AOV camera control method, controller, medium and product

Abstract

The embodiment of the invention provides an AOV camera control method, a controller, a medium and a product, and is applied to the field of cameras, and the method comprises the steps: obtaining a timestamp triggered by a target behavior and / or a target alarm event, carrying out the construction of a thermodynamic diagram according to the timestamp and a plurality of preset time periods, and obtaining a behavior thermodynamic diagram; performing time period extraction according to the behavior thermodynamic diagram to obtain a predicted activity time period; in a first preset period, obtaining the probability of occurrence of the target behavior and / or the target alarm event in the predicted activity period, and determining the credible state of the predicted activity period according to the probability; and obtaining the current electric quantity of the AOV camera, and controlling the working state of the AOV camera according to the credible state and / or the current electric quantity. According to the embodiment of the invention, the working state of the AOV camera can be controlled by predicting the credible state of the activity period and the current electric quantity, so that the dynamic balance between low-power-consumption operation and user experience can be realized.

Description

Technical Field

[0001] The present application relates to the field of camera technology, and in particular to a control method, controller, medium and product of an AOV camera. Background Art

[0002] In related technologies, always-on video (AOV) cameras generally employ a timed sleep mechanism to optimize power consumption and battery life. This mechanism periodically shuts down the main control chip and wireless communication module, maintaining only a basic heartbeat connection with the server. Upon detecting an environmental event or a user's active access, the device awakens from sleep to respond. While this passive energy-saving design effectively extends device battery life, it can result in a response delay of several seconds when a user initiates a remote viewing request, creating a bottleneck for interactive scenarios with high real-time requirements. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems existing in the prior art. To this end, this application proposes a control method, controller, medium and product for an AOV camera, aiming to achieve a dynamic balance between low power consumption operation and user experience.

[0004] In a first aspect, an embodiment of the present application provides a control method for an AOV camera, which is applied to an AOV camera. The method includes: Obtaining a timestamp of a target behavior and / or a target alarm event being triggered, and constructing a heat map based on the timestamp and a plurality of preset time periods to obtain a behavior heat map; Extracting time periods based on the behavior heat map to obtain predicted activity periods; Within a first preset period, obtaining a probability of a target behavior and / or a target alarm event occurring during the predicted activity period, and determining a credibility state of the predicted activity period based on the probability; The current power level of the AOV camera is obtained, and the working state of the AOV camera is controlled according to the trusted state and / or the current power level.

[0005] According to some embodiments of the present application, constructing a heat map based on the timestamp and multiple preset time periods to obtain a behavior heat map includes: Dividing the second preset period into equally spaced time periods to obtain a plurality of the preset time periods; The number of times the timestamp occurs in each of the preset time periods is counted, and a heat map is constructed according to each of the times and each of the preset time periods to obtain a behavior heat map.

[0006] According to some embodiments of the present application, extracting time periods based on the behavior heat map to obtain predicted activity periods includes: Calculating an average of each of the times to obtain an average number of times; Time periods are extracted based on the behavior heat map and each of the times to obtain the preset number of time periods with times higher than the average number, and the preset time periods are determined as predicted activity periods.

[0007] According to some embodiments of the present application, determining the credibility of the predicted activity period based on the probability includes one of the following: When the probability is greater than a preset probability threshold, determining that the credibility state of the predicted activity period is credible; When the probability is less than or equal to the preset probability threshold, the credibility state of the predicted activity period is determined to be untrustworthy.

[0008] According to some embodiments of the present application, controlling the working state of the AOV camera according to the trusted state and / or the current power includes one of the following: When the credible state of the predicted activity period is credible and the current power level is greater than or equal to a preset power threshold, controlling the AOV camera to be in a working state; When the credible state of the predicted activity period is credible and the current power level is less than the preset power threshold, controlling the AOV camera to be in a dormant state; When the credible state of the predicted activity period is uncredible, the AOV camera is controlled to be in a dormant state.

[0009] According to some embodiments of the present application, the method includes: Within a third preset period, obtaining a hit rate of target behavior and / or target alarm event occurring during the predicted activity period in which the trustworthy status is trustworthy; The trust state is adjusted according to the hit rate to be a trust state of the predicted activity period that is trustworthy.

[0010] According to some embodiments of the present application, adjusting the trust state to a trust state of the predicted activity period that is trustworthy according to the hit rate includes: When the hit rate is greater than or equal to a preset hit rate threshold, maintaining the credibility of the predicted activity period as credible; When the hit rate is less than a preset hit rate threshold, the credibility status of the predicted activity period is adjusted from credible to uncredible.

[0011] In a second aspect, an embodiment of the present application provides a controller comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the control method of the AOV camera of the first aspect described above when executing the computer program.

[0012] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the control method of the AOV camera as described in the first aspect above.

[0013] In a fourth aspect, an embodiment of the present application provides a computer program product, comprising a computer program or computer instructions, characterized in that the computer program or the computer instructions are stored in a computer-readable storage medium, a processor of a computer device reads the computer program or the computer instructions from the computer-readable storage medium, and the processor executes the computer program or the computer instructions, so that the computer device performs the control method of the AOV camera as described in the first aspect above.

[0014] According to the technical solution of the embodiment of the present application, there are at least the following beneficial effects: The embodiment of the present application proposes a control method, controller, medium and product for an AOV camera, the method comprising: obtaining the timestamp of the triggering of the target behavior and / or target alarm event, constructing a heat map based on the timestamp and multiple preset time periods to obtain a behavior heat map; extracting time periods based on the behavior heat map to obtain a predicted activity period; within a first preset cycle, obtaining the probability of the target behavior and / or target alarm event occurring during the predicted activity period, and determining the trusted state of the predicted activity period based on the probability; obtaining the current power level of the AOV camera, and controlling the working state of the AOV camera based on the trusted state and / or the current power level. Because the embodiment of the present application can control the working state of the AOV camera by predicting the trusted state of the activity period and the current power level, it can achieve a dynamic balance between low-power operation and user experience.

[0015] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0017] Figure 1 This is a flow chart of a method for controlling an AOV camera provided by one embodiment of the present application; Figure 2 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 3 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 4is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 5 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 6 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 7 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 8 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 9 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 10 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 11 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 12 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 13 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 14 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Figure 15 1 is a schematic diagram of a controller for executing a control method for an AOV camera provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application.

[0019] In the description of this application, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on this application.

[0020] In the description of this application, "several" means one or more, "many" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The terms "first" and "second" are used solely to distinguish technical features and are not to be construed as indicating or implying relative importance, or as implicitly specifying the number or order of the technical features indicated.

[0021] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0022] In some cases, always-on video (AOV) cameras often employ a timed sleep mechanism to optimize power consumption and battery life. This mechanism periodically shuts down the main control chip and wireless communication module, maintaining only a basic heartbeat connection with the server. Upon detecting an environmental event or a user's active access, the device awakens from sleep to respond. While this passive energy-saving design effectively extends device battery life, it can result in a response delay of several seconds when a user initiates a remote viewing request, creating a bottleneck for interactive scenarios requiring high real-time performance.

[0023] Based on the above situation, the embodiments of the present application propose a control method, controller, medium and product for an AOV camera, aiming to achieve a dynamic balance between low-power operation and user experience.

[0024] The following further describes various embodiments of the control method of the AOV camera of the present application in conjunction with the accompanying drawings.

[0025] like Figure 1 As shown, Figure 1 1 is a flowchart of a control method for an AOV camera provided by an embodiment of the present application; the control method for an AOV camera may include but is not limited to step S110, step S120, step S130 and step S140.

[0026] Step S110: Obtain the timestamp of the target behavior and / or the target alarm event triggering, and construct a heat map based on the timestamp and multiple preset time periods to obtain a behavior heat map; Step S120: extract time periods based on the behavior heat map to obtain predicted activity periods; Step S130: within a first preset period, obtaining the probability of the target behavior and / or target alarm event occurring during the predicted activity period, and determining the credibility of the predicted activity period based on the probability; Step S140: Obtain the current power of the AOV camera, and control the working state of the AOV camera according to the trustworthy state and / or the current power.

[0027] It can be understood that the above-mentioned target behavior is the behavior of the user remotely viewing the camera screen, which can be software preview, device playback access, or software preview and device playback access, and the embodiments of the present application do not specifically limit it.

[0028] It is understandable that the target alarm event mentioned above may be human shape detection, motion detection, or both human shape detection and motion detection, and the embodiments of the present application do not specifically limit them.

[0029] It can be understood that the above-mentioned first preset period can be 7 days, which can be set according to actual needs and is not specifically limited in the embodiment of the present application.

[0030] It is worth noting that, since the embodiment of the present application can control the working state of the AOV camera by predicting the trustworthy state and current power level during the activity period, it can achieve a dynamic balance between low-power operation and user experience.

[0031] like Figure 2 As shown, Figure 2 This is a flowchart of a control method for an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S110, a heat map is constructed according to the timestamp and multiple preset time periods to obtain a behavior heat map, including but not limited to steps S210 and S220.

[0032] Step S210: Divide the second preset period into equally spaced time periods to obtain a plurality of preset time periods; Step S220: Count the number of timestamps in each preset time period, and construct a heat map based on each number and each preset time period to obtain a behavior heat map.

[0033] It can be understood that the above-mentioned second preset period can be one day and can be set according to actual needs. The embodiment of the present application does not specifically limit it.

[0034] Exemplarily, the second preset period is one day, that is, 24 hours, and the 24 hours are divided into equally spaced time periods, for example, each 15 minutes, that is, the time periods are: 00:00 to 00:15, 00:15 to 00:30, ... 23:45 to 00:00.

[0035] It can be understood that by constructing a heat map based on the number of timestamps in each preset time period and each preset time period, a behavior heat map is obtained, so that the behavior heat map can intuitively reflect the frequency of target behaviors and / or target alarm events in each time period.

[0036] like Figure 3 As shown, Figure 3 This is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S120, it includes but is not limited to step S310 and step S320.

[0037] Step S310, averaging each number to obtain an average number; Step S320: extract time periods based on the behavior heat map and the frequency, obtain a preset number of time periods with frequency higher than the average frequency, and determine the preset time periods as predicted activity periods.

[0038] It is understandable that the preset number may be 3, that is, the first 3 preset time periods with times higher than the average times are used as the predicted activity periods.

[0039] It can be understood that since the behavior heat map can intuitively reflect the frequency of target behaviors and / or target alarm events in each time period, time period extraction can be performed through the behavior heat map and the number of times, and time periods with a higher frequency of target behaviors and / or target alarm events can be extracted and determined as predicted activity periods.

[0040] like Figure 4 As shown, Figure 4 This is a flowchart of a control method for an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S130 of determining the trustworthy state of the predicted activity period based on probability, it includes but is not limited to step S410 and step S420.

[0041] Step S410: When the probability is greater than the preset probability threshold; Step S420: Determine whether the credibility status of the predicted activity period is credible.

[0042] It can be understood that when the probability of the target behavior and / or target alarm event occurring during the predicted activity period is greater than the preset probability threshold, it means that the frequency of sending the target behavior and / or target alarm event is high during the predicted activity period, so the trustworthy status of the predicted activity period is determined to be trustworthy.

[0043] like Figure 5 As shown, Figure 5This is a flowchart of a control method for an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S130 of determining the trustworthy state of the predicted activity period based on probability, it includes but is not limited to step S510 and step S520.

[0044] Step S510: When the probability is less than or equal to the preset probability threshold; Step S520: Determine whether the credibility status of the predicted activity period is untrustworthy.

[0045] It can be understood that when the probability of the target behavior and / or target alarm event occurring during the predicted activity period is less than or equal to the preset probability threshold, it means that the frequency of the target behavior and / or target alarm event occurring during the predicted interaction time is still relatively low, so the credibility of the predicted activity period is determined to be untrustworthy.

[0046] like Figure 6 As shown, Figure 6 This is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S140 of controlling the working state of the AOV camera according to the trusted state and / or the current power, it includes but is not limited to step S610 and step S620.

[0047] Step S610: When the trustworthy status of the predicted activity period is trustworthy and the current power level is greater than or equal to the preset power level threshold; Step S620: Control the AOV camera to be in working state.

[0048] It can be understood that when the trusted state of the predicted activity period is trusted and the current power is greater than or equal to the preset power threshold, it means that the AOV camera at this time has sufficient power and the probability of target behavior and / or target alarm events occurring in the current time period is high. Therefore, the AOV camera is controlled to be in a working state, thereby avoiding a response delay of several seconds when the user initiates a remote viewing request, improving the real-time nature of the operation, and achieving a dynamic balance between low-power operation and user experience.

[0049] like Figure 7 As shown, Figure 7 This is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S140 of controlling the working state of the AOV camera according to the trusted state and / or the current power, it includes but is not limited to step S710 and step S720.

[0050] Step S710: When the trustworthy status of the predicted activity period is trustworthy and the current power level is less than the preset power threshold; Step S720: Control the AOV camera to be in a dormant state.

[0051] It can be understood that when the credible state of the predicted activity period is credible and the current power is less than the preset power threshold, it means that the probability of the target behavior and / or target alarm event occurring in the current time period is high, but the power is insufficient. If the AOV camera is always in working state, it is easy to cause the AOV camera to run out of power. Therefore, the AOV camera is controlled to be in sleep state, thereby achieving low-power operation of the AOV camera.

[0052] like Figure 8 As shown, Figure 8 This is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S140 of controlling the working state of the AOV camera according to the trusted state and / or the current power, it includes but is not limited to step S810 and step S820.

[0053] Step S810: When the trustworthy status of the predicted activity period is untrustworthy; Step S820: Control the AOV camera to be in a dormant state.

[0054] It can be understood that when the credible state of the predicted activity period is unreliable, it means that the probability of the target behavior and / or target alarm event occurring in the current time period is small, so the AOV camera is controlled to be in a dormant state, thereby achieving low power consumption operation of the AOV camera.

[0055] like Figure 9 As shown, Figure 9 4 is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; the method for controlling an AOV camera may also include but is not limited to step S910 and step S920.

[0056] Step S910: obtaining a hit rate of target behaviors and / or target alarm events occurring during a predicted activity period with a credible status within a third preset period; Step S920: Adjust the trustworthy state to a trustworthy state of the predicted activity period according to the hit rate.

[0057] It can be understood that the third preset period mentioned above can be 7 days and can be set according to actual needs. The embodiment of the present application does not specifically limit it.

[0058] It can be understood that by adjusting the trusted state to the trusted state of the trusted predicted activity period through the hit rate, it is possible to dynamically adjust the trusted state to the trusted state of the trusted predicted activity period, thereby avoiding the waste of resources caused by the AOV camera being in a working state during the trusted state of the trusted predicted activity period with a low hit rate when target behavior and / or target alarm events occur, thereby achieving low power consumption operation of the AOV camera.

[0059] like Figure 10 As shown, Figure 10 This is a flowchart of a control method for an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S920, it includes but is not limited to step S1010 and step S1020.

[0060] Step S1010: When the hit rate is greater than or equal to the preset hit rate threshold; Step S1020: Maintain the credibility status of the predicted activity period as credible.

[0061] It can be understood that when the hit rate is greater than or equal to the preset hit rate threshold, it means that the frequency of target behavior and / or target alarm events occurring during the predicted activity period when the trustworthy state is trustworthy is high, so the trustworthy state of the predicted activity period is kept as trustworthy, so that when the battery is sufficient, the AOV camera is kept in working state, thereby avoiding a response delay of several seconds when the user initiates a remote viewing request, improving the real-time performance of the operation, and achieving a dynamic balance between low-power operation and user experience.

[0062] It is understandable that the above-mentioned preset hit rate threshold may be 60%, which may be set according to actual needs and is not specifically limited in the embodiments of the present application.

[0063] like Figure 11 As shown, Figure 11 This is a flowchart of a method for controlling an AOV camera provided by another embodiment of the present application; regarding the above-mentioned step S920, it includes but is not limited to step S1110 and step S1120.

[0064] Step S1110: When the hit rate is less than the preset hit rate threshold; Step S1120: Adjust the credibility status of the predicted activity period from credible to uncredible.

[0065] It can be understood that if the hit rate is less than the preset hit rate threshold for a consecutive preset number of days, it means that within the consecutive preset number of days, the frequency of target behavior and / or target alarm events occurring during the predicted activity period with a credible status is low. If the AOV camera is kept in a working state, it will lead to a waste of resources. Therefore, the credible status of the predicted activity period is adjusted from credible to uncredible, avoiding waste of resources and achieving low power consumption operation of the AOV camera.

[0066] It can be understood that the above-mentioned preset number of days can be 3 days, which can be set according to actual needs and is not specifically limited in the embodiment of the present application.

[0067] Based on the control methods of the AOV cameras of the above-mentioned embodiments, overall embodiments of the control methods of the AOV cameras of the present application are respectively proposed below.

[0068] 1. Recording and classification of behavioral events: The system records the target behavior and target alarm events locally in real time: The user's behavior of remotely viewing the camera image (including app preview, device playback access, etc.); Alarm events triggered by the device's local algorithm (such as human detection and motion detection). Each event records its precise timestamp for subsequent time series statistical analysis.

[0069] 2. Time series statistics and behavior heat map construction: Using a 24-hour cycle, divide the day into multiple equally spaced time periods (e.g., 15-minute intervals). Count the number of events within each period, construct a time-frequency mapping matrix, and generate a behavior heat map. This heat map reveals the temporal concentration of user interactions and alerts, visually reflecting device activity cycles.

[0070] 3. Clustering and identification of high-frequency activity periods: We analyze and process the behavioral heatmap using an interval clustering algorithm. Using a density-based clustering algorithm, we divide the entire day into time periods and extract the top N time periods (e.g., three) where behavioral frequency is significantly higher than the average. These are initially designated as "predicted activity periods." This method has greater adaptability than simple threshold judgment.

[0071] 4. Forecast accuracy verification mechanism: In subsequent operation cycles, the actual occurrence of events during the predicted activity period is verified.

[0072] If user previews or alerts continue to occur during the forecast activity period, it is considered a "hit"; If the hit rate within a continuous verification period (e.g., 7 days) is higher than a set threshold (e.g., 90%), the period will be officially marked as a "trusted activity period"; Otherwise, discard the time period and continue with the next round of learning.

[0073] 5. Energy sensing and wake-up control: The system determines the current power level of the device before each predicted activity period begins: If the system is in a trusted activity period and the battery level is above a set threshold (e.g., 90%), the system will remain in operation and will not enter sleep mode. If the battery is low or the device is in an inactive period, it will enter a sleep state or shut down the communication module. This strategy uses the combined conditions of behavior and power to control the system, avoiding blind frequency increases and maintaining energy efficiency.

[0074] 6. Model update and dynamic withdrawal: If the hit rate of the trusted period decreases in subsequent cycles (e.g. <60% for three consecutive days), the tag will be automatically revoked; The system rebuilds the heat map and updates the clustering results every N days (e.g., 7 days) to ensure that the model adapts to changes in user behavior. It also allows manual intervention through the user interface to set or shut down the predictive control logic.

[0075] The process is as follows: like Figure 12 As shown, Figure 12 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; 1. Event recording and heat map generation: Behavioral event recording and classification: Real-time recording of user preview and alarm events, mapped to 15-minute time slices; Time series statistics and behavior heat map construction: Aggregate 7 days of data to generate a smooth heat map; Process logic: Initialize the data structure (7 days × 96 time slice heat map); Collect events and update daily heatmaps; Every day at midnight, the next day begins, triggering aggregation; Aggregate 7 days of data on demand or daily and output a heat map.

[0076] like Figure 13 As shown, Figure 13 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; 2. Clustering and time period verification: Clustering and high-frequency activity period identification: Density-based clustering is used to extract the top three high-frequency time periods; Forecast accuracy verification mechanism: verify the hit rate of the forecast period and mark the reliable period; Process logic: Obtain a smooth heat map and calculate the dynamic threshold; Apply density-based clustering to extract the top three high-frequency time periods; Verify the hit rate within a 7-day period. If it is ≥90%, mark it as a trusted period; otherwise, discard it; Output the trusted time period and continue to scheduling.

[0077] like Figure 14 As shown, Figure 14 is a flow chart of a method for controlling an AOV camera provided by another embodiment of the present application; Scheduling and model updating: Energy sensing and wake-up control: Decide whether to wake up or sleep based on power level and trusted time period; Model update and dynamic withdrawal: regularly update heat maps / clusters, withdraw low hit rate periods, and support user intervention; Process logic: Check the current time and battery level to decide whether to wake up or sleep; Update heatmaps and clusters every 7 days; If the hit rate during the trusted period is less than 60% for three consecutive days, the label will be revoked; Check for user manual intervention and adjust logic; Returns the event collection and runs in a loop.

[0078] It is worth noting that the embodiment of the present application has strong active prediction capabilities, does not rely on image content or single events, and can predict the user's frequently used time periods; the false trigger rate is low, and the hit rate mechanism effectively filters short-term behavior fluctuations; the experience is significantly improved, the system is always running during high-frequency usage periods, and the remote preview response is delay-free; taking into account battery life and safety, the strategy is activated only when the battery is sufficient to ensure the device usage time; the deployment threshold is low, the algorithm is lightweight, and it is compatible with common low-power controllers or AI edge processing platforms.

[0079] Based on the control methods of the AOV cameras in the above-mentioned embodiments, various embodiments of the controller, computer-readable storage medium, and computer program product of the present application are respectively proposed below.

[0080] like Figure 15 As shown, Figure 15 Schematic diagram of a controller for executing a control method for an AOV camera provided by an embodiment of the present application. The controller 700 implemented in the present application includes: a processor 710, a memory 720, and a computer program stored in the memory 720 and executable on the processor 710, wherein: Figure 15 In the figure, a processor 710 and a memory 720 are taken as an example.

[0081] The processor 710 and the memory 720 may be connected via a bus or other means. Figure 15 The bus connection is taken as an example.

[0082] The memory 720 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory 720 may include a high-speed random access memory and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 720 may optionally include a memory 720 remotely located relative to the processor 710, and these remote memories 720 may be connected to the controller 700 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0083] Those skilled in the art will understand that Figure 15 The device structure shown in the figure does not constitute a limitation on the controller 700, and the controller 700 may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0084] exist Figure 15 In the controller 700 shown, the processor 710 can be used to call the control program stored in the memory 720 to implement the above-mentioned AOV camera control method. Specifically, the non-transient software program and instructions required to implement the AOV camera control method of the above-mentioned embodiment are stored in the memory 720. When executed by the processor 710, the AOV camera control method of the above-mentioned embodiment is performed.

[0085] It is worth noting that since the controller 700 of the embodiment of the present application can execute the control method of the AOV camera of any of the above-mentioned embodiments, the specific implementation methods and technical effects of the controller 700 of the embodiment of the present application can refer to the specific implementation methods and technical effects of the control method of the AOV camera of any of the above-mentioned embodiments.

[0086] In addition, an embodiment of the present application further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to execute the above-described control method of the AOV camera. Figures 1 to 14 The method steps in .

[0087] It is worth noting that since the computer-readable storage medium of the embodiment of the present application can execute the control method of the AOV camera of any of the above-mentioned embodiments, the specific implementation methods and technical effects of the computer-readable storage medium of the embodiment of the present application can refer to the specific implementation methods and technical effects of the control method of the AOV camera of any of the above-mentioned embodiments.

[0088] In addition, an embodiment of the present application further provides a computer program product, including a computer program or computer instructions, the computer program or computer instructions being stored in a computer-readable storage medium, the processor of a computer device reading the computer program or computer instructions from the computer-readable storage medium, and the processor executing the computer program or computer instructions, so that the computer device executes the above-described control method for an AOV camera. For example, executing the above-described Figures 1 to 14 The method steps in .

[0089] It is worth noting that since the computer program product of the embodiment of the present application can execute the control method of the AOV camera of any of the above-mentioned embodiments, the specific implementation methods and technical effects of the computer program product of the embodiment of the present application can refer to the specific implementation methods and technical effects of the control method of the AOV camera of any of the above-mentioned embodiments.

[0090] Those skilled in the art will appreciate that all or some of the steps and systems disclosed above can be implemented as software, firmware, hardware, or any suitable combination thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is well known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically includes computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0091] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0093] It should also be understood that the various implementation methods provided in the embodiments of the present application can be combined arbitrarily to achieve different technical effects.

[0094] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the above implementation mode. Technical personnel familiar with the art can also make various equivalent modifications or substitutions under the shared conditions that do not violate the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A control method for an AOV camera, characterized in that: Applied to an AOV camera, the method includes: Obtaining a timestamp of a target behavior and / or a target alarm event being triggered, and constructing a heat map based on the timestamp and a plurality of preset time periods to obtain a behavior heat map; Extracting time periods based on the behavior heat map to obtain predicted activity periods; Within a first preset period, obtaining a probability of a target behavior and / or a target alarm event occurring during the predicted activity period, and determining a credibility state of the predicted activity period based on the probability; The current power level of the AOV camera is obtained, and the working state of the AOV camera is controlled according to the trusted state and / or the current power level.

2. The method according to claim 1, characterized in that The heat map is constructed according to the timestamp and multiple preset time periods to obtain a behavior heat map, including: Dividing the second preset period into equally spaced time periods to obtain a plurality of the preset time periods; The number of times the timestamp occurs in each of the preset time periods is counted, and a heat map is constructed according to each of the times and each of the preset time periods to obtain a behavior heat map.

3. The method according to claim 2, characterized in that Extracting time periods based on the behavior heat map to obtain predicted activity periods includes: Calculating an average of each of the times to obtain an average number of times; Time periods are extracted based on the behavior heat map and each of the times to obtain the preset number of time periods with times higher than the average number, and the preset time periods are determined as predicted activity periods.

4. The method according to claim 1, wherein Determining the credibility of the predicted activity period according to the probability includes one of the following: When the probability is greater than a preset probability threshold, determining that the credibility state of the predicted activity period is credible; When the probability is less than or equal to the preset probability threshold, the credibility state of the predicted activity period is determined to be untrustworthy.

5. The method according to claim 4, characterized in that The controlling the working state of the AOV camera according to the trusted state and / or the current power level includes one of the following: When the credible state of the predicted activity period is credible and the current power level is greater than or equal to a preset power threshold, controlling the AOV camera to be in a working state; When the credible state of the predicted activity period is credible and the current power level is less than the preset power threshold, controlling the AOV camera to be in a dormant state; When the credible state of the predicted activity period is uncredible, the AOV camera is controlled to be in a dormant state.

6. The method according to claim 4, characterized in that The method comprises: Within a third preset period, obtaining a hit rate of target behavior and / or target alarm event occurring during the predicted activity period in which the trustworthy status is trustworthy; The trust state is adjusted according to the hit rate to be a trust state of the predicted activity period that is trustworthy.

7. The method according to claim 6, characterized in that The adjusting the trust state to a trust state of the predicted activity period that is trustworthy according to the hit rate includes: When the hit rate is greater than or equal to a preset hit rate threshold, maintaining the credibility of the predicted activity period as credible; When the hit rate is less than a preset hit rate threshold, the credibility state of the predicted activity period is adjusted from credible to uncredible.

8. A controller, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the control method of the AOV camera according to any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that: Computer-executable instructions are stored, and the computer-executable instructions are used to execute the control method of the AOV camera according to any one of claims 1 to 7.

10. A computer program product comprising a computer program or computer instructions, characterized in that The computer program or the computer instructions are stored in a computer-readable storage medium, and the processor of the computer device reads the computer program or the computer instructions from the computer-readable storage medium. The processor executes the computer program or the computer instructions, so that the computer device performs the control method of the AOV camera according to any one of claims 1 to 7.

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