Monitoring method, system, device and equipment based on information acquisition FSU

Abstract

The invention relates to the technical field of intelligent control, and discloses an information acquisition FSU-based monitoring method, system, device and equipment, and the method comprises the steps: building a three-dimensional space model based on the layout of a point location of a camera device and the layout of a point location of an infrared detection device, and when the camera device and / or the infrared detection device detects the change of a signal, building a three-dimensional space model; and acquiring abnormal signal data through the information acquisition FSU, performing edge calculation analysis on the abnormal signal data through an image recognition algorithm based on the three-dimensional space model to obtain a scene recognition result, and triggering a monitoring control strategy according to the scene recognition result. According to the method, the abnormal signal data is subjected to edge calculation analysis through the three-dimensional space model and the image recognition algorithm, so that the monitoring control strategy is triggered, the monitoring operation efficiency is improved, and the accuracy and the stability of the monitoring data are ensured.

Description

Technical Field

[0001] The present application relates to the field of control technology, and in particular to a monitoring method, system, device and equipment based on an information collection FSU. Background Art

[0002] Traditional dynamic environment room monitoring equipment monitors through independent processing of access control, infrared and other equipment, and generally can only report relevant alarm information to the platform for processing. In addition, the camera equipment in the room is also connected to the platform through traditional dynamic environment gateway equipment. All information is aggregated and processed on the platform. The operation steps are complicated and the workload of personnel is heavy. In large platforms, due to the large amount of information, the accuracy and real-time performance of the received monitoring data information are poor, and there is also the problem of false alarms. Summary of the invention

[0003] The main purpose of this application is to provide a monitoring method, system, device and equipment based on information collection FSU, aiming to solve the technical problem that the accuracy and stability of monitoring data cannot be guaranteed due to the limitations of the linkage and computing capabilities of traditional gateway devices.

[0004] To achieve the above objectives, the present application proposes a monitoring method based on information collection FSU, the method comprising:

[0005] Construct a three-dimensional space model based on the camera equipment and infrared detection equipment layout points;

[0006] When the camera device and / or infrared detection device detects a signal change, the abnormal signal data is acquired through the information acquisition FSU;

[0007] Based on the three-dimensional space model, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result, and a monitoring and control strategy is triggered according to the scene recognition result.

[0008] In one embodiment, the scene recognition results include entry of operation and maintenance personnel, intrusion of illegal personnel and misentry of other animals. Based on the three-dimensional space model, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain the scene recognition result, and the step of triggering the monitoring control strategy according to the scene recognition result includes:

[0009] Based on the three-dimensional space model, real-time data is acquired through a signal collector;

[0010] When the abnormal signal data is consistent with the real-time data, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result;

[0011] When the scene recognition result is that the operation and maintenance personnel enter or an illegal person breaks in, extracting the facial information of the abnormal signal data;

[0012] Recognize the facial information through an image recognition algorithm to obtain a recognition result, and output corresponding information according to the recognition result;

[0013] When the scene recognition result is that other animals have strayed in, the species category of the life form is obtained by analyzing the abnormal signal data, and corresponding alarm information is generated.

[0014] In one embodiment, the step of identifying the face information by using an image recognition algorithm, obtaining a recognition result, and outputting corresponding information according to the recognition result includes:

[0015] Recognize the facial information through an image recognition algorithm to obtain a recognition result;

[0016] When the recognition result is an illegal person, a corresponding alarm message is generated and the facial information is output;

[0017] When the identification result is an operation and maintenance personnel, the identification result is output.

[0018] In one embodiment, when the scene recognition result is that other animals have strayed into the scene, the step of obtaining the species category of the living organism by analyzing the abnormal signal data and generating corresponding alarm information includes:

[0019] When the scene recognition result is that other animals have strayed in, based on the edge computing animal model, feature extraction and classification are performed on the abnormal signal data to obtain key information of the living organism;

[0020] The key information of the living organism is mapped to the corresponding species category through the edge computing animal model classifier, the species category of the living organism is obtained, and the corresponding alarm information is generated.

[0021] In one embodiment, when the camera device and / or the infrared detection device detects a signal change, the step of acquiring abnormal signal data through the information acquisition FSU includes:

[0022] When the camera device and / or infrared detection device detects a signal change, the signal change single monitoring area triggers the adjacent monitoring area;

[0023] Based on the interactive identification between the PTZ camera device and the adjacent monitoring area, the spatial position of the signal change is determined by acquiring the infrared radiation intensity and change direction of the signal change;

[0024] The spatial position is photographed by the camera device to obtain an abnormal picture, and the abnormal picture is transmitted to the information collection FSU as abnormal signal data.

[0025] In one embodiment, the step of constructing a three-dimensional space model based on the camera equipment and the infrared detection equipment comprises:

[0026] Based on the camera equipment and infrared detection equipment layout points, the initial three-dimensional space model is constructed through the software built-in model;

[0027] or,

[0028] Based on the camera equipment layout points and the infrared detection equipment layout points, image data of different perspectives are acquired through the pan-tilt camera equipment, and an initial three-dimensional space model is constructed according to the image data;

[0029] The camera device and the infrared detection device are mapped to corresponding points of the initial three-dimensional space model to obtain a three-dimensional space model.

[0030] In addition, to achieve the above-mentioned purpose, the present application also proposes a monitoring system based on an information collection FSU, wherein the monitoring system based on the information collection FSU comprises: a camera device, an infrared detection device and an information collection FSU;

[0031] The camera device and the infrared detection device are both connected to the information collection FSU.

[0032] In addition, to achieve the above purpose, the present application also proposes a monitoring device based on an information collection FSU, the monitoring device based on an information collection FSU comprising:

[0033] A model building module is used to build a three-dimensional space model based on the camera equipment and infrared detection equipment.

[0034] A data acquisition module, used to acquire abnormal signal data through the information acquisition FSU when the camera device and / or the infrared detection device detects a signal change;

[0035] The monitoring and control module is used to perform edge computing analysis on the abnormal signal data based on the three-dimensional space model through an image recognition algorithm to obtain a scene recognition result, and trigger a monitoring and control strategy according to the scene recognition result.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes a monitoring device based on information collection FSU, the device comprising: a memory, a processor and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the monitoring method based on information collection FSU as described above.

[0037] In addition, to achieve the above objectives, the present application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the monitoring method based on the information collection FSU as described above are implemented.

[0038] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the monitoring method based on the information collection FSU as described above are implemented.

[0039] The technical solution proposed in this application is to construct a three-dimensional space model based on the layout of camera equipment and infrared detection equipment. When the camera equipment and / or infrared detection equipment detects a signal change, the abnormal signal data is obtained through the information acquisition FSU. Based on the three-dimensional space model, the abnormal signal data is analyzed by edge computing through the image recognition algorithm to obtain the scene recognition result, and the monitoring control strategy is triggered according to the scene recognition result. Because the application uses the three-dimensional space model and image recognition algorithm to perform edge computing analysis on the abnormal signal data, thereby triggering the monitoring control strategy, the monitoring operation efficiency is improved, and the accuracy and stability of the monitoring data are ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0042] Figure 1 A flow chart of the monitoring method embodiment 1 of the present application based on information collection FSU is provided;

[0043] Figure 2 A flow chart of the second embodiment of the monitoring method based on information collection FSU of the present application is provided;

[0044] Figure 3 This is the flow chart of monitoring data fusion analysis for this application scenario;

[0045] Figure 4 A flow chart of the third embodiment of the monitoring method based on information collection FSU of the present application is provided;

[0046] Figure 5This is a schematic diagram of the module structure of a monitoring device based on information collection FSU according to an embodiment of the present application;

[0047] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the monitoring method based on the information collection FSU in the embodiment of the present application.

[0048] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] Traditional dynamic environment room monitoring equipment monitors through independent processing of access control, infrared and other intelligent devices, and generally can only report relevant alarm information to the platform for processing. In addition, the camera equipment in the room is also connected to the platform through traditional dynamic environment gateway equipment. All information is aggregated and processed on the platform. The operation steps are complicated and the workload of personnel is heavy. In large platforms, due to the large amount of information, the accuracy and real-time performance of the received monitoring data information are poor, and there is also the problem of false alarms.

[0052] Therefore, in order to overcome the above-mentioned defects, the present application provides a solution, which performs edge computing analysis on abnormal signal data through a three-dimensional spatial model and image recognition algorithm, thereby triggering a monitoring control strategy, improving the monitoring operation efficiency, and ensuring the accuracy and stability of the monitoring data.

[0053] It should be noted that the execution subject of each embodiment of the present application can be a computing service system with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic system capable of realizing the above functions, a monitoring system based on an information collection FSU, etc. The following embodiments are described below taking a monitoring system based on an information collection FSU as an example.

[0054] Based on this, the embodiment of the present application provides a monitoring method based on information collection FSU, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the monitoring method based on information collection FSU of the present application.

[0055] In this embodiment, the monitoring method based on the information collection FSU includes steps S10 to S30:

[0056] Step S10, constructing a three-dimensional space model based on the camera equipment layout points and the infrared detection equipment layout points.

[0057] It should be noted that a computer room usually refers to a room or space where important IT equipment such as servers, network equipment, storage devices, etc. are placed. It is the core part of a data center, communication center or enterprise IT infrastructure. This application can be applied in a computer room environment, and this embodiment does not limit this.

[0058] In the computer room, the camera equipment usually refers to high-definition cameras or intelligent surveillance cameras, which are used to capture the image information in the computer room in real time. Infrared detection technology is based on the principle of infrared radiation. All objects above absolute zero (-273.15℃) will emit infrared radiation. When a living organism moves within the detection range, the infrared detection signal will change, and the intensity and direction of the infrared radiation emitted by the living organism will be analyzed. The three-dimensional space model is a digital model built based on three-dimensional geometric information, which can truly reflect the structure, equipment layout, spatial relationship and other information inside the computer room.

[0059] Step S20: When the camera device and / or the infrared detection device detects a signal change, abnormal signal data is acquired through the information acquisition FSU.

[0060] It is understandable that the camera equipment captures the dynamic scenes in the computer room in real time. When abnormal changes appear in the image, such as the movement of living things, unusual movement of equipment position, camera being blocked, etc., these are regarded as signal changes.

[0061] At the same time, infrared detection equipment focuses on life detection and temperature monitoring in the room. When infrared detection equipment detects abnormal temperature changes, such as unauthorized life activity, equipment overheating, or potential fire hazards, these are also considered important signal changes. Once the camera or infrared detection equipment detects a signal change, this information is immediately transmitted to the information collection FSU (Field Supervision Unit).

[0062] It should be noted that the information collection FSU is an edge computing gateway device with powerful data processing capabilities and can also perform real-time analysis and decision-making at the source of data generation. It receives raw data from cameras and infrared detection equipment, and uses built-in algorithms and models to quickly process these data to identify potential abnormal signals.

[0063] In this application, when the information collection FSU is installed, it is ensured that the infrared detection equipment and the camera equipment can be normally connected through physical wiring. The information collection FSU can normally configure the access and data access of various devices in the software interface, the video stream of the camera equipment can be accessed by pulling the stream, and the various image recognition algorithms downloaded by the edge computing gateway can be used normally. In addition, the field of view captured by the camera equipment layout points needs to radiate each other to reduce the blind spots of the field of view, and the range detected by the infrared detection equipment layout points needs to cover the entire computer room.

[0064] It is understandable that compared with traditional data center or cloud processing methods, edge computing gateway devices have lower latency and higher real-time performance in data processing. This means that when an abnormal situation occurs in the computer room, the information collection FSU can quickly capture these changes and immediately trigger the corresponding alarm or response mechanism, thereby effectively shortening the time from abnormal detection to problem solving.

[0065] Step S30: Based on the three-dimensional space model, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result, and a monitoring and control strategy is triggered according to the scene recognition result.

[0066] It should be noted that image recognition algorithms, such as convolutional neural networks or deep learning models, can be deployed on edge computing devices to identify key information such as personnel activities and equipment status changes in the computer room, and detect abnormal signals such as equipment overheating and human intrusion.

[0067] It should be understood that based on the edge computing analysis results of the abnormal signal data, combined with the equipment layout and location information in the three-dimensional space model, a scene recognition result is generated, and based on the scene recognition result, the corresponding monitoring and control strategy is automatically triggered.

[0068] For example, if a human intrusion is detected, the access control system or monitoring system can be activated to record and track the intruder; if the equipment is detected to be overheating, the alarm system can be triggered to notify the operation and maintenance personnel to handle it.

[0069] In addition, monitoring and control strategies can also include automatic adjustment of equipment parameters (such as fan speed, air conditioning temperature, etc.), triggering of emergency response plans, etc.

[0070] This embodiment constructs a three-dimensional space model based on the camera equipment layout points and infrared detection equipment layout points. When the camera equipment and / or infrared detection equipment detects a signal change, the abnormal signal data is obtained through the information acquisition FSU. Based on the three-dimensional space model, the abnormal signal data is edge-computing analyzed through the image recognition algorithm to obtain the scene recognition result, and the monitoring control strategy is triggered according to the scene recognition result. Since the present application uses the three-dimensional space model and the image recognition algorithm to perform edge computing analysis on the abnormal signal data, thereby triggering the monitoring control strategy, the monitoring operation efficiency is improved, and the accuracy and stability of the monitoring data are ensured.

[0071] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , the step S30 includes S301 to S305:

[0072] Step S301, based on the three-dimensional space model, real-time data is acquired through a signal acquisition FSU.

[0073] It is understandable that although the camera or infrared equipment can detect signal changes, due to the performance limitations of the equipment itself (such as resolution, detection range, sensitivity, etc.) and the influence of environmental factors (such as light changes, temperature fluctuations, noise interference, etc.), the detected data may have certain errors or uncertainties. The accuracy of the data can be further improved by collecting real-time data through the information acquisition FSU and comparing and verifying it with the abnormal signal data.

[0074] Step S302, when the abnormal signal data is consistent with the real-time data, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result.

[0075] It should be understood that the abnormal signal data is consistent with the real-time data, which means that the signal changes captured by the camera or infrared detection equipment (such as people breaking in, animals entering by mistake, or equipment overheating, etc.) and the real-time data collected by the information collection FSU at the same time (such as video streams, temperature readings, etc.) are synchronized in time and confirm each other in content, that is, both indicate that some abnormal event has occurred.

[0076] It can be understood that edge computing transfers computing and data storage tasks from centralized data centers to the edge of the network, that is, close to where the data is generated, and performs real-time processing and analysis of abnormal signal data near the camera or infrared detection equipment (i.e., the edge), and combines image recognition algorithms to identify specific scenes occurring in the computer room, such as entry of operation and maintenance personnel, intrusion of illegal personnel, and other animals entering by mistake.

[0077] Step S303, when the scene recognition result is that the operation and maintenance personnel enter or an illegal person breaks in, extract the facial information of the abnormal signal data.

[0078] It is understandable that if the scene recognition result is that operation and maintenance personnel have entered or illegal personnel have broken in, facial information is extracted from the video stream or image frame, that is, a face detection algorithm is used to locate the face area in the image, and a face feature extraction algorithm is used to extract key features of the face, such as the position and shape of the eyes, nose, mouth, etc.

[0079] Step S304, identifying the face information through an image recognition algorithm, obtaining a recognition result, and outputting corresponding information according to the recognition result.

[0080] It should be understood that the extracted facial information is input into an image recognition algorithm, the algorithm extracts features of the input facial image, and compares them with features in a preset database.

[0081] It should be noted that the preset database contains the facial features of known operation and maintenance personnel, and may also contain the facial features of illegal persons in the blacklist.

[0082] Based on the result of feature comparison, the algorithm will determine whether the input face image matches a feature in the database. If the match is successful, the system will obtain a recognition result, that is, the face is a known operation and maintenance personnel, or an illegal person on a blacklist, and output the corresponding information based on the recognition result.

[0083] The step S304 includes:

[0084] Recognize the facial information through an image recognition algorithm to obtain a recognition result;

[0085] When the recognition result is an illegal person, a corresponding alarm message is generated and the facial information is output;

[0086] When the identification result is an operation and maintenance personnel, the identification result is output.

[0087] It is understandable that, based on the recognition result, it is determined whether the recognized face is an illegal person or an operation and maintenance personnel. When the recognition result is an illegal person, the system immediately generates an alarm message, which may include detailed information such as the illegal person's facial image, entry time, and location. When the recognition result is an operation and maintenance personnel, the system will record the entry information of the operation and maintenance personnel, such as time and location, and may also output the recognition result to the relevant management system.

[0088] Step S305, when the scene recognition result is that other animals have strayed in, the species category of the life form is obtained by analyzing the abnormal signal data, and corresponding alarm information is generated.

[0089] It should be understood that when other animals are identified as having strayed into the room, the system will further analyze the abnormal signal data, which usually includes video streams, infrared signals, etc. By analyzing the abnormal signal data, the system can identify the species of the life form that strayed into the room, such as cats, dogs, birds, etc.

[0090] Once the species of the organism is determined, the system will generate corresponding alarm information according to the preset rules. The alarm information may include detailed information such as the type, quantity, location, time, and recommended response measures.

[0091] The step S305 includes:

[0092] When the scene recognition result is that other animals have strayed in, based on the edge computing animal model, feature extraction and classification are performed on the abnormal signal data to obtain key information of the living organism;

[0093] The key information of the living organism is mapped to the corresponding species category through the edge computing animal model classifier, the species category of the living organism is obtained, and the corresponding alarm information is generated.

[0094] It should be noted that the system deploys an animal model on the edge device. This model can identify the characteristics of different animals based on deep learning technology and after being trained with a large number of animal images and videos.

[0095] It is understandable that the edge computing animal model extracts features from abnormal signal data, including key information such as the shape, color, texture, and movement trajectory of the animal. The extracted feature information is input into the classifier of the edge computing animal model, which classifies the living organisms based on the feature information and maps them to the corresponding species categories, such as cats, dogs, birds, rodents, etc.

[0096] For ease of understanding, refer to Figure 3 This invention is provided for illustration, but is not intended to limit the present application. Figure 3 This is the flow chart of the monitoring data fusion analysis of the application scenario, including the fusion analysis and processing flow of three scenarios: operation and maintenance personnel entering, illegal personnel breaking in, and other animals entering by mistake. The following example illustrates the triggering scenario:

[0097] 1. When the infrared detection device detects a signal change and there is a sign of a living being intruding, it will work with other infrared detection devices to calculate the approximate spatial position coordinates of the living being by analyzing the intensity and direction of change of the infrared radiation emitted by the object.

[0098] 2. Information Collection After the FSU obtains the spatial coordinate information of the living organism, it links the camera equipment to monitor and capture the target monitoring area. The captured pictures are analyzed through edge computing to determine whether the living organism is a human or an animal.

[0099] (1) If the life form is a human, the face is extracted for face recognition to determine whether it is an in-stock maintenance personnel.

[0100] a) If the intruder is not an in-house maintenance personnel, an alarm message will be generated and the image information of the illegal intruder will be reported to the platform.

[0101] b) If the person is an in-stock maintenance personnel, the maintenance information shall be recorded.

[0102] (2) If the life form is not a human, the algorithm model is called to analyze the species category of the life form and generate corresponding alarm information.

[0103] 3. Report the analysis results and accompanying alarm information of the information collection FSU to the platform.

[0104] This embodiment obtains real-time data through a signal collector based on a three-dimensional space model. When the abnormal signal data is consistent with the real-time data, the abnormal signal data is analyzed by edge computing through an image recognition algorithm to obtain a scene recognition result. When the scene recognition result is that operation and maintenance personnel have entered or illegal personnel have broken in, the facial information of the abnormal signal data is extracted, the facial information is recognized through an image recognition algorithm to obtain a recognition result, and corresponding information is output according to the recognition result. When the scene recognition result is that other animals have mistakenly entered, the species category of the life form is obtained by analyzing the abnormal signal data, and corresponding alarm information is generated, thereby realizing intelligent response to different scenes, effectively ensuring regional safety and order, and reducing false alarms and missed alarms.

[0105] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 4 , the step S20 may include steps S201 to S203:

[0106] Step S201: When the camera device and / or the infrared detection device detects a signal change, the signal change single monitoring area triggers the adjacent monitoring area.

[0107] It is understood that when the camera device and / or infrared detection device detects a signal change, the abnormal signal data is first sent to the associated single monitoring area processing unit, which analyzes the trigger signal to determine the type, location and severity of the signal change. If the signal change is confirmed to be abnormal (such as a person or animal mistakenly entering the machine room), the processing unit will generate a linkage request to trigger a response from the adjacent monitoring area.

[0108] The linkage request is sent to the processing units in the adjacent monitoring area, which will adjust the status of their monitoring equipment according to the preset rules and strategies, such as adjusting the focus and direction of the camera or activating the infrared detection equipment. At the same time, they can also trigger other security equipment, such as access control systems, alarms, etc., to provide additional security.

[0109] Step S202, based on the interactive identification between the PTZ camera device and the adjacent monitoring area, the spatial position of the signal change is determined by acquiring the infrared radiation intensity and change direction of the signal change.

[0110] It should be understood that the overall monitoring range can be determined by the camera equipment. The monitoring areas of each camera equipment radiate to each other, and interactive identification of nearby areas is carried out. Infrared detection and image algorithm recognition are superimposed, and the point is used to lead the whole. Relying on the variable monitoring area of ​​the pan-tilt camera equipment, the alarm triggered by a single monitoring area drives the joint monitoring of multiple monitoring areas, thereby realizing all-round monitoring of the computer room.

[0111] It should be understood that the PTZ camera equipment will automatically adjust its focal length, direction or viewing angle according to preset rules or algorithms, and make real-time adjustments based on the location and dynamic characteristics of the signal changes to ensure image clarity and coverage. When adjusting the focal length and direction, the PTZ camera equipment will capture the motion trajectory or direction of the signal changes. By analyzing these motion trajectories or directions, the system can determine the movement path of the signal changes in space, thereby locating its position more accurately.

[0112] It should be noted that the infrared detection equipment measures the infrared radiation intensity in the area where the signal changes. The infrared radiation intensity is a function of the object's temperature, so it can provide additional information about the signal change (such as the intruder's body temperature).

[0113] By combining the information on infrared radiation intensity and change direction, the position of the signal change in three-dimensional space can be calculated.

[0114] Step S203: Use the camera to photograph the spatial position to obtain an abnormal picture, and transmit the abnormal picture as abnormal signal data to the information collection FSU.

[0115] It should be understood that, according to the determined spatial position, the camera device will automatically adjust its focus, direction, viewing angle and other parameters to ensure that the position can be clearly photographed. After the camera device is adjusted to the right position, the shooting command is triggered to capture the image of the spatial position, which may contain specific features of the abnormal signal, such as the appearance of the intruder, the activity of the animal, etc. The abnormal image captured will be regarded as abnormal signal data, which contains visual information about the abnormal signal, and then the abnormal signal data (i.e., the abnormal image and its additional information) will be transmitted to the information acquisition FSU.

[0116] In this embodiment, when the camera device and / or the infrared detection device detects a signal change, the single monitoring area of ​​the signal change triggers the adjacent monitoring area. Based on the interactive recognition between the pan-tilt camera device and the adjacent monitoring area, the spatial position of the signal change is determined by obtaining the infrared radiation intensity and change direction of the signal change. The spatial position is photographed by the camera device to obtain an abnormal picture, and the abnormal picture is transmitted to the information collection FSU as abnormal signal data, thereby realizing a linkage effect, enhancing the sensitivity and accuracy of monitoring, and improving the speed and efficiency of emergency response.

[0117] In the third embodiment, step S10 may include:

[0118] Based on the camera equipment and infrared detection equipment layout points, the initial three-dimensional space model is constructed through the software built-in model;

[0119] or,

[0120] Based on the camera equipment layout points and the infrared detection equipment layout points, image data of different perspectives are acquired through the pan-tilt camera equipment, and an initial three-dimensional space model is constructed according to the image data;

[0121] The camera device and the infrared detection device are mapped to corresponding points of the initial three-dimensional space model to obtain a three-dimensional space model.

[0122] It is understandable that according to the characteristics and needs of the monitoring area, appropriate software built-in 3D space models are selected. These models may include preset elements such as buildings, terrain, and indoor layout. According to the actual layout point information, adjust the parameters (size, shape, position, etc.) of the software built-in model to ensure that the model is consistent with the actual situation. In the software, the adjusted built-in model is rendered into the initial 3D space model. In addition, the built-in commonly used 3D space model supports parameter modification, or you can use the built-in default model and manually drag and drop the device to the correct position of the model.

[0123] Alternatively, by controlling the pan-tilt camera equipment, the image data of the monitoring area is captured from multiple different perspectives, covering the entire monitoring area and including enough feature points for three-dimensional reconstruction. Then, the captured image data is processed, including feature extraction, matching, optimization and other steps. Using image processing software or three-dimensional modeling tools, an initial three-dimensional space model is constructed based on the processed image data.

[0124] According to the layout information of the camera equipment and infrared detection equipment, their specific positions in the three-dimensional space model are determined. In the three-dimensional space model, according to the determined mapping rules, the camera equipment and infrared detection equipment are mapped to the corresponding points, and the model of each device is marked. Then, the accuracy of the mapping results is verified to ensure that the positions of the camera equipment and infrared detection equipment in the three-dimensional space model are consistent with the actual layout points. After completing the mapping and adjustment, the final three-dimensional space model is generated.

[0125] This embodiment constructs an initial three-dimensional space model through the software built-in model based on the camera equipment layout points and the infrared detection equipment layout points, or, based on the camera equipment layout points and the infrared detection equipment layout points, obtains image data of different perspectives through the pan-tilt camera equipment, constructs the initial three-dimensional space model according to the image data, maps the camera equipment and the infrared detection equipment to the corresponding points of the initial three-dimensional space model, and obtains the three-dimensional space model, thereby improving the accuracy of spatial perception and the three-dimensionality of the monitoring system.

[0126] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the monitoring method of the present application based on the information collection FSU. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0127] This application also provides a monitoring device based on information collection FSU, please refer to Figure 5 , the monitoring device based on information collection FSU includes:

[0128] A model building module 10 is used to build a three-dimensional space model based on the camera equipment layout points and the infrared detection equipment layout points;

[0129] The data acquisition module 20 is used to acquire abnormal signal data through the information acquisition FSU when the camera device and / or the infrared detection device detects a signal change;

[0130] The monitoring and control module 30 is used to perform edge computing analysis on the abnormal signal data based on the three-dimensional space model through an image recognition algorithm to obtain a scene recognition result, and trigger a monitoring and control strategy according to the scene recognition result.

[0131] The monitoring device based on the information collection FSU provided by the present application adopts the monitoring method based on the information collection FSU in the above embodiment, which can solve the technical problem that the accuracy and stability of the monitoring data cannot be guaranteed due to the limitations of the linkage capability and computing capability of the traditional gateway device. Compared with the prior art, the beneficial effects of the monitoring device based on the information collection FSU provided by the present application are the same as the beneficial effects of the monitoring method based on the information collection FSU provided by the above embodiment, and the other technical features of the monitoring device based on the information collection FSU are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0132] The present application provides a monitoring device based on an information collection FSU, and the monitoring device based on the information collection FSU includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the monitoring method based on the information collection FSU in the above-mentioned embodiment 1.

[0133] Reference below Figure 6 , which shows a schematic diagram of the structure of a monitoring device based on information collection FSU suitable for implementing the embodiment of the present application. The monitoring device based on information collection FSU in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Desctions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The monitoring device based on the information collection FSU shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0134] like Figure 6As shown, the monitoring device based on the information acquisition FSU may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the monitoring system based on the information acquisition FSU are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the monitoring device based on the information acquisition FSU to communicate with other systems wirelessly or by wire to exchange data. Although the figure shows a monitoring device based on the information acquisition FSU with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0135] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0136] The monitoring device based on the information collection FSU provided by the present application adopts the monitoring method based on the information collection FSU in the above embodiment, which can solve the technical problem that the accuracy and stability of the monitoring data cannot be guaranteed due to the limitations of the linkage ability and computing ability of the traditional gateway device. Compared with the prior art, the beneficial effects of the monitoring device based on the information collection FSU provided by the present application are the same as the beneficial effects of the monitoring method based on the information collection FSU provided by the above embodiment, and the other technical features of the monitoring device based on the information collection FSU are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0137] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0138] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0139] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the monitoring method based on the information collection FSU in the above embodiment.

[0140] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0141] The computer-readable storage medium may be included in the monitoring device based on the information collection FSU; or may exist independently without being assembled into the monitoring device based on the information collection FSU.

[0142] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the monitoring device based on the information collection FSU, the monitoring device based on the information collection FSU: constructs a three-dimensional space model based on the layout of points of the camera device and the layout of points of the infrared detection device, and when the camera device and / or the infrared detection device detects a signal change, obtains abnormal signal data through the information collection FSU, and based on the three-dimensional space model, performs edge computing analysis on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result, and triggers a monitoring control strategy according to the scene recognition result.

[0143] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0144] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0145] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0146] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned monitoring method based on the information collection FSU, and can solve the technical problem that the accuracy and stability of the monitoring data cannot be guaranteed due to the limitations of the linkage capability and computing capability of traditional gateway devices. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the monitoring method based on the information collection FSU provided by the above-mentioned embodiment, and will not be repeated here.

[0147] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned monitoring method based on the information collection FSU when executed by a processor.

[0148] The computer program product provided by the present application can solve the technical problem that the accuracy and stability of monitoring data cannot be guaranteed due to the limitations of the linkage capability and computing capability of traditional gateway devices. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the monitoring method based on the information collection FSU provided in the above embodiment, which will not be repeated here.

[0149] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A monitoring method based on information collection FSU, characterized in that: The method comprises the following steps: Construct a three-dimensional space model based on the camera equipment and infrared detection equipment layout points; When the camera device and / or infrared detection device detects a signal change, the abnormal signal data is acquired through the information acquisition FSU; Based on the three-dimensional space model, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result, and a monitoring and control strategy is triggered according to the scene recognition result.

2. The monitoring method based on the information collection FSU according to claim 1, characterized in that: The scene recognition results include the entry of maintenance personnel, illegal intrusion of personnel and other animals entering by mistake. Based on the three-dimensional space model, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain the scene recognition result, and the steps of triggering the monitoring control strategy according to the scene recognition result include: Based on the three-dimensional space model, real-time data is acquired through the signal acquisition FSU; When the abnormal signal data is consistent with the real-time data, edge computing analysis is performed on the abnormal signal data through an image recognition algorithm to obtain a scene recognition result; When the scene recognition result is that the operation and maintenance personnel enter or an illegal person breaks in, extracting the facial information of the abnormal signal data; Recognize the facial information through an image recognition algorithm to obtain a recognition result, and output corresponding information according to the recognition result; When the scene recognition result is that other animals have strayed in, the species category of the life form is obtained by analyzing the abnormal signal data, and corresponding alarm information is generated.

3. The monitoring method based on the information collection FSU according to claim 2, characterized in that: The step of identifying the face information by an image recognition algorithm, obtaining a recognition result, and outputting corresponding information according to the recognition result comprises: Recognize the facial information through an image recognition algorithm to obtain a recognition result; When the recognition result is an illegal person, a corresponding alarm message is generated and the facial information is output; When the identification result is an operation and maintenance personnel, the identification result is output.

4. The monitoring method based on the information collection FSU according to claim 2, characterized in that: When the scene recognition result is that other animals have strayed in, the step of obtaining the species category of the living being by analyzing the abnormal signal data and generating corresponding alarm information includes: When the scene recognition result is that other animals have strayed in, based on the edge computing animal model, feature extraction and classification are performed on the abnormal signal data to obtain key information of the living organism; The key information of the living organism is mapped to the corresponding species category through the edge computing animal model classifier, the species category of the living organism is obtained, and the corresponding alarm information is generated.

5. The monitoring method based on the information collection FSU according to any one of claims 1 to 4, characterized in that: The step of acquiring abnormal signal data through the information acquisition FSU when the camera device and / or the infrared detection device detects a signal change includes: When the camera device and / or infrared detection device detects a signal change, the signal change single monitoring area triggers the adjacent monitoring area; Based on the interactive identification between the PTZ camera device and the adjacent monitoring area, the spatial position of the signal change is determined by acquiring the infrared radiation intensity and change direction of the signal change; The spatial position is photographed by the camera device to obtain an abnormal picture, and the abnormal picture is transmitted to the information collection FSU as abnormal signal data.

6. The monitoring method based on the information collection FSU according to any one of claims 1 to 4, characterized in that: The step of constructing a three-dimensional space model based on the camera equipment and the infrared detection equipment comprises: Based on the camera equipment and infrared detection equipment layout points, the initial three-dimensional space model is constructed through the software built-in model; or, Based on the camera equipment layout points and the infrared detection equipment layout points, image data of different perspectives are acquired through the pan-tilt camera equipment, and an initial three-dimensional space model is constructed according to the image data; The camera device and the infrared detection device are mapped to corresponding points of the initial three-dimensional space model to obtain a three-dimensional space model.

7. A monitoring system based on information collection FSU, characterized in that: The monitoring system based on the information acquisition FSU includes: a camera device, an infrared detection device and an information acquisition FSU; The camera device and the infrared detection device are both connected to the information collection FSU.

8. A monitoring device based on information collection FSU, characterized in that: The monitoring device based on the information collection FSU includes: A model building module is used to build a three-dimensional space model based on the camera equipment and infrared detection equipment. A data acquisition module, used to acquire abnormal signal data through the information acquisition FSU when the camera device and / or the infrared detection device detects a signal change; The monitoring and control module is used to perform edge computing analysis on the abnormal signal data based on the three-dimensional space model through an image recognition algorithm to obtain a scene recognition result, and trigger a monitoring and control strategy according to the scene recognition result.

9. A monitoring device based on information collection FSU, characterized in that: The monitoring device based on the information collection FSU includes: a memory, a processor, and a monitoring program based on the information collection FSU stored in the memory and executable on the processor. When the monitoring program based on the information collection FSU is executed by the processor, the monitoring method based on the information collection FSU as described in any one of claims 1 to 6 is implemented.

10. A storage medium, characterized in that: The storage medium stores a monitoring program based on the information collection FSU. When the monitoring program based on the information collection FSU is executed by the processor, the monitoring method based on the information collection FSU according to any one of claims 1 to 6 is implemented.

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