CN116795624A - Secondary intelligent analysis method for intelligent camera - Google Patents

Secondary intelligent analysis method for intelligent camera Download PDF

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Publication number
CN116795624A
CN116795624A CN202211522564.2A CN202211522564A CN116795624A CN 116795624 A CN116795624 A CN 116795624A CN 202211522564 A CN202211522564 A CN 202211522564A CN 116795624 A CN116795624 A CN 116795624A
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intelligent
camera
analyzer
cameras
analysis
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兰雨晴
余丹
唐霆岳
王丹星
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China Standard Intelligent Security Technology Co Ltd
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China Standard Intelligent Security Technology Co Ltd
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Priority to CN202211522564.2A priority Critical patent/CN116795624A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3093—Configuration details thereof, e.g. installation, enabling, spatial arrangement of the probes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3096—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents wherein the means or processing minimize the use of computing system or of computing system component resources, e.g. non-intrusive monitoring which minimizes the probe effect: sniffing, intercepting, indirectly deriving the monitored data from other directly available data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/60—Software deployment
    • G06F8/65—Updates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Multimedia (AREA)
  • Computer Security & Cryptography (AREA)
  • Image Analysis (AREA)

Abstract

The embodiment of the invention discloses a secondary intelligent analysis method for an intelligent camera, and relates to the technical field of image recognition. The method comprises the following steps: collecting image data of a target monitoring area in real time through a plurality of intelligent cameras; the intelligent camera performs primary analysis on the currently acquired picture data according to a first locally preset intelligent analysis algorithm so as to judge whether an abnormal condition exists in a current target monitoring area; if the intelligent camera judges that the abnormal condition exists in the target monitoring area, intelligent alarm information is sent to the intelligent analyzer; when the intelligent analyzer receives the intelligent alarm information, performing secondary analysis on the picture data of the current target monitoring area according to a locally preset second intelligent analysis algorithm to obtain a secondary analysis result of the current target monitoring area. The intelligent analyzer can effectively reduce the calculation pressure of the intelligent analyzer, improve the analysis efficiency of the picture data and enable the intelligent analyzer to be connected with more intelligent cameras.

Description

Secondary intelligent analysis method for intelligent camera
Technical Field
The invention belongs to the technical field of image recognition, and particularly relates to a secondary intelligent analysis method for an intelligent camera.
Background
Image recognition technology is an important area of artificial intelligence. The method is a technology for identifying objects and objects of various different modes by carrying out object identification on images, and is widely applied to various industries, such as application scenes of object area monitoring, character identification, abnormal behavior analysis, potential danger identification and the like. Especially in the monitoring field, the image recognition technology is utilized to recognize abnormal conditions, so that the method has the advantages of intelligence and automation, effectively improves the efficiency of monitoring management, and saves a large amount of manpower and material resources.
The existing regional video monitoring method is characterized in that firstly, a camera is used for collecting picture data of a target monitoring region in real time, then all the picture data (including pictures and video data) are sent to an intelligent analyzer according to a certain frame rate, and finally the intelligent analyzer is used for identifying abnormal conditions in the picture data according to a preset intelligent analysis algorithm, so that the abnormal conditions in the target monitoring region are intelligently and automatically identified. However, all the picture data are required to be analyzed by the intelligent analyzer, so that a higher calculation performance requirement is provided for the intelligent analyzer, and the calculation performance of the intelligent analyzer is always limited, so that the picture data analysis efficiency is reduced, the number of the intelligent analyzers connected with cameras is limited, and the expansibility of the system is poor.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a secondary intelligent analysis method for an intelligent camera, which is used for solving the problems of lower image data analysis efficiency and poor system expansibility of the existing regional video monitoring method. According to the invention, firstly, the intelligent camera is used for identifying abnormal conditions of the monitored picture data, and after the abnormal conditions are identified, the corresponding picture data are sent to the intelligent analyzer for secondary identification, so that the calculation pressure of the intelligent analyzer is effectively reduced, the analysis efficiency of the picture data is improved, more intelligent cameras can be connected to the intelligent analyzer, and the intelligent analyzer has the advantage of high expansibility.
The embodiment of the invention provides a secondary intelligent analysis method for an intelligent camera, which comprises the following steps of:
collecting image data of a target monitoring area in real time through a plurality of intelligent cameras;
the intelligent camera performs primary analysis on the currently acquired picture data according to a first locally preset intelligent analysis algorithm so as to judge whether an abnormal condition exists in a current target monitoring area;
if the intelligent camera judges that the abnormal condition exists in the target monitoring area, intelligent alarm information is sent to the intelligent analyzer; the intelligent alarm information comprises picture data of a current target monitoring area;
and when the intelligent analyzer receives the intelligent alarm information, performing secondary analysis on the picture data of the current target monitoring area according to a locally preset second intelligent analysis algorithm to obtain a secondary analysis result of the current target monitoring area.
In an alternative embodiment, the preset first/second intelligent analysis algorithm is an intelligent analysis recognition algorithm based on a preset abnormal situation feature library.
In an optional embodiment, the intelligent alarm information further includes a current intelligent camera identifier, a primary analysis result of the target monitoring area, and current time information.
In an optional embodiment, the secondary intelligent analysis method for an intelligent camera further includes:
the intelligent analyzer captures image data acquired by a plurality of intelligent cameras in real time in an idle state;
and the intelligent analyzer analyzes the currently captured image data acquired by the plurality of intelligent cameras in real time according to a locally preset second intelligent analysis algorithm.
In an optional embodiment, before the intelligent analyzer captures the image data collected by the plurality of intelligent cameras in real time in the idle state, the method further includes:
the intelligent analyzer calculates a local idling judgment value at the current time based on a first formula according to the local CPU utilization rate at the current time, the received alarm information and the data quantity of the picture data in the received alarm information;
the intelligent analyzer judges whether the local idling judgment value at the current time is equal to 1, if so, the local idling state at the current time is determined, then the step of capturing the picture data acquired by a plurality of intelligent cameras by the intelligent analyzer in the idling state is continuously executed, otherwise, the local idling state at the current time is determined;
wherein, the first formula is:
in the first formula, E (t) represents an idling determination value of the intelligent analyzer at the current moment; η (t) represents the CPU utilization of the intelligent analyzer at the current moment; g (t_a) represents that the intelligent analyzer receives the intelligent alarm information value of the a-th intelligent camera at the current moment, if the intelligent alarm information of the a-th intelligent camera is received at the current moment, G (t_a) =1, otherwise G (t_a) =0; s (t_a) represents the data amount of picture data in the intelligent alarm information of the a-th intelligent camera received at the current moment, and the unit is a bit; s is S 0 Representing a preset unit data quantity, wherein the unit is a bit; a=1, 2,; n represents the total number of intelligent cameras connected to the intelligent analyzer.
In an optional embodiment, the intelligent analyzer further performs a step of updating the historical alarm times corresponding to the intelligent camera identifications in the currently received intelligent alarm information when the intelligent analyzer receives the intelligent alarm information each time; wherein, the initial value of the historical alarm times corresponding to each camera mark is 0.
In an optional embodiment, the capturing, by the intelligent analyzer, image data collected in real time by the plurality of intelligent cameras in an idle state includes:
when the intelligent analyzer is in an idle state, a plurality of intelligent cameras are screened out based on a second formula according to the historical alarm times corresponding to each camera mark recorded locally and the distance between each camera and other cameras closest to the intelligent analyzer, and the intelligent cameras are used as intelligent cameras required to be subjected to spot inspection at the current moment;
capturing image data acquired in real time by an intelligent camera of the spot check required at the current moment;
wherein the second formula is:
in the second formula, A (t) represents a number array of the intelligent camera which needs to be subjected to spot check at the current moment; d (t_a) represents the historical alarm times corresponding to the a intelligent camera locally recorded until the current time; l (L) min (a) Representing the distance between the a-th intelligent camera and other cameras closest to the a-th intelligent camera;substituting a value of a from a value of 1 to n into a bracket to obtain a maximum value in the bracket; />Substituting the value of a from 1 to n into a bracket to obtain a value composition array of a for the calculation formula in the bracket to be established; e represents a natural constant;
after the intelligent analyzer analyzes the currently captured image data acquired by the plurality of intelligent cameras in real time according to a local preset second intelligent analysis algorithm, the method further comprises:
the intelligent analyzer calculates a control value for controlling the intelligent camera of the required spot check to carry out software upgrading at the current moment based on a third formula according to an analysis result of the image data acquired in real time by the intelligent camera of the required spot check currently grabbed;
the intelligent analyzer judges whether the control value of the intelligent camera for controlling the required spot check at the current moment for software upgrading is equal to 1;
if the control value for controlling the intelligent camera of the required spot check to carry out software upgrading at the previous moment is equal to 1, controlling the intelligent camera of the required spot check to carry out software upgrading;
wherein the third formula is:
in the third formula, J (t) represents a control value for controlling the intelligent camera for the selective examination to perform software upgrading at the current moment; a (t_i) represents the ith element value in the current time array A (t); f [ a (t_i) ] represents an analysis result of the image data acquired by the a (t_i) th intelligent camera in real time, if the analysis result is that the target monitoring area is abnormal, F [ a (t_i) ]=1, otherwise F [ a (t_i) ]=0; size [ A (t) ] represents the number of elements in the array A (t); i=1, 2,..size [ a (t) ].
According to the secondary intelligent analysis method for the intelligent camera, firstly, the intelligent camera collects the picture data of a target monitoring area in real time, and the abnormal condition in the picture information is analyzed according to a first intelligent analysis algorithm; and then, sending the picture information with the abnormal condition to an intelligent analyzer, and enabling the intelligent analyzer to carry out secondary analysis on the picture information with the abnormal condition according to a second intelligent analysis algorithm to obtain a second analysis result. The intelligent analyzer can utilize the calculation power of the intelligent camera to avoid continuous stream pulling decoding of the intelligent analyzer to the camera, effectively reduce the calculation pressure of the intelligent analyzer, improve the analysis efficiency of the picture data, enable the intelligent analyzer to be connected with more intelligent cameras, and have the advantage of high expansibility.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a secondary intelligent analysis method for an intelligent camera according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a flowchart of a secondary intelligent analysis method for an intelligent camera according to an embodiment of the present invention. Referring to fig. 1, the method includes the following steps S101-S104:
s101: and collecting the picture data of the target monitoring area in real time through a plurality of intelligent cameras.
S102: the intelligent camera performs primary analysis on the currently acquired picture data according to a first locally preset intelligent analysis algorithm so as to judge whether an abnormal condition exists in a current target monitoring area; if yes, step S103 is executed.
S103: and sending intelligent alarm information to the intelligent analyzer.
The intelligent alarm information comprises picture data of a current target monitoring area;
in this embodiment, the intelligent alarm information further includes a current intelligent camera identifier, a primary analysis result of the target monitoring area, and current time information, through which the intelligent analyzer can fully understand abnormal and related information conditions, so as to facilitate subsequent spot check work.
S104: and when the intelligent analyzer receives the intelligent alarm information, performing secondary analysis on the picture data of the current target monitoring area according to a locally preset second intelligent analysis algorithm to obtain a secondary analysis result of the current target monitoring area.
Preferably, the preset first/second intelligent analysis algorithm is an intelligent analysis and identification algorithm based on a preset abnormal condition feature library.
In the embodiment, a large amount of picture information with abnormal conditions can be acquired in advance, then the characteristic data of the abnormal conditions in the picture information is obtained by utilizing a big data technology and stored into the characteristic library for training of an intelligent analysis algorithm, so that the analysis and identification accuracy of the intelligent analysis and identification algorithm based on the abnormal condition characteristic library is effectively improved.
The beneficial effects of the technical scheme are as follows: according to the secondary intelligent analysis method for the intelligent camera, firstly, the intelligent camera collects picture data of a target monitoring area in real time, and the abnormal condition in the picture information is analyzed according to a first intelligent analysis algorithm; and then, sending the picture information with the abnormal condition to an intelligent analyzer, and enabling the intelligent analyzer to carry out secondary analysis on the picture information with the abnormal condition according to a second intelligent analysis algorithm to obtain a second analysis result. The intelligent analyzer can utilize the calculation power of the intelligent camera to avoid continuous stream pulling decoding of the intelligent analyzer to the camera, effectively reduce the calculation pressure of the intelligent analyzer, improve the analysis efficiency of the picture data, enable the intelligent analyzer to be connected with more intelligent cameras, and have the advantage of high expansibility.
As an optional embodiment, the secondary intelligent analysis method for an intelligent camera may further include the following steps S201 to S202:
s201: the intelligent analyzer captures image data acquired by a plurality of intelligent cameras in real time in an idle state;
s202: and the intelligent analyzer analyzes the currently captured image data acquired by the plurality of intelligent cameras in real time according to a locally preset second intelligent analysis algorithm.
The beneficial effects of the technical scheme are as follows: when the intelligent analyzer is idle, the image data acquired by the intelligent camera is analyzed according to the second intelligent analysis algorithm, and the performance of the second intelligent analysis algorithm is superior to that of the first intelligent analysis algorithm, so that the accuracy of analysis is effectively improved under the condition that the performance of the intelligent analyzer is not affected.
As an optional embodiment, the step S201 may further include the following steps S301 to S304:
s301: the intelligent analyzer calculates a local idling judgment value at the current time based on a first formula according to the local CPU utilization rate at the current time, the received alarm information and the data quantity of the picture data in the received alarm information;
s302: the intelligent analyzer judges whether the local idleness judging value at the current moment is equal to 1, if yes, the step S303 is executed, otherwise, the step S304 is executed;
s303: determining that the current time is in an idle state locally, and then continuing to execute step S201;
s304: determining that the local area is not in an idle state at the current moment;
wherein, the first formula is:
in the first formula, E (t) represents an idling determination value of the intelligent analyzer at the current moment; η (t) represents the CPU utilization of the intelligent analyzer at the current moment; g (t_a) represents that the intelligent analyzer receives the intelligent alarm information value of the a-th intelligent camera at the current moment, if the intelligent alarm information of the a-th intelligent camera is received at the current moment, G (t_a) =1, otherwise G (t_a) =0; s (t_a) represents the data amount of picture data in the intelligent alarm information of the a-th intelligent camera received at the current moment, and the unit is a bit; s is S 0 Representing a preset unit data quantity, wherein the unit is a bit; a=1, 2,; n represents the total number of intelligent cameras connected to the intelligent analyzer.
The beneficial effects of the technical scheme are as follows: judging whether the current intelligent analyzer is idle or not according to the local CPU utilization rate of the intelligent analyzer at the current time, the received alarm information and the data quantity of the picture data in the received alarm information by utilizing the first formula (1), and facilitating the follow-up distribution of sampling inspection work to the intelligent analyzer in an idle state so as to achieve the aim of larger utilization of resources.
As an optional embodiment, the intelligent analyzer further performs a step of updating the historical alarm times corresponding to the intelligent camera identifier in the currently received intelligent alarm information when the intelligent analyzer receives the intelligent alarm information each time; wherein, the initial value of the historical alarm times corresponding to each camera mark is 0.
The beneficial effects of the technical scheme are as follows: the intelligent alarm information objectively reflects the information of identifying abnormal conditions of the corresponding intelligent cameras, so that whether the corresponding intelligent cameras need to be subjected to spot check or not can be determined conveniently according to the information, and the intelligent level of the system is effectively improved.
As an alternative embodiment, the step S201 may include the following steps S401 to S402:
s401: when the intelligent analyzer is in an idle state, a plurality of intelligent cameras are screened out based on a second formula according to the historical alarm times corresponding to each camera mark recorded locally and the distance between each camera and other cameras closest to the intelligent analyzer, and the intelligent cameras are used as intelligent cameras required to be subjected to spot inspection at the current moment;
s402: capturing image data acquired in real time by an intelligent camera of the spot check required at the current moment;
wherein the second formula is:
in the second formula, A (t) represents a number array of the intelligent camera which needs to be subjected to spot check at the current moment; d (t_a) represents the historical alarm times corresponding to the a intelligent camera locally recorded until the current time; l (L) min (a) Representing the distance between the a-th intelligent camera and other cameras closest to the a-th intelligent camera;substituting a value of a from a value of 1 to n into a bracket to obtain a maximum value in the bracket; />Substituting the value of a from 1 to n into a bracket to obtain a value composition array of a for the calculation formula in the bracket to be established; e represents a natural constant;
preferably, after the step S202, the following steps S501 to S503 may be further included:
s501: the intelligent analyzer calculates a control value for controlling the intelligent camera of the required spot check to carry out software upgrading at the current moment based on a third formula according to an analysis result of the image data acquired in real time by the intelligent camera of the required spot check currently grabbed;
s502: the intelligent analyzer judges whether the control value of the intelligent camera for controlling the required spot check at the current moment for software upgrading is equal to 1; if yes, executing S503;
s503: controlling the intelligent camera of the required spot check to carry out software upgrading;
wherein the third formula is:
in the third formula, J (t) represents a control value for controlling the intelligent camera of the required spot check to perform software upgrade at the current moment, J (t) =1 represents the intelligent camera of the required spot check to perform software upgrade, and J (t) =0 represents the intelligent camera of the required spot check not to perform software upgrade; a (t_i) represents the ith element value in the current time array A (t); f [ a (t_i) ] represents an analysis result of the image data acquired by the a (t_i) th intelligent camera in real time, if the analysis result is that the target monitoring area is abnormal, F [ a (t_i) ]=1, otherwise F [ a (t_i) ]=0; size [ A (t) ] represents the number of elements in the array A (t); i=1, 2,..size [ a (t) ].
The beneficial effects of the technical scheme are as follows: the intelligent cameras which need to be subjected to targeted spot inspection are screened out from all intelligent cameras according to the number of intelligent alarm times of the intelligent cameras which push pictures to the intelligent analyzer according to the history and the distance between each intelligent camera and other intelligent cameras which are closest to each other, so that the detection state of the intelligent cameras can be effectively known; and then judging whether the intelligent camera needs to be controlled to carry out software upgrading according to the result of carrying out secondary analysis on the image acquired by the intelligent camera with the targeted spot check by utilizing a third formula (3), and further carrying out upgrading operation timely under the condition that the current software version is old and the alarm cannot be effectively identified, so that the working stability of the system is ensured.
From the content of the embodiment, it can be known that the intelligent analyzer monitors various intelligent alarms of the intelligent camera by using the equipment SDK, when the intelligent alarms occur, the intelligent camera captures a picture and pushes the picture to the intelligent analyzer, and the intelligent analyzer receives the picture data and performs secondary analysis on the picture by using an intelligent algorithm with a higher level than that of the camera; in addition, the intelligent analyzer not only receives the pushing information of the intelligent camera grabs, but also performs secondary analysis on the picture data acquired by the intelligent camera of the targeted grabbing part in a more idle state so as to prevent the situation that the intelligent camera in a high-level abnormal state cannot recognize and cannot alarm.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the methods specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the method specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the methods specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof. The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims (7)

1. The secondary intelligent analysis method for the intelligent camera is characterized by comprising the following steps of:
collecting image data of a target monitoring area in real time through a plurality of intelligent cameras;
the intelligent camera performs primary analysis on the currently acquired picture data according to a first locally preset intelligent analysis algorithm so as to judge whether an abnormal condition exists in a current target monitoring area;
if the intelligent camera judges that the abnormal condition exists in the target monitoring area, intelligent alarm information is sent to the intelligent analyzer; the intelligent alarm information comprises picture data of a current target monitoring area;
and when the intelligent analyzer receives the intelligent alarm information, performing secondary analysis on the picture data of the current target monitoring area according to a locally preset second intelligent analysis algorithm to obtain a secondary analysis result of the current target monitoring area.
2. The secondary intelligent analysis method for an intelligent camera according to claim 1, wherein the preset first/second intelligent analysis algorithm is an intelligent analysis recognition algorithm based on a preset abnormal situation feature library.
3. The secondary intelligent analysis method for intelligent cameras according to claim 1 or 2, wherein the intelligent alarm information further comprises a current intelligent camera identification, a primary analysis result of a target monitoring area and current time information.
4. The secondary intelligent analysis method for an intelligent camera according to claim 3, wherein the method further comprises:
the intelligent analyzer captures image data acquired by a plurality of intelligent cameras in real time in an idle state;
and the intelligent analyzer analyzes the currently captured image data acquired by the plurality of intelligent cameras in real time according to a locally preset second intelligent analysis algorithm.
5. The secondary intelligent analysis method for intelligent cameras as claimed in claim 4, further comprising, before said intelligent analyzer captures the image data collected by the plurality of intelligent cameras in real time in an idle state:
the intelligent analyzer calculates a local idling judgment value at the current time based on a first formula according to the local CPU utilization rate at the current time, the received alarm information and the data quantity of the picture data in the received alarm information;
the intelligent analyzer judges whether the local idling judgment value at the current time is equal to 1, if so, the local idling state at the current time is determined, then the step of capturing the picture data acquired by a plurality of intelligent cameras by the intelligent analyzer in the idling state is continuously executed, otherwise, the local idling state at the current time is determined;
wherein, the first formula is:
in the first formula, E (t) represents an idling determination value of the intelligent analyzer at the current moment; η (t) represents the CPU utilization of the intelligent analyzer at the current moment; g (t_a) represents that the intelligent analyzer receives the intelligent alarm information value of the a-th intelligent camera at the current moment, if the intelligent alarm information of the a-th intelligent camera is received at the current moment, G (t_a) =1, otherwise G (t_a) =0; s (t_a) represents the data amount of picture data in the intelligent alarm information of the a-th intelligent camera received at the current moment, and the unit is a bit; s is S 0 Representing a preset unit data quantity, wherein the unit is a bit; a=1, 2, …, n; n represents the total number of intelligent cameras connected to the intelligent analyzer.
6. The secondary intelligent analysis method for an intelligent camera according to claim 5, wherein the intelligent analyzer further performs the step of updating the historical alarm times corresponding to the intelligent camera identification in the currently received intelligent alarm information each time the intelligent alarm information is received; wherein, the initial value of the historical alarm times corresponding to each camera mark is 0.
7. The secondary intelligent analysis method for intelligent cameras as claimed in claim 6, wherein said intelligent analyzer captures image data collected by a plurality of intelligent cameras in real time in an idle state, comprising:
when the intelligent analyzer is in an idle state, a plurality of intelligent cameras are screened out based on a second formula according to the historical alarm times corresponding to each camera mark recorded locally and the distance between each camera and other cameras closest to the intelligent analyzer, and the intelligent cameras are used as intelligent cameras required to be subjected to spot inspection at the current moment;
capturing image data acquired in real time by an intelligent camera of the spot check required at the current moment;
wherein the second formula is:
in the second formula, A (t) represents a number array of the intelligent camera which needs to be subjected to spot check at the current moment; d (t_a) represents the historical alarm times corresponding to the a intelligent camera locally recorded until the current time; l (L) min (a) Representing the distance between the a-th intelligent camera and other cameras closest to the a-th intelligent camera;substituting a value of a from a value of 1 to n into a bracket to obtain a maximum value in the bracket; />Substituting the value of a from 1 to n into a bracket to obtain a value composition array of a for the calculation formula in the bracket to be established; e represents a natural constant;
after the intelligent analyzer analyzes the currently captured image data acquired by the plurality of intelligent cameras in real time according to a local preset second intelligent analysis algorithm, the method further comprises:
the intelligent analyzer calculates a control value for controlling the intelligent camera of the required spot check to carry out software upgrading at the current moment based on a third formula according to an analysis result of the image data acquired in real time by the intelligent camera of the required spot check currently grabbed;
the intelligent analyzer judges whether the control value of the intelligent camera for controlling the required spot check at the current moment for software upgrading is equal to 1;
if the control value for controlling the intelligent camera of the required spot check to carry out software upgrading at the previous moment is equal to 1, controlling the intelligent camera of the required spot check to carry out software upgrading;
wherein the third formula is:
in the third formula, J (t) represents a control value for controlling the intelligent camera for the selective examination to perform software upgrading at the current moment; a (t_i) represents the ith element value in the current time array A (t); f [ a (t_i) ] represents an analysis result of the image data acquired by the a (t_i) th intelligent camera in real time, if the analysis result is that the target monitoring area is abnormal, F [ a (t_i) ]=1, otherwise F [ a (t_i) ]=0; size [ A (t) ] represents the number of elements in the array A (t); i=1, 2, …, size [ a (t) ].
CN202211522564.2A 2022-11-30 2022-11-30 Secondary intelligent analysis method for intelligent camera Pending CN116795624A (en)

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