the access areas;

[0016] The motion path is determined based on the passage area, and the acquisition parameters are determined based on the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle.

[0017] As a further aspect of the present invention: the step of periodically acquiring the location of each inspection terminal and locating the problem area on the campus map based on the location includes:

[0018] The position of each inspection terminal is acquired periodically, and the movement speed of each inspection terminal is calculated.

[0019] The movement speed is compared with a preset speed value. When the movement speed is less than the preset speed value, the relative position of the inspection terminal in the movement path is calculated.

[0020] Based on the relative position, query the video capture angle, and mark the suspicious area on the campus map according to the video capture angle and the position of the inspection terminal;

[0021] Count all questionable intervals and the number of times they are marked. When the number of markings reaches a preset condition, the corresponding questionable area is marked as a problem interval.

[0022] In the step of counting all questionable intervals and their number of markings, questionable intervals that have an intersection are considered as the same interval and are merged.

[0023] As a further aspect of the present invention: the step of obtaining the collected information from each inspection terminal based on the problem interval includes:

[0024] Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location.

[0025] When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information;

[0026] Obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal based on the location of the problem interval, and extract the collected information based on the traversal and matching results;

[0027] In this process, the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each collection terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the collected information is extracted.

[0028] As a further aspect of the present invention: during the operation of the inspection terminal, the steps of acquiring video information according to a preset frequency and adjusting the movement speed in real time according to the video information include:

[0029] Video information is acquired according to a preset frequency and then converted into grayscale video.

[0030] The grayscale video is normalized, and the grayscale video is segmented into regions based on the normalization result.

[0031] Real-time comparison of region segmentation results between adjacent frames of images, and calculation of the difference rate;

[0032] When the difference rate reaches a preset threshold, the audio segment in the video information is extracted with the time point of the image as the center.

[0033] The audio segment is identified, and the movement speed is adjusted in real time based on the identification result.

[0034] As a further aspect of the present invention: the calculation formula for converting the video information into grayscale video is as follows:

[0035]

[0036] The formula for normalizing the grayscale video is:

[0037]

[0038] In the formula, I t (x,y) is the gray value of (x,y) at time t, R t (x,y), G t (x,y) and B t (x, y) are the RGB values ​​of (x, y) at time t, respectively; J t (x,y) is the normalized value of (x,y) at time t.

[0039] The present invention also provides an intelligent campus environment inspection system, the system comprising:

[0040] The inspection terminal setting module is used to acquire the campus map and determine the number of inspection terminals and their movement paths based on the campus map.

[0041] The problem area location module is used to periodically obtain the location of each inspection terminal and locate the problem area on the campus map based on the location;

[0042] The information acquisition module is used to acquire the information collected by each inspection end based on the problem interval;

[0043] The report generation module is used to generate a test report based on the collected information;

[0044] During the operation of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information.

[0045] As a further aspect of the present invention: the inspection end setting module includes:

[0046] The personnel location determination unit is used to acquire campus images containing temperature information at preset aerial photography trajectories, identify the campus images, and determine the personnel locations.

[0047] Access area marking unit, used to mark access areas on the campus map with the location of the person as the center;

[0048] Map segmentation units are used to segment the campus map according to the access areas to obtain sub-regions;

[0049] The acquisition parameter determination unit is used to determine the motion path based on the passage area and to determine the acquisition parameters according to the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle.

[0050] As a further aspect of the present invention: the problem interval location module includes:

[0051] The speed calculation unit is used to periodically acquire the position of each inspection terminal and calculate the movement speed of each inspection terminal.

[0052] The relative position calculation unit is used to compare the movement speed with a preset speed value, and when the movement speed is less than the preset speed value, calculate the relative position of the inspection end in the movement path;

[0053] The interval marking unit is used to query the video acquisition angle based on the relative position, and mark the suspicious interval on the campus map based on the video acquisition angle and the position of the inspection end.

[0054] The interval statistics unit is used to count all questionable intervals and the number of times they are marked. When the number of markings reaches a preset condition, the corresponding questionable area is marked as a problem interval.

[0055] In the step of counting all questionable intervals and their number of markings, questionable intervals that have an intersection are considered as the same interval and are merged.

[0056] As a further aspect of the present invention: the information acquisition module includes:

[0057] The traversal matching unit is used to obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal according to the location of the problem interval, and extract the collection information according to the traversal matching result;

[0058] Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location.

[0059] When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information;

[0060] In this process, the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each collection terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the collected information is extracted.

[0061] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention acquires and identifies videos through the inspection terminal, adjusts the movement speed in real time during the identification process, obtains location information in real time in the background to calculate the movement speed, reverse-engineers the problem area based on the movement speed, and then reads the videos acquired by each inspection terminal from the positioning results for subsequent supervision; the present invention has a clear supervision target, high utilization of computing resources, high flexibility, and can quickly adapt to different areas, with excellent portability. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0063] Figure 1 This is a flowchart of a smart campus environment inspection method.

[0064] Figure 2 This is the first sub-flowchart of the intelligent campus environment inspection method.

[0065] Figure 3 This is the second sub-flowchart of the intelligent campus environment inspection method.

[0066] Figure 4 This is a block diagram showing the composition of an intelligent campus environment inspection system. Detailed Implementation

[0067] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0068] Example 1

[0069] Figure 1The flowchart below illustrates a method for intelligent campus environment inspection. In this embodiment of the invention, a method for intelligent campus environment inspection includes:

[0070] Step S100: Obtain a campus map and determine the number of inspection terminals and their movement paths based on the campus map;

[0071] The campus map is pre-stored data by default. The campus map can be obtained by reading the top view in the campus building model. The number of inspection terminals and their movement paths are determined according to the zoning in the campus map. Multiple inspection terminals have the same movement path. When an inspection terminal completes a movement path, it can obtain video of most areas of the campus. The number of inspection terminals is determined by the staff according to the specific situation. The more inspection terminals there are, the more video is obtained and the better the inspection effect.

[0072] Step S200: Periodically obtain the location of each inspection terminal, and locate the problem area on the campus map based on the location;

[0073] During the movement of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information. Therefore, the position of each inspection terminal is acquired periodically, and the speed of each inspection terminal can be calculated based on the position and time (the data processing terminal calculates the speed of the inspection terminal based on the position). Generally, if the inspection terminal detects an anomaly, it will reduce the video and acquire a longer video. Therefore, the interval where the speed slows down is the interval where there is a problem, which is the aforementioned problem interval.

[0074] Step S300: Obtain the collected information from each inspection terminal based on the problem interval;

[0075] The information collected by the inspection terminal is sent to the data processing terminal at regular intervals. A large part of this data is normal data with little analytical value, and therefore has no value in transmission. In other words, only a portion of the data from each inspection terminal is useful data (data corresponding to the problem area), and this type of data can be obtained for analysis.

[0076] Step S400: Generate a detection report based on the collected information;

[0077] The process of generating a test report based on the collected information is relatively easy and can be completed with the help of a human terminal containing recognition algorithms. The collected information is sent to the human terminal, and the test report is received from the human terminal.

[0078] Figure 2 This is the first sub-flowchart of the intelligent campus environment inspection method. The steps of obtaining a campus map and determining the number of inspection terminals and their movement paths based on the campus map include:

[0079] Step S101: Acquire campus images containing temperature information at set intervals according to the preset aerial photography trajectory, identify the campus images, and determine the location of personnel;

[0080] In the campus map, all roads are pre-set. However, sometimes students will take some "side paths," which are determined by the location of the people. In the preprocessing stage before the method of this invention is used, campus images containing temperature information are acquired multiple times according to the preset aerial photography trajectory (this process can also be completed by cameras installed on campus). The location of people can be determined by recognizing the campus images based on the temperature information.

[0081] Step S102: Mark the access area on the campus map with the personnel's location as the center;

[0082] Based on the location of the personnel, the areas that can be accessed on the campus map are marked as accessible areas;

[0083] Step S103: Divide the campus map into sub-regions based on the access areas;

[0084] The process of dividing the campus map is not complicated. Once the passable areas are marked, other areas are considered impassable areas. Of course, the division of the campus map is dynamic. If some areas in the impassable areas are used by people, then the corresponding areas will also be marked as passable areas.

[0085] Step S104: Determine the motion path based on the passage area, and determine the acquisition parameters according to the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle;

[0086] The inspection device moves within the passageway and determines its movement path. As it moves along the path, it continuously captures video. The acquisition parameters at each location need to be preset, with the goal of maximizing the range of video footage acquired by the inspection device.

[0087] Figure 3 This is the second sub-flowchart of the intelligent campus environment inspection method. The step of periodically acquiring the location of each inspection terminal and locating the problem area on the campus map based on the location includes:

[0088] Step S201: Periodically acquire the position of each inspection terminal and calculate the movement speed of each inspection terminal;

[0089] The data processing terminal periodically receives the position signals sent by the inspection terminal. Based on the position signals and the time, the movement speed of each inspection terminal can be calculated.

[0090] Step S202: Compare the movement speed with a preset speed value. When the movement speed is less than the preset speed value, calculate the relative position of the inspection terminal in the movement path.

[0091] As can be seen from the above, during operation, the inspection terminal will identify the acquired video. If a problem is found in the acquired video, the movement speed will be adjusted. Therefore, the movement speed can be used to remotely determine whether there is a problem with the inspection terminal.

[0092] Step S203: Query the video acquisition angle based on the relative position, and mark the suspicious area on the campus map based on the video acquisition angle and the position of the inspection terminal;

[0093] The video capture angle is a capture parameter, which is related to the location. The corresponding video capture angle can be found by the relative position of the inspection terminal in the movement path, and then the corresponding area can be marked on the campus map as a suspicious area.

[0094] Step S204: Count all suspicious intervals and their marking counts. When the marking count reaches a preset condition, mark the corresponding suspicious area as a problem interval.

[0095] There is more than one inspection terminal. If the previous inspection terminal marks a certain area as a suspicious area, and the next inspection terminal moves to that area and still marks the area as a suspicious area, then the probability that there is indeed an anomaly in the suspicious area is very high. Therefore, the number of times a suspicious area is marked is a very important parameter.

[0096] Furthermore, the preset conditions are determined by the management personnel. If the management personnel want to conduct higher-level supervision of the campus, they can set the conditions to once. At this time, as long as an inspection terminal marks a certain area, that area will enter the next level of supervision.

[0097] It is worth mentioning that, in the step of counting all suspicious intervals and their number of markings, suspicious intervals that have an intersection are considered as the same interval and are merged; if the areas marked by two inspection ends only partially overlap, they will be considered as the same area and merged.

[0098] As a preferred embodiment of the technical solution of the present invention, the step of obtaining the collected information of each inspection terminal based on the problem interval includes:

[0099] Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location.

[0100] When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information;

[0101] The above-mentioned limitations restrict the storage process of the collected information. The marking results of each inspection terminal for the area will be synchronized to other inspection terminals. When the inspection terminal moves to the area marked by other inspection terminals, it will mark the collected video for the corresponding time period.

[0102] Obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal based on the location of the problem interval, and extract the collected information based on the traversal and matching results;

[0103] When managers want to query the video of a specific location, they can retrieve the marked data from each inspection terminal.

[0104] It should be noted that the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each acquisition terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the acquisition information is extracted. The purpose of this limitation is to maximize the amount of video (different time periods) corresponding to a certain location, so as to facilitate the subsequent recognition process.

[0105] As a preferred embodiment of the technical solution of the present invention, during the operation of the inspection terminal, the steps of acquiring video information according to a preset frequency and adjusting the movement speed in real time according to the video information include:

[0106] Video information is acquired according to a preset frequency and then converted into grayscale video.

[0107] The grayscale video is normalized, and the grayscale video is segmented into regions based on the normalization result.

[0108] Real-time comparison of region segmentation results between adjacent frames of images, and calculation of the difference rate;

[0109] When the difference rate reaches a preset threshold, the audio segment in the video information is extracted with the time point of the image as the center.

[0110] The audio segment is identified, and the movement speed is adjusted in real time based on the identification result.

[0111] The above content defines the working process of the inspection terminal. The process of adjusting the movement speed of the inspection terminal is an essential technical feature of the present invention. The inspection terminal has a built-in video recognition algorithm, which acquires video information according to a preset frequency and converts the video information into grayscale video according to a preset image conversion formula. Compared with color values, grayscale values ​​are one-dimensional data, but their range is [0, 255], which is more difficult to process. Therefore, the grayscale video is further processed, that is, normalized, adjusting the range of values ​​of each point. Based on the normalized video, the grayscale video can be segmented into regions. It should be noted that the processing of the video is actually processing the images in the video sequentially. The region segmentation process is a kind of contour recognition, which groups pixels with small differences into one category to obtain sub-regions.

[0112] By comparing images from adjacent time points in real time, the differences between the two images can be calculated. If a difference exists, it means that the content in the video has changed. At this point, it is necessary to extract the audio information and identify it. The identification method can be text recognition. Then, it is determined whether there are any sensitive words. Based on the presence of sensitive words, the motion speed can be adjusted in real time.

[0113] In one embodiment of the technical solution of the present invention, the calculation formula for converting the video information into grayscale video is as follows:

[0114]

[0115] The formula for normalizing the grayscale video is:

[0116]

[0117] In the formula, I t (x,y) is the gray value of (x,y) at time t, R t (x,y), G t (x,y) and B t (x, y) are the RGB values ​​of (x, y) at time t, respectively; J t (x,y) is the normalized value of (x,y) at time t.

[0118] Example 2

[0119] Figure 4 This is a structural block diagram of a campus environment intelligent inspection system. In this embodiment of the invention, a campus environment intelligent inspection system 10 includes:

[0120] The inspection terminal setting module 11 is used to acquire a campus map and determine the number of inspection terminals and their movement paths based on the campus map.

[0121] Problem area location module 12 is used to periodically obtain the location of each inspection terminal and locate the problem area on the campus map based on the location;

[0122] The information acquisition module 13 is used to acquire the information collected by each inspection end based on the problem interval;

[0123] Report generation module 14 is used to generate a detection report based on the collected information;

[0124] During the operation of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information.

[0125] The inspection terminal setting module 11 includes:

[0126] The personnel location determination unit is used to acquire campus images containing temperature information at preset aerial photography trajectories, identify the campus images, and determine the personnel locations.

[0127] Access area marking unit, used to mark access areas on the campus map with the location of the person as the center;

[0128] Map segmentation units are used to segment the campus map according to the access areas to obtain sub-regions;

[0129] The acquisition parameter determination unit is used to determine the motion path based on the passage area and to determine the acquisition parameters according to the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle.

[0130] The problem interval location module 12 includes:

[0131] The speed calculation unit is used to periodically acquire the position of each inspection terminal and calculate the movement speed of each inspection terminal.

[0132] The relative position calculation unit is used to compare the movement speed with a preset speed value, and when the movement speed is less than the preset speed value, calculate the relative position of the inspection end in the movement path;

[0133] The interval marking unit is used to query the video acquisition angle based on the relative position, and mark the suspicious interval on the campus map based on the video acquisition angle and the position of the inspection end.

[0134] The interval statistics unit is used to count all questionable intervals and the number of times they are marked. When the number of markings reaches a preset condition, the corresponding questionable area is marked as a problem interval.

[0135] In the step of counting all questionable intervals and their number of markings, questionable intervals that have an intersection are considered as the same interval and are merged.

[0136] The information acquisition module 13 includes:

[0137] The traversal matching unit is used to obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal according to the location of the problem interval, and extract the collection information according to the traversal matching result;

[0138] Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location.

[0139] When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information;

[0140] In this process, the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each collection terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the collected information is extracted.

[0141] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent inspection of the campus environment, characterized in that, The method includes: Obtain a campus map and determine the number of inspection terminals and their movement paths based on the campus map; The location of each inspection terminal is obtained periodically, and the problem area is located on the campus map based on the location. Based on the aforementioned problem range, the collected information from each inspection terminal is obtained; A test report is generated based on the collected information; During the operation of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information; The step of periodically acquiring the location of each inspection terminal and locating the problem area on the campus map based on the location includes: The position of each inspection terminal is acquired periodically, and the movement speed of each inspection terminal is calculated. The movement speed is compared with a preset speed value. When the movement speed is less than the preset speed value, the relative position of the inspection terminal in the movement path is calculated. Based on the relative position, query the video capture angle, and mark the suspicious area on the campus map according to the video capture angle and the position of the inspection terminal; Count all questionable intervals and the number of times they are marked. When the number of markings reaches a preset condition, the corresponding questionable area is marked as a problem interval. In the step of counting all questionable intervals and their number of markings, questionable intervals that have an intersection are considered as the same interval and are merged.

2. The intelligent campus environment inspection method according to claim 1, characterized in that, The steps of obtaining a campus map and determining the number of inspection terminals and their movement paths based on the campus map include: The campus images containing temperature information are acquired periodically according to a preset aerial photography trajectory. The campus images are then identified to determine the location of personnel. Mark access areas on the campus map with the location of personnel as the center; The campus map is divided into sub-regions based on the access areas; The motion path is determined based on the passage area, and the acquisition parameters are determined based on the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle.

3. The intelligent campus environment inspection method according to claim 1, characterized in that, The steps for obtaining the collected information from each inspection terminal based on the problem interval include: Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location. When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information; Obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal based on the location of the problem interval, and extract the collected information based on the traversal and matching results; In this process, the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each collection terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the collected information is extracted.

4. The intelligent campus environment inspection method according to claim 1, characterized in that, During the operation of the inspection terminal, the steps of acquiring video information according to a preset frequency and adjusting the movement speed in real time based on the video information include: Video information is acquired according to a preset frequency and then converted into grayscale video. The grayscale video is normalized, and the grayscale video is segmented into regions based on the normalization result. Real-time comparison of region segmentation results between adjacent frames of images, and calculation of the difference rate; When the difference rate reaches a preset threshold, the audio segment in the video information is extracted with the time point of the image as the center. The audio segment is identified, and the movement speed is adjusted in real time based on the identification result.

5. The intelligent campus environment inspection method according to claim 4, characterized in that, The formula for converting the video information into grayscale video is as follows: The formula for normalizing the grayscale video is: In the formula, I t (x,y) is the gray value of (x,y) at time t, R t (x,y), G t (x,y) and B t (x, y) are the RGB values ​​of (x, y) at time t, respectively; J t (x,y) is the normalized value of (x,y) at time t.

6. A campus environment intelligent inspection system, characterized in that, The system includes: The inspection terminal setting module is used to acquire the campus map and determine the number of inspection terminals and their movement paths based on the campus map. The problem area location module is used to periodically obtain the location of each inspection terminal and locate the problem area on the campus map based on the location; The information acquisition module is used to acquire the information collected by each inspection end based on the problem interval; The report generation module is used to generate a test report based on the collected information; During the operation of the inspection terminal, video information is acquired according to a preset frequency, and the movement speed is adjusted in real time based on the video information; The problem interval location module includes: The speed calculation unit is used to periodically acquire the position of each inspection terminal and calculate the movement speed of each inspection terminal. The relative position calculation unit is used to compare the movement speed with a preset speed value, and when the movement speed is less than the preset speed value, calculate the relative position of the inspection end in the movement path; The interval marking unit is used to query the video acquisition angle based on the relative position, and mark the suspicious interval on the campus map based on the video acquisition angle and the position of the inspection end. The interval statistics unit is used to count all questionable intervals and the number of times they are marked. When the number of markings reaches a preset condition, the corresponding questionable area is marked as a problem interval. In the step of counting all questionable intervals and their number of markings, questionable intervals that have an intersection are considered as the same interval and are merged.

7. The intelligent campus environment inspection system according to claim 6, characterized in that, The inspection terminal setting module includes: The personnel location determination unit is used to acquire campus images containing temperature information at preset aerial photography trajectories, identify the campus images, and determine the personnel locations. Access area marking unit, used to mark access areas on the campus map with the location of the person as the center; Map segmentation units are used to segment the campus map according to the access areas to obtain sub-regions; The acquisition parameter determination unit is used to determine the motion path based on the passage area and to determine the acquisition parameters according to the sub-region and the passage area; the acquisition parameters include resolution and video acquisition angle.

8. The intelligent campus environment inspection system according to claim 6, characterized in that, The information acquisition module includes: The traversal matching unit is used to obtain the location of the problem interval, traverse and match the location tags in the information collected by each collection terminal according to the location of the problem interval, and extract the collection information according to the traversal matching result; Once any inspection terminal marks a suspicious area on the school map, the relative position of that inspection terminal is read and sent to other inspection terminals as the suspicious location. When any inspection terminal moves to a suspicious location, a location tag is inserted into the collected information; In this process, the location of the interval is replaced by the center point of the interval. In the step of traversing and matching the location tags in the information collected by each collection terminal according to the location of the problem interval, when the distance between the location of the problem interval and the location tag is less than a preset distance threshold, the collected information is extracted.

Images