Power operation safety monitoring method, device, equipment, storage medium and product
Through intelligent analysis and real-time processing of monitoring data at the power operation site, the problem of traditional monitoring equipment lacking intelligent recognition capabilities is solved, and efficient safety monitoring of the power operation site is achieved, and safety is improved.
Patent Information
- Application Number
- CN202411804629.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-03-18
AI Technical Summary
Traditional power operation monitoring equipment lacks intelligent identification capabilities, and it is difficult to identify and stop violations in a timely manner, resulting in lagging handling of safety hazards.
Provide a power operation safety monitoring method, by obtaining monitoring data (image data and environmental parameter data) of the target area, determining the processing method according to the data type, performing object detection and behavioral analysis, and generating alarm prompt information.
The safety of the power operation site has been improved. Through intelligent analysis and real-time processing of monitoring data, violations can be identified and dealt with in a timely manner, and safety hazards can be reduced.
Smart Images
Figure CN119649458A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method, device, equipment, storage medium and product for monitoring power operation safety. Background Art
[0002] Due to its high-risk nature, safety monitoring of power operations has always attracted much attention.
[0003] Although traditional monitoring equipment, such as law enforcement devices and surveillance balls, can realize video surveillance, they generally lack intelligent recognition capabilities, making it difficult to identify and stop violations in a timely manner, and the handling of safety hazards is delayed.
[0004] Based on the above reasons, in the field of power operations, there is an urgent need to provide a method that can monitor the operation site and analyze the monitoring data at the same time, so as to improve the safety of the power operation site as much as possible. Summary of the invention
[0005] Based on this, it is necessary to provide a method, device, equipment, storage medium and product for power operation safety monitoring that can improve the safety of power operation sites in response to the above technical problems.
[0006] In a first aspect, the present application provides a method for monitoring power operation safety, comprising:
[0007] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0008] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0009] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0010] In one embodiment, determining a target processing method corresponding to the monitoring data according to the data type of the monitoring data includes:
[0011] In the case where the monitoring data is image data, determining that the target processing method corresponding to the monitoring data is a target detection method;
[0012] In the case where the monitoring data is environmental parameter data, it is determined that the target processing method corresponding to the monitoring data is a threshold comparison method.
[0013] In one embodiment, when the monitoring data is image data, the monitoring data is processed based on the target processing method to obtain the monitoring result of the target area at the current moment, including:
[0014] Input the image data into the target detection model to obtain the target detection result;
[0015] When the target detection result indicates that the target object exists in the image data, a behavior detection is performed on the target object to obtain a behavior detection result;
[0016] When the behavior detection result indicates that the target object has the target behavior, the monitoring result of the target area at the current moment is determined as the first monitoring result.
[0017] In one embodiment, the method further comprises:
[0018] When the target detection result indicates that there is no target object in the image data, determining the monitoring result of the target area at the current moment as the second monitoring result; or
[0019] When the target detection result indicates that there is a target object in the image data and the target object does not have a target behavior, determining that the monitoring result of the target area at the current moment is a second monitoring result;
[0020] Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0021] In one embodiment, when the monitoring data is environmental parameter data, the monitoring data is processed based on the target processing method to obtain the monitoring result of the target area at the current moment, including:
[0022] Determine the monitoring result of the target area at the current moment according to the size relationship between the environmental parameter data and the corresponding preset threshold;
[0023] The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0024] In one embodiment, the method further comprises:
[0025] Generate warning information based on the identification information of the target object.
[0026] In a second aspect, the present application also provides a power operation safety monitoring device, comprising:
[0027] A data acquisition module, used to acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0028] A method determination module is used to determine a target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0029] The data processing module is used to process the monitoring data based on the target processing method to obtain the monitoring result of the target area at the current moment.
[0030] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:
[0031] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0032] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0033] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:
[0035] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0036] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0037] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0038] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:
[0039] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0040] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0041] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0042] The above-mentioned power operation safety monitoring method, device, equipment, storage medium and product obtain the monitoring data of the target area at the current moment, and determine different target processing methods according to different data types when the data types of the monitoring data are different. Then, according to the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment. In the above process, different processing methods are used for different types of monitoring data to obtain the monitoring result of the target area at the current moment, so that the monitoring result is more accurate, thereby improving the safety of the target area. BRIEF DESCRIPTION OF THE DRAWINGS
[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0044] Figure 1 A diagram showing an application environment of a method for monitoring power operation safety in an embodiment;
[0045] Figure 2 A schematic diagram of a flow chart of a method for monitoring power operation safety in one embodiment;
[0046] Figure 3 A schematic flow chart of a monitoring result determination step in one embodiment;
[0047] Figure 4 A schematic flow chart of a monitoring result determination step in another embodiment;
[0048] Figure 5A is an application environment diagram of a method for monitoring power operation safety in another embodiment;
[0049] Figure 5B A schematic diagram of a flow chart of a method for monitoring power operation safety in another embodiment;
[0050] Figure 6 is a structural block diagram of a power operation safety monitoring device in one embodiment;
[0051] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION
[0052] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0053] The power operation safety monitoring method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the power operation safety monitoring device 10 includes a front-end monitoring module 102 and an intelligent analysis module 104, the front-end monitoring module 102 is connected to the intelligent analysis module 104, and the embodiment of the present application is applied to the intelligent analysis module 104. Specifically, the intelligent analysis module 104 obtains the monitoring data of the target area sent by the front-end monitoring module 102 at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data; the intelligent analysis module 104 determines the target processing method corresponding to the monitoring data according to the data type of the monitoring data; the intelligent analysis module 104 processes the monitoring data based on the target processing method, and obtains the monitoring result of the target area at the current moment. Among them, the front-end monitoring module 102 may include an image acquisition device and an environmental data acquisition device, for example, it may include a camera and a sensor.
[0054] In an exemplary embodiment, Figure 2 As shown, a method for monitoring the safety of power operations is provided. Figure 1 Taking the intelligent analysis module 104 in FIG. 1 as an example, the method includes the following steps:
[0055] S210, obtaining monitoring data of the target area at the current moment.
[0056] The target area may be a part of the power operation site. The monitoring data includes at least one of image data and environmental parameter data; the environmental parameter data may be data collected by a sensor and used to describe the environmental information of the target area; the image data may be collected by a sensor or a camera, and there is no limitation on this.
[0057] Exemplarily, the monitoring data may be collected by a monitoring device and transmitted to the intelligent analysis module in real time, wherein the monitoring device may be a camera or a sensor.
[0058] S220: Determine a target processing method corresponding to the monitoring data according to the data type of the monitoring data.
[0059] The target processing method is the method for processing the monitoring data.
[0060] Exemplarily, the correspondence between reference data and reference processing methods may be predetermined, and the reference processing method corresponding to the monitoring data in the correspondence may be used as the target processing method corresponding to the monitoring data.
[0061] Exemplarily, the monitoring data may also be input into a pre-trained processing method determination model to obtain a target processing method corresponding to the monitoring data. The processing method determination model may be constructed based on a common neural network, which will not be described in detail here.
[0062] S230, based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0063] Exemplarily, when the monitoring data is image data, the target processing method corresponding to the monitoring data is determined to be a target detection method. For example, the image data is input into a target detection model to obtain a target detection result, and the monitoring result of the target area at the current moment is determined based on the target detection result.
[0064] Exemplarily, when the monitoring data is environmental parameter data, the target processing method corresponding to the monitoring data is determined to be a threshold comparison method. For example, the environmental parameter data is compared with a predetermined parameter threshold, and the monitoring result of the target area at the current moment is determined based on the comparison result between the two.
[0065] In the above-mentioned power operation safety monitoring method, by obtaining the monitoring data of the target area at the current moment, when the data type of the monitoring data is different, different target processing methods are determined according to different data types. Then, according to the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment. In the above process, different processing methods are used for different types of monitoring data to obtain the monitoring result of the target area at the current moment, so that the monitoring result is more accurate, thereby improving the safety of the target area.
[0066] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, when the monitoring data is image data, the above target-based processing method is used to process the monitoring data to obtain the specific process of the monitoring result of the target area at the current moment.
[0067] See also Figure 3 The steps for determining the monitoring results shown include:
[0068] S310, input the image data into the target detection model to obtain the target detection result.
[0069] The target detection model may be a model based on a common neural network, which is used to process image data and output a target detection result. The target detection result is used to characterize whether a target object exists in the image data. The target object may be a staff member.
[0070] It should be noted that in the process of training the target detection model, the sample image data can be inserted into the target detection model to obtain the prediction result of the target object existence, and then the model parameters of the target detection model can be adjusted according to the prediction result and the existence label corresponding to the sample image data to improve the model accuracy of the target detection model.
[0071] Furthermore, in order to regulate the target user's operation in the target area, the target detection result can also be used to characterize whether the target object exists in the image data, and if the target object exists, whether the target object operates in a standardized manner, for example, whether the target object wears a helmet, work clothes, and a safety belt.
[0072] Optionally, in order to improve the accuracy of the target detection results, the image data may be preprocessed before being input into the target detection model, for example, by denoising or enhancing the image to improve the image quality for subsequent analysis.
[0073] S320: When the target detection result indicates that there is a target object in the image data, a behavior detection is performed on the target object to obtain a behavior detection result.
[0074] The behavior detection result is used to characterize whether the target object has a target behavior. The target behavior mainly refers to some behaviors that are not allowed to appear in the target area, such as smoking, making phone calls, crossing the line, etc.
[0075] Exemplarily, the image data may be input into a behavior detection model to obtain a behavior detection result of the target object.
[0076] Exemplarily, a plurality of behavior templates may be predetermined, and the matching between the behavior of the target object and each behavior template may be determined. If the matching is successful, it may be determined that the target object has the corresponding target behavior.
[0077] S330: When the behavior detection result indicates that the target object has the target behavior, determine that the monitoring result of the target area at the current moment is the first monitoring result.
[0078] Furthermore, warning information is generated according to the identification information of the target object.
[0079] The identification information of the target object may be the account information of the target object. Specifically, when the target object has the target behavior, an alarm prompt information for reminding the target object to pay attention to safety is generated and output to the target object.
[0080] In addition, in order to enhance the warning effect of the alarm prompt information, on-site prompts can also be given through on-site audio, indicator lights, etc. For the convenience of management, the alarm prompt information can also be output to the terminal of the manager, such as a mobile phone and a computer, so that the manager can view the violation.
[0081] S340: When the target object does not have the target behavior, determine that the monitoring result of the target area at the current moment is the second monitoring result.
[0082] S350: When the target detection result indicates that the target object does not exist in the image data, determine that the monitoring result of the target area at the current moment is a second monitoring result.
[0083] Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0084] In the above embodiment, when the monitoring data is image data, the monitoring data is processed based on the target processing method to obtain a specific method of monitoring the target area at the current moment, and corresponding responses are made for different monitoring results to improve the safety of the target area.
[0085] Optionally, the image data may be input into a monitoring result determination model to obtain a monitoring result. Exemplarily, a convolutional neural network model in deep learning is used to perform target detection on the preprocessed image to obtain at least one of a target category, a target position, and a corresponding confidence level.
[0086] Among them, the target category includes: which category the target belongs to, such as "safety helmet", "work clothes", etc.; the target position includes: the exact position of the target in the image, which can be represented by a bounding box, including the coordinates and size of the bounding box; the confidence includes: the credibility of the detection result, that is, the probability that the model believes that the identified target belongs to this category.
[0087] Among them, the monitoring result determination model is trained with a large amount of labeled data, and can accurately identify key targets such as target objects (i.e. workers), safety helmets, work clothes, safety belts, etc. in the image. During the detection process, the model will output the category, location (usually represented by a bounding box) and confidence level (indicating the model's confidence in the detection result of the target) of each target. On the basis of target detection, the behavior of the staff is further analyzed. By extracting the motion trajectory, posture changes and other features of the target (such as the operator), it is compared with the preset violation behavior template. The violation behavior template is usually constructed based on historical data and contains feature descriptions of various violations. During the comparison process, similarity calculation, machine learning classifiers and other methods are used to determine whether the operator has committed violations such as smoking, making phone calls, crossing the line and crossing the boundary.
[0088] Furthermore, when the monitoring results characterize and identify the violation, an alarm message is generated. The alarm message includes the type of violation, the specific location (indicated by the bounding box or coordinates in the image), the time of occurrence and other detailed information. At the same time, different alarm message methods (such as on-site sound, indicator light, mobile phone push, etc.) can be used to push the alarm message to managers and staff in real time according to the urgency of the alarm message.
[0089] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the above Qingtian target processing method is provided to process the monitoring data when the monitoring data is environmental parameter data, and obtain the specific process of the monitoring result of the target area at the current moment.
[0090] See also Figure 4 The steps for determining the monitoring results shown include:
[0091] S410, determining the monitoring result of the target area at the current moment according to the size relationship between the environmental parameter data and the corresponding preset threshold value.
[0092] The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0093] Exemplarily, if the upper temperature limit of the target area is a, when the temperature data represented by the environmental reference data exceeds a, the monitoring result is determined to be the first monitoring result; when it does not exceed a, the monitoring result is determined to be the second monitoring result.
[0094] Exemplarily, if the upper pressure limit of the target area is b, when the environmental reference data represents that the environmental data exceeds b, the monitoring result is determined to be the first monitoring result; when it does not exceed b, the monitoring result is determined to be the second monitoring result.
[0095] In the above embodiment, the above-mentioned Qingtian target processing method is given to process the monitoring data when the monitoring data is environmental parameter data to obtain a specific method of the monitoring result of the target area at the current moment. Based on the threshold comparison method, the process of determining the monitoring result is simpler and faster.
[0096] Furthermore, in order to achieve long-term preservation and effective management of monitoring data, the present application also provides data management and storage functions. Specifically including: Database design: Database structure, used to store monitoring data, alarm information, user information and other data to ensure data integrity and queryability. Data backup and recovery: Back up the database regularly to prevent data loss. At the same time, provide data recovery function to ensure rapid recovery when data is damaged or lost. Data analysis and mining: Use data analysis tools to conduct in-depth mining of stored monitoring data to extract valuable information and rules. Provide strong support for decision-making on safe management of power operations. Security protection: Strengthen the system's security protection measures to prevent security issues such as attacks and data leaks.
[0097] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the power operation safety monitoring method provided by the present application is applied to Figure 5A Taking the application environment shown as an example, the power operation safety monitoring method provided in this application is introduced in detail.
[0098] See also Figure 5B The power operation safety monitoring method shown is described by applying the method to a power operation safety monitoring device, and includes:
[0099] S510, the front-end monitoring module outputs the collected image data and environmental parameter data to the data transmission module;
[0100] S520, the data transmission module encrypts the received monitoring data to obtain encrypted data;
[0101] S530, the data transmission module transmits the encrypted data to the intelligent analysis module;
[0102] S540, the intelligent analysis module decrypts the encrypted data and preprocesses the decrypted image data to obtain preprocessed image data;
[0103] Among them, data preprocessing includes at least one of data cleaning (removing noise, duplicate data, etc.), data conversion (converting raw data into a format that is convenient for subsequent analysis and processing), etc.;
[0104] Exemplarily, Gaussian filtering and histogram equalization image processing techniques may be used to perform pre-processing operations such as denoising and enhancement on the received image.
[0105] The Gaussian filter formula is:
[0106] ;
[0107] Where (x, y) is the image pixel coordinate, is the standard deviation, which is used to control the degree of filtering. Histogram equalization adjusts the histogram distribution of the image to make the image contrast more uniform, which is convenient for subsequent analysis.
[0108] S550, the intelligent analysis module performs target detection on the preprocessed image data to obtain a target detection result;
[0109] S560, when the target detection result indicates that there is a target object in the image data, the intelligent analysis module performs behavior detection on the image data to obtain a behavior detection result;
[0110] S570, when the behavior detection result indicates that the target object has the target behavior, the intelligent analysis module generates an alarm prompt information and outputs the alarm prompt information to the user interaction module;
[0111] S580, the user interaction module outputs the warning prompt information to the target object.
[0112] It should be noted that in order to make the monitoring data more comprehensive, in this application, during the installation of the monitoring equipment, it is necessary to ensure that the camera or sensor can fully cover the key areas in the target area without blind spots, and adjust the camera's focus, exposure and other parameters to obtain the best image quality. After the installation is completed, necessary scheduling and calibration are carried out to ensure the stable operation of the entire system.
[0113] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
[0114] Based on the same inventive concept, the embodiment of the present application also provides a power operation safety monitoring device for implementing the power operation safety monitoring method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more power operation safety monitoring device embodiments provided below can refer to the limitations of the power operation safety monitoring method above, and will not be repeated here.
[0115] In an exemplary embodiment, Figure 6As shown, a power operation safety monitoring device is provided, including: a data acquisition module 610, a mode determination module 620 and a data processing module 630, wherein:
[0116] The data acquisition module 610 is used to acquire the monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0117] A method determination module 620 is used to determine a target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0118] The data processing module 630 is used to process the monitoring data based on the target processing method to obtain the monitoring result of the target area at the current moment.
[0119] In one embodiment, the method determination module 620 includes a first determination unit for determining that the target processing method corresponding to the monitoring data is a target detection method when the monitoring data is image data; and a second determination unit for determining that the target processing method corresponding to the monitoring data is a threshold comparison method when the monitoring data is environmental parameter data.
[0120] In one embodiment, when the monitoring data is image data, the data processing module 630 includes a first processing unit for inputting the image data into a target detection model to obtain a target detection result; a second processing unit for performing behavior detection on the target object to obtain a behavior detection result when the target detection result indicates that there is a target object in the image data; and a third determination unit for determining that the monitoring result of the target area at the current moment is a first monitoring result when the behavior detection result indicates that there is a target behavior in the target object.
[0121] In one embodiment, the data processing module 630 also includes a fourth determination unit for determining that the monitoring result of the target area at the current moment is the second monitoring result when there is no target object in the image data represented by the target detection result; or, a fifth determination unit for determining that the monitoring result of the target area at the current moment is the second monitoring result when there is a target object in the image data represented by the target detection result and there is no target behavior of the target object; wherein the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0122] In one embodiment, when the monitoring data is environmental parameter data, the data processing module 630 is specifically used to determine the monitoring result of the target area at the current moment based on the size relationship between the environmental parameter data and the corresponding preset threshold; wherein the environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0123] In one embodiment, the data processing module further includes an information generating unit, which is used to generate warning prompt information according to the identification information of the target object.
[0124] Each module in the above-mentioned power operation safety monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.
[0125] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for monitoring the safety of power operations is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.
[0126] Those skilled in the art will understand that Figure 7The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0127] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:
[0128] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0129] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0130] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0131] In one embodiment, when the processor executes the computer program, the following steps are also implemented:
[0132] In the case where the monitoring data is image data, determining that the target processing method corresponding to the monitoring data is a target detection method;
[0133] In the case where the monitoring data is environmental parameter data, it is determined that the target processing method corresponding to the monitoring data is a threshold comparison method.
[0134] In one embodiment, when the processor executes the computer program, the following steps are also implemented:
[0135] Input the image data into the target detection model to obtain the target detection result;
[0136] When the target detection result indicates that the target object exists in the image data, a behavior detection is performed on the target object to obtain a behavior detection result;
[0137] When the behavior detection result indicates that the target object has the target behavior, the monitoring result of the target area at the current moment is determined as the first monitoring result.
[0138] In one embodiment, when the processor executes the computer program, the following steps are also implemented:
[0139] When the target detection result indicates that there is no target object in the image data, determining the monitoring result of the target area at the current moment as the second monitoring result; or
[0140] When the target detection result indicates that there is a target object in the image data and the target object does not have a target behavior, determining that the monitoring result of the target area at the current moment is a second monitoring result;
[0141] Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0142] In one embodiment, when the processor executes the computer program, the following steps are also implemented:
[0143] Determine the monitoring result of the target area at the current moment according to the size relationship between the environmental parameter data and the corresponding preset threshold;
[0144] The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0145] In one embodiment, when the processor executes the computer program, the following steps are also implemented:
[0146] Generate warning information based on the identification information of the target object.
[0147] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
[0148] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0149] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0150] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0151] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0152] In the case where the monitoring data is image data, determining that the target processing method corresponding to the monitoring data is a target detection method;
[0153] In the case where the monitoring data is environmental parameter data, it is determined that the target processing method corresponding to the monitoring data is a threshold comparison method.
[0154] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0155] Input the image data into the target detection model to obtain the target detection result;
[0156] When the target detection result indicates that the target object exists in the image data, a behavior detection is performed on the target object to obtain a behavior detection result;
[0157] When the behavior detection result indicates that the target object has the target behavior, the monitoring result of the target area at the current moment is determined as the first monitoring result.
[0158] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0159] When the target detection result indicates that there is no target object in the image data, determining the monitoring result of the target area at the current moment as the second monitoring result; or
[0160] When the target detection result indicates that there is a target object in the image data and the target object does not have a target behavior, determining that the monitoring result of the target area at the current moment is a second monitoring result;
[0161] Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0162] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0163] Determine the monitoring result of the target area at the current moment according to the size relationship between the environmental parameter data and the corresponding preset threshold;
[0164] The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0165] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0166] Generate warning information based on the identification information of the target object.
[0167] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:
[0168] Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data;
[0169] Determine the target processing method corresponding to the monitoring data according to the data type of the monitoring data;
[0170] Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
[0171] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0172] In the case where the monitoring data is image data, determining that the target processing method corresponding to the monitoring data is a target detection method;
[0173] In the case where the monitoring data is environmental parameter data, it is determined that the target processing method corresponding to the monitoring data is a threshold comparison method.
[0174] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0175] Input the image data into the target detection model to obtain the target detection result;
[0176] When the target detection result indicates that the target object exists in the image data, a behavior detection is performed on the target object to obtain a behavior detection result;
[0177] When the behavior detection result indicates that the target object has the target behavior, the monitoring result of the target area at the current moment is determined as the first monitoring result.
[0178] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0179] When the target detection result indicates that there is no target object in the image data, determining the monitoring result of the target area at the current moment as the second monitoring result; or
[0180] When the target detection result indicates that there is a target object in the image data and the target object does not have a target behavior, determining that the monitoring result of the target area at the current moment is a second monitoring result;
[0181] Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
[0182] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0183] Determine the monitoring result of the target area at the current moment according to the size relationship between the environmental parameter data and the corresponding preset threshold;
[0184] The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
[0185] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:
[0186] Generate warning information based on the identification information of the target object.
[0187] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0188] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.
[0189] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0190] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for monitoring power operation safety, characterized in that: The method comprises: Acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data; Determine, according to the data type of the monitoring data, a target processing method corresponding to the monitoring data; Based on the target processing method, the monitoring data is processed to obtain the monitoring result of the target area at the current moment.
2. The method according to claim 1, characterized in that The determining, according to the data type of the monitoring data, a target processing method corresponding to the monitoring data includes: In the case where the monitoring data is image data, determining that the target processing mode corresponding to the monitoring data is a target detection mode; In the case where the monitoring data is environmental parameter data, it is determined that the target processing method corresponding to the monitoring data is a threshold comparison method.
3. The method according to claim 2, characterized in that In the case where the monitoring data is image data, the monitoring data is processed based on the target processing mode to obtain the monitoring result of the target area at the current moment, including: Inputting the image data into a target detection model to obtain a target detection result; When the target detection result indicates that a target object exists in the image data, performing behavior detection on the target object to obtain a behavior detection result; In a case where the behavior detection result indicates that the target object has the target behavior, the monitoring result of the target area at the current moment is determined to be the first monitoring result.
4. The method according to claim 3, characterized in that The method further comprises: In a case where the target detection result indicates that there is no target object in the image data, determining that the monitoring result of the target area at the current moment is a second monitoring result; or, When the target detection result indicates that there is a target object in the image data and the target object does not have a target behavior, determining that the monitoring result of the target area at the current moment is a second monitoring result; Among them, the safety factor corresponding to the second monitoring result is higher than the safety factor corresponding to the first monitoring result.
5. The method according to claim 2, characterized in that: In the case where the monitoring data is environmental parameter data, the monitoring data is processed based on the target processing mode to obtain the monitoring result of the target area at the current moment, including: Determine the monitoring result of the target area at the current moment according to the magnitude relationship between the environmental parameter data and the corresponding preset threshold value; The environmental parameter data includes at least one of temperature data, humidity data, pressure data and noise data; different environmental parameter data correspond to different preset thresholds.
6. The method according to claim 3, characterized in that The method further comprises: Generate warning information according to the identification information of the target object.
7. A power operation safety monitoring device, characterized in that: The device comprises: A data acquisition module, used to acquire monitoring data of the target area at the current moment; wherein the monitoring data includes at least one of image data and environmental parameter data; A method determination module, used to determine a target processing method corresponding to the monitoring data according to the data type of the monitoring data; The data processing module is used to process the monitoring data based on the target processing method to obtain the monitoring result of the target area at the current moment.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.