WO2018161218A1

WO2018161218A1 - Big data sequencing recommendation method and system with monitoring system

Info

Publication number: WO2018161218A1
Application number: PCT/CN2017/075766
Authority: WO
Inventors: 马岩
Original assignee: 深圳市博信诺达经贸咨询有限公司
Priority date: 2017-03-06
Filing date: 2017-03-06
Publication date: 2018-09-13

Abstract

Disclosed in the present invention is a big data sequencing recommendation method with a monitoring system, the method comprising the following steps: a monitoring system extracts figure information from big data; the monitoring system compares the figure information with a wanted person portrait from a public security system; and when the comparison result is a match, the monitoring system recommends the data corresponding to the figure information to a monitoring party. The technical solution provided in the present invention has the advantage of favorable user experience.

Description

Big data sorting recommendation method and system for monitoring system

Technical field

The present invention relates to the field of monitoring, and in particular, to a method and system for recommending big data sorting of a monitoring system.

Background technique

The monitoring system consists of 5 parts: camera, transmission, control, display, and record registration. The camera transmits the video image to the control host through the coaxial video cable, and the control host distributes the video signal to each monitor and recording device, and simultaneously records the voice signal to be transmitted into the recorder. By controlling the host, the operator can issue commands to control the up, down, left, and right movements of the pan/tilt and focus the zoom on the lens, and can be implemented in the multi-channel camera and the pan/tilt by the control host. Switch between. With special recording processing mode, images can be recorded, played back, processed, etc., so that the recording effect is optimal.

The big data video files of the existing monitoring system only have the storage function, and cannot be recommended to the user according to the situation, and the user experience is low.

technical problem

The application provides a method for recommending big data ranking of a monitoring system. It solves the shortcomings of the prior art technical solutions.

Technical solution

In one aspect, a method for recommending a big data ranking of a monitoring system is provided, the method comprising the steps of: monitoring a system to extract character information in big data; and monitoring a system to compare the character information with an image of a wanted person of the public security system; monitoring When the system is consistent, the data corresponding to the character information is recommended to the monitoring party.

Optionally, the method further includes:

The monitoring system sends an alarm message to the public security system, and the alarm message includes: a time interval of the character avatar and the character avatar.

Optionally, the method further includes:

If an abnormal situation occurs within the scope of the monitoring system, all task video files of a section before the abnormal time occurs are recommended to the prosecution party.

In a second aspect, a big data ranking recommendation system for a monitoring system is provided, the system comprising:

a transceiver unit for extracting character information in big data;

The processing unit is configured to compare the character information with the wanted character avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the character information to the monitoring party.

Optionally, the system further includes:

The transceiver unit is configured to send an alarm message to the public security system, where the alarm message includes: a time interval of the character avatar and the character avatar.

Optionally, the system further includes:

The processing unit is configured to recommend, to the prosecution party, all task video files of a section before the abnormality occurrence time, if an abnormal situation occurs within the scope of the monitoring system.

In a third aspect, a monitoring system is provided, including: a processor, a wireless transceiver, a memory, and a bus, wherein the processor, the wireless transceiver, and the memory are connected by a bus.

The wireless transceiver is configured to extract character information in big data;

The processor is configured to compare the character information with the wanted character avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the character information to the monitoring party.

Optionally, the transceiver is configured to send an alarm message to the public security system, where the alarm message includes: a time interval of the character avatar and the character avatar.

Optionally, the processor is configured to recommend, to the prosecution party, all task video files of a segment before the abnormal situation occurs, if an abnormal situation occurs in the monitoring system.

Beneficial effect

The technical solution provided by the present invention recommends a video file to a user according to a specific situation, so it has the advantage of improving user experience.

DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without paying any creative work.

1 is a flowchart of a method for recommending big data sorting of a monitoring system according to a first preferred embodiment of the present invention;

2 is a structural diagram of a big data sorting recommendation system of a monitoring system according to a second preferred embodiment of the present invention.

FIG. 3 is a hardware structural diagram of a monitoring system according to a second preferred embodiment of the present invention.

Embodiments of the invention

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are a part of the embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

Please refer to FIG. 1. FIG. 1 is a method for recommending big data sorting of a monitoring system according to a first preferred embodiment of the present invention. The method is as shown in FIG. 1 and includes the following steps:

Step S101: The monitoring system extracts the character information in the big data.

Step S102: The monitoring system compares the character information with the wanted character of the public security system.

Step S103: The monitoring system recommends the data corresponding to the person information to the monitoring party when the comparison is consistent.

Optionally, the monitoring system sends an alarm message to the public security system, where the alarm message includes: a time interval of the character avatar and the character avatar.

Optionally, if an abnormal situation occurs within the scope of the monitoring system, all videos of a segment before the abnormal time occurs are recommended to the user.

Please refer to FIG. 2. FIG. 2 is a big data sorting recommendation system of a monitoring system according to a second preferred embodiment of the present invention. The system is as shown in FIG. 2, and includes:

The transceiver unit 201 is configured to extract character information in the big data;

The processing unit 202 is configured to compare the person information with the wanted person avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the person information to the monitoring party.

Optionally, the transceiver unit 201 is configured to send an alarm message to the public security system, where the alarm message includes: a time interval of the character avatar and the character avatar.

Optionally, the processing unit 202 is configured to recommend, to the prosecution party, all the task video files of a segment before the abnormal situation occurs, if an abnormal situation occurs within the monitoring system.

Referring to FIG. 3, FIG. 3 is a monitoring system 30, including: a processor 301, a wireless transceiver 302, a memory 303, and a bus 304. The wireless transceiver 302 is configured to transmit and receive data with and from an external device. The number of processors 301 can be one or more. In some embodiments of the present application, processor 301, memory 302, and transceiver 303 may be connected by bus 304 or other means. Monitoring system 30 can be used to perform the steps of FIG. For the meaning and examples of the terms involved in the embodiment, reference may be made to the corresponding embodiment of FIG. 1. I will not repeat them here.

The wireless transceiver 302 is configured to extract character information in big data.

The program code is stored in the memory 303. The processor 901 is configured to call the program code stored in the memory 903 for performing the following operations:

The processor 301 is configured to compare the person information with the wanted character avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the person information to the monitoring party.

It should be noted that the processor 301 herein may be a processing component or a general term of multiple processing components. For example, the processing element can be a central processor (Central) Processing Unit, CPU), or a specific integrated circuit (Application Specific Integrated) Circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present application, such as one or more microprocessors (digital singnal Processor, DSP), or one or more Field Programmable Gate Arrays (FPGAs).

The memory 303 may be a storage device or a collective name of a plurality of storage elements, and is used to store executable program code or parameters, data, and the like required for the application running device to operate. And the memory 303 may include random access memory (RAM), and may also include non-volatile memory (non-volatile memory) Memory), such as disk storage, flash (Flash), etc.

Bus 304 can be an industry standard architecture (Industry Standard Architecture, ISA) bus, Peripheral Component (PCI) bus or extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 3, but it does not mean that there is only one bus or one type of bus.

The terminal may further include input and output means connected to the bus 304 for connection to other parts such as the processor 301 via the bus. The input/output device can provide an input interface for the operator, so that the operator can select the control item through the input interface, and can also be other interfaces through which other devices can be externally connected.

It should be noted that, for the foregoing various method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should understand that the present invention is not limited by the described action sequence. Because certain steps may be performed in other sequences or concurrently in accordance with the present invention. In addition, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the above embodiments, the descriptions of the various embodiments are different, and the parts that are not described in detail in a certain embodiment can be referred to the related descriptions of other embodiments.

A person skilled in the art may understand that all or part of the various steps of the foregoing embodiments may be performed by a program to instruct related hardware. The program may be stored in a computer readable storage medium, and the storage medium may include: Flash drive, read-only memory (English: Read-Only Memory, referred to as: ROM), random accessor (English: Random Access Memory, referred to as: RAM), disk or CD.

The content downloading method and the related device and system provided by the embodiments of the present invention are described in detail above. The principles and implementation manners of the present invention are described in the specific examples. The description of the above embodiments is only used to help understand the present invention. The method of the invention and its core idea; at the same time, for the person of ordinary skill in the art, according to the idea of the present invention, there are some changes in the specific embodiment and the scope of application. In summary, the content of the specification should not be understood. To limit the invention.

Claims

A method for recommending big data sorting of a monitoring system, characterized in that the method comprises the following steps:

The monitoring system extracts the character information in the big data;

The monitoring system compares the character information with the wanted characters of the public security system;

When the monitoring system is consistent, the data corresponding to the character information is recommended to the monitoring party.
The method of claim 1 further comprising:

The monitoring system sends an alarm message to the public security system, and the alarm message includes: a time interval of the character avatar and the character avatar.
The method of claim 2, wherein the method further comprises:

If an abnormal situation occurs within the scope of the monitoring system, all task video files of a section before the abnormal time occurs are recommended to the prosecution party.
A big data ranking recommendation system for a monitoring system, characterized in that the system comprises:

a transceiver unit for extracting character information in big data;

The processing unit is configured to compare the character information with the wanted character avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the character information to the monitoring party.
The system of claim 4, wherein the system further comprises:

The transceiver unit is configured to send an alarm message to the public security system, where the alarm message includes: a time interval of the character avatar and the character avatar.
The system of claim 5, wherein the system further comprises:

The processing unit is configured to recommend, to the prosecution party, all task video files of a section before the abnormality occurrence time, if an abnormal situation occurs within the scope of the monitoring system.
A monitoring system includes: a processor, a wireless transceiver, a memory, and a bus, wherein the processor, the wireless transceiver, and the memory are connected by a bus, wherein

The wireless transceiver is configured to extract character information in big data;

The processor is configured to compare the character information with the wanted character avatar of the public security system, and when the comparison is consistent, recommend the data corresponding to the character information to the monitoring party.
The monitoring system according to claim 7, wherein the transceiver is configured to send an alarm message to the public security system, the alarm message comprising: a time interval of the character avatar and the character avatar.
The monitoring system according to claim 7, wherein the processor is configured to recommend, to the prosecution party, all task video files of a section before the abnormality occurrence time, if an abnormal situation occurs within the monitoring system.