CN110691240B - Mobile detection missing recording detection method and device - Google Patents
Mobile detection missing recording detection method and device Download PDFInfo
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- CN110691240B CN110691240B CN201911073180.5A CN201911073180A CN110691240B CN 110691240 B CN110691240 B CN 110691240B CN 201911073180 A CN201911073180 A CN 201911073180A CN 110691240 B CN110691240 B CN 110691240B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/06—Diagnosis, testing or measuring for television systems or their details for recorders
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
- H04N5/78—Television signal recording using magnetic recording
- H04N5/781—Television signal recording using magnetic recording on disks or drums
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The invention provides a mobile detection missing record detection method and a mobile detection missing record detection device. The method comprises the following steps: acquiring the flow average value of a network camera device in a network environment within preset time every preset time; judging whether the working mode of the network camera device is a mobile detection mode or not according to the flow mean value; if the working mode of the network camera device is the mobile detection mode, the interactive data stream between the network camera device and the network video recording device corresponding to the network camera device is analyzed, and whether the network camera device is missed in recording or not is confirmed through the interactive data stream. The invention realizes the detection and the warning of the video missing of the network camera devices under different network video recording devices in the network environment, lightens the workload of an IT or a network administrator, reminds a user to maintain IPC equipment in time, avoids a series of risks caused by the missing of the video at key moments, and improves the detection efficiency and the detection accuracy.
Description
Technical Field
The present invention relates to the field of network security management technologies, and in particular, to a method and an apparatus for detecting mobile detection missing records.
Background
At present, a network video recorder (NVR device) mainly functions to receive, store and manage a digital video stream transmitted by an internet protocol camera (IPC device) through a network. Through the NVR equipment, a plurality of IPC equipment can be watched, browsed, played back, managed and stored at the same time, the involvement of computer hardware is eliminated, and the trouble of installing software is avoided.
When an IPC device fails, is restarted accidentally or is abnormally connected with a network, a problem of missing records is caused, and the NVR device cannot sense the problem.
In the existing method, whether video missing recording exists or not can be judged only by manually logging in a control page of the NVR equipment or accessing the NVR storage equipment and checking the continuity of a video file. The method is complicated in operation, time-consuming and labor-consuming, is easy to have the problem of judgment errors caused by human factors when the video files are checked, and is low in detection efficiency and large in error.
Disclosure of Invention
In view of the above, the present invention provides a method for detecting missing records in motion detection, comprising:
acquiring a flow average value of a network camera device in a network environment within preset time every preset time;
judging whether the working mode of the network camera device is a mobile detection mode or not according to the flow mean value;
and if the working mode of the network camera device is the mobile detection mode, analyzing an interactive data stream between the network camera device and a network video recording device corresponding to the network camera device, and determining whether the network camera device is missed to record or not through the interactive data stream.
Preferably, if the working mode of the network camera device is the mobile detection mode, analyzing an interactive data stream between the network camera device and the network video recording device corresponding to the network camera device, and determining whether the network camera device is missed in recording through the interactive data stream includes:
if the working mode of the network camera device is a mobile detection mode, judging whether the data stream between the network camera device and the network video recording device corresponding to the network camera device contains a real-time stream transmission protocol data stream;
and if the network camera device does not contain the real-time streaming protocol data stream, determining whether the network camera device misses recording according to the state information of the network camera device in the heartbeat cycle.
Preferably, the "determining whether the network camera device is missed to record according to the status information of the network camera device in the heartbeat cycle" includes:
judging whether the network camera device sends state information to the network video recording device in a heartbeat period or not;
if the network camera device sends state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in a normal working state;
and if the network camera device does not send state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in an abnormal working state.
Preferably, after the "determining that the network camera apparatus is in the abnormal operating state", the method further includes:
acquiring video file names of all video files in a preset video recording time corresponding to the network camera device in the network video recording device, and acquiring video starting time and video ending time according to the video file names;
judging whether all video files are continuous or not according to the video file name, the video recording starting time and the video recording ending time;
and if the information is not continuous, judging that the missing record occurs, and generating missing record warning information.
Preferably, after "determining whether all video files are continuous according to the video file name and the end time", the method further includes:
if the network video recording device is continuous, judging whether the network video recording device contains a mobile detection starting log of the network camera device and a mobile detection ending log corresponding to the mobile detection starting log;
if the mobile detection start log and the mobile detection end log are contained, acquiring the mobile detection start time in the mobile detection start log and the mobile detection end time in the mobile detection end log;
judging whether the corresponding video files are contained in the range of the motion detection starting time and the motion detection ending time;
and if the corresponding video file is not contained, judging that the missing record occurs, and generating missing record warning information.
Preferably, after the step of determining that the skip recording occurs and generating the skip recording warning information if the corresponding video file is not included, the method further includes:
marking the network camera device and recording abnormal counting times corresponding to the missing record warning information;
and if the abnormal counting times are not less than the preset counting times, generating a software abnormal alarm, and clearing the abnormal counting times of the network camera device.
Preferably, the determining whether the working mode of the network camera device is the mobile detection mode according to the flow average value includes:
judging whether the current flow average value is less than 10% of the flow average value before the preset time;
if the average value of the flow before the preset time is less than 10%, judging that the working mode of the network camera device is a mobile detection mode;
if the current flow average value is not less than 10% of the flow average value before the preset time, judging whether the difference between the current flow average value and the flow average value before the preset time is less than 20%;
if the difference between the current flow average value and the flow average value before the preset time is less than 20%, judging that the working mode of the network camera device is a real-time monitoring mode;
and if the difference between the current flow average value and the flow average value before the preset time is not less than 20%, judging that the working mode of the network camera device is a mobile detection mode.
Preferably, the calculation method of the flow average value is as follows:
and the average flow value is the total flow/preset time of data sent to the network video recording device by the network camera device in the preset time.
Preferably, after the determining whether the working mode of the network camera device is the mobile detection mode according to the flow average value, the method further includes:
if the working mode of the network camera device is a real-time monitoring mode, acquiring a flow average value of the network camera device within a preset time at intervals of preset time;
judging whether the current flow average value is less than 10% of the flow average value before the preset time;
and if the current flow average value is less than 10% of the flow average value before the preset time, judging that missing recording occurs, and generating missing recording warning information.
In addition, in order to solve the above problem, the present application further provides a mobile detection device for missing recording, including:
the acquisition module is used for acquiring the flow average value of the network camera device in the network environment within the preset time at each interval of preset time;
the judging module is used for judging whether the working mode of the network camera device is a mobile detection mode according to the flow mean value;
and the analysis module is used for analyzing an interactive data stream between the network camera device and the network video recording device corresponding to the network camera device when the working mode of the network camera device is a mobile detection mode, and confirming whether the network camera device is missed to record or not through the interactive data stream.
The invention provides a mobile detection missing record detection method and a mobile detection missing record detection device. The method comprises the steps of judging whether the current working mode of the network camera device is a mobile detection mode or not through the flow average value in the preset time, and then confirming whether the network camera device is missed in recording or not according to the interactive data stream between the network camera device and the network video recording device. The invention realizes the detection and the warning of the video missing of the network camera devices under different network video recording devices in the network environment, lightens the workload of an IT or a network administrator, reminds a user to maintain IPC equipment in time, avoids a series of risks caused by the missing of the video at key moments, and improves the detection efficiency and the detection accuracy.
Drawings
Fig. 1 is a schematic structural diagram of a hardware operating environment according to an embodiment of a method for detecting missing records in motion detection of the present invention;
FIG. 2 is a flowchart illustrating a mobile detection method for missed records according to a first embodiment of the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of a mobile detection skip-recording method according to the present invention;
fig. 4 is a flowchart illustrating a second embodiment of the motion detection skip-recording method according to the present invention, which includes a step S320;
FIG. 5 is a flowchart illustrating a third exemplary embodiment of a method for detecting missed records in motion detection according to the present invention;
fig. 6 is a flowchart illustrating a step S200 of a mobile detection skip-recording detection method according to a fourth embodiment of the present invention;
FIG. 7 is a flowchart illustrating a fifth embodiment of a motion detection skip detection method according to the present invention;
fig. 8 is a flowchart illustrating a flow analysis mobile detection video skip problem according to a sixth embodiment of the mobile detection skip detection method of the present invention;
FIG. 9 is a flowchart illustrating a combination of processes 1-3 according to a sixth embodiment of the method for detecting missing records in motion detection;
fig. 10 is a functional block diagram of the motion detection skip-recording detection apparatus according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
Reference will now be made in detail to the embodiments of the present invention, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic structural diagram of a hardware operating environment of a terminal according to an embodiment of the present invention.
The mobile detection missing record detection system in the embodiment of the invention can be a PC, and can also be a mobile terminal device such as a smart phone, a tablet computer or a portable computer. As shown in fig. 1, the motion detection system may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may comprise a display screen, an input unit such as a keyboard, a remote control, and the optional user interface 1003 may also comprise a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high speed RAM memory or a stable memory such as a disk memory. The memory 1005 may alternatively be a storage device separate from the processor 1001. Optionally, the motion detection skip-recording system may further include a RF (Radio Frequency) circuit, an audio circuit, a WiFi module, and the like. In addition, the mobile detection and omission detecting system can be further configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor and the like, and the details are not repeated herein.
Those skilled in the art will appreciate that the motion detection skip detection system shown in FIG. 1 is not intended to be limiting and may include more or fewer components than shown, or some components in combination, or a different arrangement of components. As shown in fig. 1, the memory 1005, which is a computer-readable storage medium, may include an operating system, a data interface control program, a network connection program, and a motion detection and miss detection program.
The invention provides a mobile detection missing record detection method and a mobile detection missing record detection device. The method realizes the video missing detection and alarm of the network camera devices under different network video recording devices in the network environment, reduces the workload of IT or network managers, reminds users of maintaining IPC equipment in time, avoids a series of risks caused by missing recording at key moments, and improves the detection efficiency and the detection accuracy.
Example 1:
referring to fig. 2, a first embodiment of the present invention provides a method for detecting a motion detection skip record, including:
step S100, acquiring a flow average value of a network camera device in a network environment within preset time at intervals of preset time;
in the embodiment, the network camera device may be an IPC device; the network video recording device is NVR equipment; wherein, a plurality of subordinate IPC devices can be connected under the NVR device. One or more NVR devices may be included within a network environment, which may be a local area network.
Above-mentioned, when predetermineeing the control of current flow for through thing networking analytical equipment, the time of predetermineeing, this time can be 2 minutes, also can be for other time length. If the preset time is 2 minutes, the IPC equipment sends the flow mean value of the NVR equipment to serve as a reference for subsequent flow analysis within 2 minutes every 2 minutes through the internet of things analysis equipment.
Step S200, judging whether the working mode of the network camera device is a mobile detection mode according to the flow mean value;
the IPC device includes two working modes, namely a mobile detection mode and a real-time monitoring mode. Wherein, remove and listen the mode, generally be called motion and listen, the image that the camera was gathered according to different frame rates can be calculated and compare by CPU according to certain algorithm, when the picture changes, if someone walks over, or the camera lens is moved (or satisfies other motion conditions), the calculated result surpasss the predetermined range, the camera can contact the server and initiate and report an emergency and ask for help or increased vigilance this moment and notify APP end, IPC will open the video recording function this moment, and can be at the very first time propelling movement alarm information, so not only can save the NVR's that IPC connects storage space, also can let the user know the condition in control area very first time.
The real-time monitoring mode is the traditional function of IPC, and is to keep continuous recording.
And the flow average value is the flow average value of the interactive data between the IPC and the NVR within the preset time, when the flow reaches and keeps a certain degree, the current mode can be determined to be the real-time monitoring mode, and the flow average value is continuously at a lower flow level, so that the mobile detection mode can be determined.
After the current working mode is judged to be the mobile detection mode, the interactive data stream can be analyzed so as to judge whether the network camera device has the condition of missing recording. Specifically, the interactive data stream is a data stream sent from IPC to NVR. Based on the working mode of the IPC equipment, whether the network camera device has the condition of missing record can be further confirmed through the interactive data stream between the IPC equipment and the NVR equipment. For example, the information can be confirmed by time, file name, flow rate, etc.
In addition, before "acquiring, every preset time, a flow average value of the network camera device in the network environment within the preset time", the method may further include:
mirroring the router or switch flow in the network environment where the NVR equipment is located to the Internet of things analysis equipment, so as to identify the network equipment existing in the network environment;
and recording the IPC equipment aiming at the identified network equipment, and ignoring other equipment.
The embodiment provides a method and a device for detecting missing records in motion detection. The method comprises the steps of judging whether the current working mode of the network camera device is a mobile detection mode or not through the flow average value in the preset time, and then confirming whether the network camera device is missed in recording or not according to the interactive data stream between the network camera device and the network video recording device. The invention realizes the detection and the warning of the video missing of the network camera devices under different network video recording devices in the network environment, lightens the workload of an IT or a network administrator, reminds a user to maintain IPC equipment in time, avoids a series of risks caused by the missing of the video at key moments, and improves the detection efficiency and the detection accuracy.
In the embodiment, the traffic interaction between the IPC equipment and the NVR equipment can be accurately identified by using the traffic identification method, and the IPC equipment starting mobile detection has high fault identification rate. By adopting the method provided by the invention, the IPC equipment under different NVR equipment can be subjected to video missing record detection and alarm, the workload of an IT or network administrator is reduced, a user is reminded of maintaining the IPC equipment in time, and a series of risks caused by missing records at key moments are avoided.
Example 2:
referring to fig. 3-4, a second embodiment of the present invention provides a method for detecting missed recording in motion detection, based on the first embodiment shown in fig. 2, where in step S300, "if the operating mode of the network camera device is the motion detection mode, the method analyzes an interactive data stream between the network camera device and a network video recording device corresponding to the network camera device, and determines whether the network camera device is missed recording through the interactive data stream", including:
step S310, if the working mode of the network camera device is the mobile detection mode, judging whether the data stream between the network camera device and the network video recording device corresponding to the network camera device contains the real-time stream transmission protocol data stream;
the real-Time Streaming protocol data stream is rtsp (real Time Streaming protocol).
If the working mode of the IPC device is the mobile detection mode, further detecting whether the RTSP data stream is included. Whether the RTSP data stream is contained or not represents whether data interaction of a real-time streaming protocol exists between the equipment and the NTR equipment or not, and whether the RTSP data stream is contained or not can judge whether the current IPC equipment is shot or not in a mobile detection mode, namely whether the current IPC equipment is in a working state or not can be checked.
Step S320, if the network camera device does not include the live streaming protocol data stream, determining whether the network camera device is missed according to the status information of the network camera device in the heartbeat cycle.
The heartbeat cycle refers to that the main server and each device periodically send information to judge the health condition of the device and judge whether the other side is alive. If the heartbeat information of the equipment is not received within the specified time, the equipment can be suspected to be in fault, whether the fault occurs or not is checked carefully, and necessary measures are taken after the fault is confirmed. In the mobile detection mode, the data stream does not contain the real-time streaming protocol data stream, and whether the missing recording condition exists in the data stream can be further judged by checking the state information of the network camera device.
It should be noted that the heartbeat cycle is a cycle in which the IPC device sends a state to the NVR device, and is generally sent once in 30s, IPC devices of different manufacturers may have differences, and software may configure the heartbeat monitoring cycle according to the identified IPC device of a specific manufacturer.
The step S320 of "determining whether the network camera device is missing from the status information of the network camera device in the heartbeat cycle" includes:
step S321, judging whether the network camera device sends state information to the network video recording device in a heartbeat cycle;
step S322, if the network camera device sends state information to the network video recording device in a heartbeat cycle, determining that the network camera device is in a normal working state;
step S323, if the network video recording device does not send status information in one heartbeat cycle, determining that the network video recording device is in an abnormal operating state.
The state information is the state information, if the IPC device sends the state to the NVR device in a heartbeat period, the IPC device works normally, and the Internet of things analysis device continues to monitor. If the IPC equipment does not send the state to the NVR equipment in a heartbeat period, the IPC equipment works abnormally, the problem of missing records exists, and at the moment, the IPC equipment is marked to be abnormal by the Internet of things analysis equipment.
In addition, if the data stream between the network camera device and the network video recording device corresponding to the network camera device includes a real-time streaming protocol data stream, that is, the data stream sent by the IPC device to the NVR device includes an RTSP stream, it is determined that the IPC device is working normally (step S322), and the internet of things analysis device continues to monitor.
Example 3:
referring to fig. 5, the present embodiment provides a method for detecting a missed record in motion detection, based on the foregoing embodiment 2, after "determining that the network camera is in an abnormal operating state" in step S323, the method further includes:
step S324, acquiring video file names of all video files in the preset video time corresponding to the network camera device in the network video recording device, and acquiring video starting time and video ending time according to the video file names;
in the method for detecting whether the file is missed by reading the file through NVR linkage, the file name can be used for determining. The method in this embodiment may be based on step S323 in embodiment 2, and may also be an independent method for determining whether to skip recording. Specifically, before step S324, the method may include:
configuring NVR brand information, logging in an account, a password, a port and monitoring network segment information;
starting a detection thread, receiving configuration information input in the previous step, storing the configuration information in a memory, and persisting the configuration information to a database;
and starting a timing task, logging in NVR equipment based on the previous configuration information, and reading the name of the video file within the latest N hours.
Specifically, the file name of the video file is analyzed, when the IPC device records, the NVR device stores the recorded file, and the stored file name is named according to the start time and the end time of the video, that is, the file name contains the start time and the end time of the video. Therefore, the start time and the end time can be acquired from the file name, and the continuity of the file can be judged according to the start time and the end time in the file name.
Step S325, judging whether all video files are continuous according to the video file name, the video starting time and the video ending time;
in step S326, if not, it is determined that a missing record occurs, and a missing record warning message is generated.
Step S327, if the network video recording device is continuous, determining whether the network video recording device includes a motion detection start log of the network camera device and a motion detection end log corresponding to the motion detection start time;
in this embodiment, a method for determining whether there is a missing record condition by using a mobile detection start/stop log is provided, where the method may be used to independently detect whether there is a missing record condition for an IPC device, or may be used in combination with the foregoing method to further verify the foregoing steps.
If it is an independent method for determining, before step S327, it may include:
configuring NVR brand information, logging in an account, a password, a port and monitoring network segment information;
starting a detection thread, receiving the configuration information input in the step, storing the configuration information in a memory, and persisting the configuration information to a database;
and starting a timing task, logging in the NVR equipment by depending on the information in the step, and acquiring the information of starting the mobile detection channel.
As described above, if the file names between the video files are consecutive, the following method can be used to further confirm the consecutive video files, thereby improving the accuracy of the judgment and preventing erroneous judgment.
It should be noted that, the network video recording device generates the movement detection log after the IPC device is started and stopped each time, and specifically, the movement detection start log and the movement detection end log are respectively generated according to the start and stop, and the corresponding start time and stop time may be stored in the logs. Multiple sets of movement detection logs may be stored in the NVR device corresponding to each IPC device.
Step S328, if the motion detection start log and the motion detection end log are included, obtaining the motion detection start time in the motion detection start log and the motion detection end time in the motion detection end log;
in the above, by determining whether there is a movement detection start log and the movement detection end log, the current state of the IPC device can be determined, specifically:
when the movement detection starting time is not read through the movement detection starting log, namely the movement detection starting log is not available, the video recording is not started, and the processing is not performed temporarily.
When the movement detection start time is acquired through the movement detection start log, but the movement detection end log is not acquired, that is, the movement detection end time is not acquired, it indicates that the IPC device is still in the video recording and is not processed temporarily.
When the motion detection start log and the motion detection end log are acquired simultaneously, the corresponding motion detection start time and the corresponding motion detection end time can be acquired through the two corresponding logs.
As described above, since the NVR device may include a plurality of sets of corresponding movement detection start/end logs, the movement detection start/end logs corresponding to the IPC device within N hours may be defined, for example, if N is 4, the movement detection start log and the movement detection end log of the IPC device within 4 hours may be obtained.
Step S329, determining whether the motion detection start time and the motion detection end time range include corresponding video files;
in step S329a, if the corresponding video file is not included, it is determined that the skip recording occurs, and skip recording warning information is generated.
Step S329b, marking the network camera device, and recording abnormal statistics times corresponding to the missed record warning information;
step S329c, if the abnormal statistics number is not less than the preset statistics number, generating a software abnormal alarm, and clearing the abnormal statistics number of the network camera device.
The video files in the time range are synchronously read, and the video starting time and the video ending time of each video file can be further analyzed; and judging whether video files exist in the starting time and the ending time of the mobile detection. If the missing is detected, the missing record is indicated in the missing time period, and an alarm message is generated.
If the missing record condition exists, the IPC equipment information is marked, the abnormal counting times are recorded, and the step S100 is reused for the missing record detection. When the abnormal counting times reach 3 times (preset counting times), a software abnormal alarm is generated to prompt a user to check the IPC equipment and the Internet of things analysis equipment, and the abnormal counting times of the IPC equipment are cleared at the same time.
In addition, after the step S329 determines whether the motion detection start time and the motion detection end time range include the corresponding video file, the method further includes: and if the corresponding video file is contained, judging that the working state of the IPC equipment is normal.
In this embodiment, after step S323, whether the IPC device has the missed record condition is verified by the file name of the video file, and further, the mobile detection start log and the mobile detection end log are used to determine the missed record condition, and the two methods, which are linked with the IPC device and the NVR device based on the file name and the mobile detection log, are an NVR-linked file reading method and an NVR-linked mobile detection method, so that whether the IPC device has the missed record can be quickly checked, and the accuracy of flow analysis and identification can be further improved.
Example 4:
referring to fig. 6, the present embodiment provides a method for detecting missing record in motion detection, based on the foregoing embodiment 1, where in the step S200, "determining whether the operation mode of the network camera device is a motion detection mode according to the traffic mean value" includes:
step S210, judging whether the current flow average value is less than 10% of the flow average value before the preset time;
in the above, when the working mode of the IPC device is judged, the judgment can be performed through the current flow average value. When the preset time is 2 minutes, the current flow average (as a) is the current flow within 2 minutes, and the flow average (as B) before the preset time is the flow average before 2 minutes which is continuous with the current flow average in time, that is, each flow average is continuous in time and the interval is 2 minutes.
Step S220, if the flow rate is less than 10% of the average flow rate before the preset time, the working mode of the network camera device is judged to be a mobile detection mode;
in this embodiment, it is first determined whether a is smaller than B × 10%, which is to determine whether the flow of the IPC device has a cliff-type decrease smaller than one tenth of the average of the previous flow, for example, the current flow average is 100kb/s and suddenly decreases to 9kb/s, and then 9kb/s is smaller than 100 × 10% kb/s, which is the cliff-type decrease with sudden flow.
Step S230, if not less than 10% of the flow average value before the preset time, determining whether the difference between the current flow average value and the flow average value before the preset time is less than 20%;
further, if the flow rate is not reduced in the cliff-type manner, whether the flow rate average value of the IPC equipment is kept in a certain numerical range or not is further judged, and the change in the range is small, namely, the difference between the front and the back is less than 20%.
Typically, it may be about 100kb/s, for example, in the range of 80-120 kb/s. The 100KB/s flow average mentioned in this example was obtained from (storage capacity/(days storable 24 × 3600)) based on laboratory data provided by the manufacturer. IPC equipment of different manufacturers records under the condition of using different resolutions, and stores video files under the condition of using different coding formats, and the difference between the video files and the average value of the flow is large. For the above scenario, the internet of things analysis device should use the flow average of the actual device counted by itself as a reference.
Step S240, if the difference between the current flow average value and the flow average value before the preset time is less than 20%, determining that the working mode of the network camera device is a real-time monitoring mode.
Step S250, if the difference between the current flow average value and the flow average value before the preset time is not less than 20%, determining that the working mode of the network camera device is the mobile detection mode.
If the flow rate is kept in a certain range and the difference with the previous flow rate mean value is less than 20%, the current working mode can be judged to be a real-time monitoring mode, namely a continuous video recording mode.
The flow average value calculation method comprises the following steps:
and the average flow value is the total flow/preset time of data sent to the network video recording device by the network camera device in the preset time.
As described above, the traffic protocol identification and traffic statistics may use a third party open source library, such as ndip. Specifically, the data interaction between the IPC device and the NVR device may be total data flow/120 s sent by the IPC device to the NVR device within 2 minutes.
In this embodiment, by using the traffic analysis, the traffic between the IPC device and the NVR device can be accurately counted, and the IPC device that does not start the motion detection or does not have the motion detection function is monitored at a high detection rate.
Example 5:
referring to fig. 7, the present embodiment provides a method for detecting missing record in motion detection, based on the foregoing embodiment 1, after "determining whether the operation mode of the network camera is the motion detection mode according to the traffic mean" in step S200, the method further includes:
step S400, if the working mode of the network camera device is a real-time monitoring mode, acquiring a flow average value of the network camera device within preset time at intervals of preset time;
step S500, judging whether the current flow average value is less than 10% of the flow average value before the preset time;
and step S600, if the current flow average value is less than 10% of the flow average value before the preset time, judging that missing recording occurs, and generating missing recording warning information.
As described above, for the IPC device operating in the real-time monitoring mode, the internet of things analysis device is used to monitor the RTSP traffic between the IPC device and the NVR device in real time, if the cliff-type traffic is reduced (less than one tenth of the mean traffic), the IPC device has a miss-recording problem, and at this time, the internet of things analysis device marks that the status of the IPC device is abnormal, and a miss-recording warning message can be generated.
After step S600, the process may return to step S324 to perform further reconfirmation of the result, thereby improving the accuracy of the determination result and preventing prejudgment.
Further, after step S500, the method further includes:
and if the current flow average value is not less than 10% of the flow average value before the preset time, judging that the working state of the network camera device is normal.
Example 6:
in addition, to better explain the method for detecting missing record in motion detection provided in the present application, the following method is used to further explain the steps in the method, and specifically includes the following steps:
scheme 1: video miss detection by traffic analysis (see flow charts in fig. 8-9):
and S10, mirroring the flow of the router or the switch in the network environment where the NVR equipment is located to the Internet of things analysis equipment, and identifying the network equipment existing in the network environment.
And S11, recording the IPC equipment according to the network equipment identified in the S10, and ignoring other equipment.
S12, firstly, counting the RTSP flow size sent to the NVR equipment by the IPC equipment within 2 minutes through the Internet of things analysis equipment (a third-party open source library such as nDPI can be used for flow protocol identification and flow counting), and preliminarily obtaining a flow average value (total data flow/120 s sent to the NVR equipment by the IPC equipment within 2 minutes) as a reference for subsequent flow analysis.
And S13, judging the current working mode of the IPC equipment according to the flow average value obtained in the step S12. If the flow mean value is about 100KB/s (the flow mean value of 100KB/s mentioned herein is obtained by (memory card storage capacity/(storable days × 24 × 3600)) according to laboratory data provided by manufacturers, IPC devices of different manufacturers record videos under the condition of using different resolutions, record video files under the condition of using different coding formats, and the IPC devices and the flow mean value have great difference and difference, for the above scenario, the internet of things analysis device should use the flow mean value of the actual device counted by the internet of things analysis device as a reference), the IPC devices work in a real-time monitoring mode; if the traffic mean is less than 10KB/s (less than one tenth of the traffic mean), the IPC device operates in the mobile detection mode.
And S14, for the IPC equipment working in the real-time monitoring mode, real-time monitoring the RTSP flow between the IPC equipment and the NVR equipment by using the Internet of things analysis equipment, if the flow of the cliff type is reduced (is less than one tenth of the average value of the flow), the IPC equipment has a problem of missing record, at the moment, the state of the IPC equipment is marked to be abnormal by the Internet of things analysis equipment, and the second step is used for confirming again.
And S15, for the IPC equipment working in the mobile detection mode, analyzing the data stream sent to the NVR equipment by the IPC equipment at regular time (usually 5-10 seconds) by using the Internet of things analysis equipment, and analyzing whether the data stream contains the RTSP stream.
And S16, if the data stream sent to the NVR equipment by the IPC equipment contains the RTSP stream, the IPC equipment works normally, and the Internet of things analysis equipment continues monitoring.
And S17, if the data stream sent by the IPC device to the NVR device does not contain the RTSP stream, the Internet of things analysis device monitors whether the IPC device sends a state message to the NVR device or not in a heartbeat period (the heartbeat period is a period in which the IPC device sends the state to the NVR device, generally, the data stream is sent once in 30s, the IPC devices of different manufacturers possibly have differences, and software can configure the heartbeat monitoring period according to the identified IPC device of the specific manufacturer).
And S18, if the IPC equipment sends the state to the NVR equipment in one heartbeat period, the IPC equipment works normally, and the Internet of things analysis equipment continues monitoring.
And S19, if the IPC equipment does not send the state to the NVR equipment in one heartbeat period, the IPC equipment works abnormally and has the problem of missing records, at the moment, the IPC equipment is marked to be abnormal by the Internet of things analysis equipment, and the IPC equipment is confirmed again by the process 2.
And (2) a flow scheme: NVR linkage reads files, detects missing records:
s20, configuring NVR brand information, logging in an account, a password, a port and monitoring network segment information;
s21, starting a detection thread, receiving the configuration information input in the S20, storing the configuration information in a memory, and persisting the configuration information to a database;
and S22, starting a timing task, logging in NVR equipment according to the information of S20, and reading the video file name within the latest N hours. And synchronously analyzing the start and end time of the video file name.
And (4) judging whether each video file is continuous or not, wherein the discontinuity indicates that video missing recording exists, and generating a piece of alarm information, otherwise, continuing to use the flow 3 for final confirmation.
And (3) a flow path: NVR linkage movement detection, monitoring missing recording:
s30, configuring NVR brand information, logging in an account, a password, a port and monitoring network segment information;
s31, starting a detection thread, receiving the configuration information input in the S30, storing the configuration information in a memory, and persisting the configuration information to a database;
s32, starting a timing task, logging in NVR equipment by depending on the information of S30, and acquiring the information of the started mobile detection channel;
s33, reading the starting of the mobile detection alarm and ending the log; or by subscribing the mobile detection alarm, acquiring the starting time and the ending time of the mobile detection;
and S34, the starting time of the motion detection is not read, which indicates that the video recording is not started, and the processing is not performed temporarily.
And S35, acquiring the starting time of the mobile detection, wherein the video is recorded and is not processed temporarily.
S36, acquiring the starting and ending time of the mobile detection; synchronously reading the video files in the range, and analyzing the start time and the end time of the video; and judging whether video files exist in the starting and ending time periods of the mobile detection. If the missing is detected, the missing record is indicated in the missing time period, and an alarm message is generated.
Otherwise, marking the IPC equipment information, recording abnormal statistics times, and reusing the first step to perform missing record detection. And when the abnormal counting times reach 3 times, generating a software abnormal alarm to prompt a user to check the IPC equipment and the Internet of things analysis equipment, and clearing the abnormal counting times of the IPC equipment.
In addition, referring to fig. 10, the present invention further provides a motion detection device for detecting missing records, including:
the acquisition module 10 is configured to acquire a flow average value of a network camera device in a network environment within a preset time every preset time interval;
the judging module 20 is configured to judge whether the working mode of the network camera device is a mobile detection mode according to the flow average value;
and the analysis module 30 is configured to, when the working mode of the network camera device is the mobile detection mode, analyze an interactive data stream between the network camera device and a network video recording device corresponding to the network camera device, and determine whether the network camera device is missed in recording through the interactive data stream.
In addition, the invention also provides a mobile detection missing record detection system, which comprises a terminal and a server side; the terminal and the server comprise memories and processors, the memories are used for storing mobile detection missing record detection programs, and the processors run the mobile detection missing record detection programs so that the mobile detection missing record detection system can execute the mobile detection missing record detection method.
In addition, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a motion detection missing record detection program, and the motion detection missing record detection program is executed by a processor to implement the motion detection missing record detection method.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention. The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (7)
1. A method for detecting a mobile detection miss, comprising:
acquiring a flow average value of a network camera device in a network environment within preset time every preset time;
judging whether the working mode of the network camera device is a mobile detection mode or not according to the flow mean value;
if the working mode of the network camera device is a mobile detection mode, judging whether the data stream between the network camera device and the network video recording device corresponding to the network camera device contains a real-time stream transmission protocol data stream;
if the network video recording device does not contain the real-time streaming protocol data stream, judging whether the network video recording device sends state information to the network video recording device in a heartbeat period; if the network camera device sends state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in a normal working state; if the network camera device does not send state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in an abnormal working state;
if the network camera device is in an abnormal working state, acquiring video file names of all video files in a preset video time corresponding to the network camera device in the network video recording device, and acquiring video recording start time and video recording end time of all the video files according to the video file names;
and judging whether all the video files are continuous or not according to the video recording starting time and the video recording ending time, if not, judging that the missing recording occurs, and generating a missing recording warning message.
2. The method as claimed in claim 1, wherein said determining whether all video files are consecutive according to the recording start time and the recording end time further comprises:
if the network video recording device is continuous, judging whether the network video recording device contains a mobile detection starting log of the network camera device and a mobile detection ending log corresponding to the mobile detection starting log;
if the mobile detection start log and the mobile detection end log are contained, acquiring the mobile detection start time in the mobile detection start log and the mobile detection end time in the mobile detection end log;
judging whether the motion detection starting time and the motion detection ending time range contain corresponding video files or not;
and if the corresponding video file is not contained, judging that the missing record occurs, and generating missing record warning information.
3. The method as claimed in claim 2, wherein after determining that the skip occurs and generating the skip warning message if the video file does not contain the corresponding video file, the method further comprises:
marking the network camera device and recording abnormal counting times corresponding to the missing record warning information;
and if the abnormal counting times are not less than the preset counting times, generating a software abnormal alarm, and clearing the abnormal counting times of the network camera device.
4. The method as claimed in claim 1, wherein the determining whether the operation mode of the network camera is the motion detection mode according to the traffic mean value comprises:
judging whether the current flow average value is less than 10% of the flow average value before the preset time;
if the average value of the flow before the preset time is less than 10%, judging that the working mode of the network camera device is a mobile detection mode;
if the current flow average value is not less than 10% of the flow average value before the preset time, judging whether the difference between the current flow average value and the flow average value before the preset time is less than 20% of the flow average value before the preset time;
if the difference between the current flow average value and the flow average value before the preset time is less than 20% of the flow average value before the preset time, judging that the working mode of the network camera device is a real-time monitoring mode;
and if the difference between the current flow average value and the flow average value before the preset time is not less than 20% of the flow average value before the preset time, judging that the working mode of the network camera device is a mobile detection mode.
5. The method of claim 1, wherein the flow mean is calculated by:
and the average flow value is the total flow/preset time of data sent to the network video recording device by the network camera device in the preset time.
6. The method as claimed in claim 1, wherein after determining whether the operation mode of the network camera is the mobile detection mode according to the traffic mean value, the method further comprises:
if the working mode of the network camera device is a real-time monitoring mode, acquiring a flow average value of the network camera device within a preset time at intervals of preset time;
judging whether the current flow average value is less than 10% of the flow average value before the preset time;
and if the current flow average value is less than 10% of the flow average value before the preset time, judging that missing recording occurs, and generating missing recording warning information.
7. A mobile detection device for detecting missing records, comprising:
the acquisition module is used for acquiring the flow average value of the network camera device in the network environment within the preset time at each interval of preset time;
the judging module is used for judging whether the working mode of the network camera device is a mobile detection mode according to the flow mean value;
the analysis module is used for judging whether the data stream between the network camera device and the network video recording device corresponding to the network camera device comprises a real-time stream transmission protocol data stream or not when the working mode of the network camera device is a mobile detection mode;
if the network video recording device does not contain the real-time streaming protocol data stream, judging whether the network video recording device sends state information to the network video recording device in a heartbeat period; if the network camera device sends state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in a normal working state; if the network camera device does not send state information to the network video recording device in a heartbeat cycle, judging that the network camera device is in an abnormal working state;
if the network camera device is in an abnormal working state, acquiring video file names of all video files in a preset video time corresponding to the network camera device in the network video recording device, and acquiring video recording start time and video recording end time of all the video files according to the video file names;
and judging whether all the video files are continuous or not according to the video recording starting time and the video recording ending time, if not, judging that the missing recording occurs, and generating a missing recording warning message.
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