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With the development of information technology, human beings have entered the information society. Information technology has provided people with a new kind of production and lifestyle, and deeply influenced the political, economic, scientific and technological fields of human society. Over the years, with the simultaneous development of the Internet and information technology, a large amount of data has been accumulated in all walks of life. According to Gartner, the world's leading information technology research and consulting company, the important factors driving the development of big data come from two aspects: one is the large amount of data generated by the consumer sector, such as online shopping and social media applications; on the other hand, it comes from urban infrastructure construction. Security is one of them.
Multiple types of security data hit
In the security industry, there are many types of data information involved. In terms of the type of data structure, it includes various types of unstructured, structured, and semi-structured information. Unstructured data mainly refers to video recording and picture recording, such as surveillance video recording, alarm recording, summary recording, vehicle bayonet picture, face capture picture, alarm capture picture, etc.; structured data includes alarm record, system log record, Operation and maintenance data records, summary analysis of structured description records, and various related information databases, such as population information, geographic data information, vehicle management information, etc.; semi-structured data such as face modeling data, fingerprint records, and so on.
The source of this information has several channels, one is the information generated inside the security system, such as various video recordings, snapshot pictures, system operation and maintenance data, log records, summary records, etc.; others are collected or integrated through external systems. Such as population information, geographic data information, face database data, vehicle management data. These data as a whole constitute the big data foundation of the security system or security field, and have the following characteristics: The most significant is that the security data volume is huge and constantly expanding, with the continuous networking and integration of the video surveillance image system. As well as the video resolution and frame rate continue to increase, the storage of real-time video data has jumped from the TB level to the PB level; secondly, security data types are numerous, such as the video, picture, geographical location information mentioned above, etc. Moreover, with the continuous integration of various security systems and related information systems, there will be more and more data types. In addition, the security data has a low value density but high value. Taking video surveillance data as an example, in a 7*24 hour continuous uninterrupted monitoring process, the data that may be useful is only one or two minutes, or even one or two seconds. At the same time, these information are updated frequently, security data is generated in large numbers every moment, and information is updated every moment.
To quickly and efficiently filter effective information from these small amounts of information, security vendors need the following two foundations: First, we need to improve the processing power and efficiency of unstructured information, accurately and quickly process video images, and face features. The data such as the model extracts useful information from it, and can perform some representation of the information, and complete the extraction and storage of the data information on the storage level of the big data, so as to perform subsequent data information retrieval, analysis and mining business. Secondly, through the use and targeted improvement of the current big data processing technology and platform framework, providing a fast retrieval mechanism for security data information, forming a targeted massive security data information processing architecture, from these large number of structured and semi-structured Quickly retrieve and analyze information.
The application of big data in the security industry
Security data is still dominated by unstructured information such as image and video, so it has its own characteristics in the analysis and processing of big data. In addition to the conventional information retrieval, the security industry is more focused on information retrieval of graphic images; current IT Big data generally focuses on analyzing and retrieving textual data. Therefore, for the security community, there are two main types of processing and analysis tools for big data in the security community. One is the processing and analysis of unstructured information such as video images. Tools, including video intelligence analysis tools, video summary tools, image sharpening tools, video sharpening tools, video transcoding tools, video editing tools, and more. The other is the big data analysis processing tool for structured and semi-structured information. In this respect, the security community draws on the architecture and experience of the IT community in processing big data. For structured and semi-structured data, Achieve fast and accurate data analysis and mining. Throughout the security field, Ping An City is the largest and most complex system, involving multiple areas such as security monitoring, command and communication, investigation and resolution, law enforcement, and social services. Video access scales range from thousands to tens With the increasing demand for high-definition, intelligent, and networked security monitoring, the daily data generated by the Ping An City project is growing at an alarming rate.
However, the application of big data technology in security fields is not as mature as in the IT and Internet industries, and the related information collision and mining needs have not yet formed a model. In the face of increasingly large data, how to achieve comprehensive application and accurate analysis of massive video data is the pain point of Big City in Ping'an City, and it also determines that it needs big data technology to support it. In all kinds of safe city construction projects, relying on big data analysis technology to extract effective security information from massive video images has long been a consensus in the security community. Facing the coming of the era, in the field of data collection, convergence and application. Continuous exploration, the first to introduce the industry's first complete integrated image processing application for public security image information. The solution is based on the integrated application platform of image information and corresponding management and control software, which can integrate various internal and external image information resources of public security into image resources. Library, and organizes, classifies and stores audio and video image information of various departments and police types, and establishes index summary to facilitate evidence search and case correlation analysis. The image resource library also has complete query, information comparison, archiving and storage. Function, and adopt dynamic management mode to ensure timely, accurate and effective information, so as to facilitate resource sharing in the province.
After completing the collection and sorting of a large amount of data, the whole program can realize the functions of video data resource reading, intelligent analysis application, online inspector, public security prevention and control, intelligent transportation, image investigation and judgment, information reporting, image resource library, etc. The value information behind the massive video surveillance data, fast feedback information to assist decision-making judgment.
Taking intelligent transportation as an example, the smart bayonet subsystem introduces data deep mining and analysis technology into the traditional security card bay, and implants several sets of license plate map detection methods, through car correlation analysis, path correlation analysis, regional data collision analysis, etc. The data mining function is combined with the actual application, and the analysis of the bayonet data is used to find out the regularity, narrow the scope of investigation, improve the early warning capability of the traffic police and the efficiency of handling the case. When the vehicle continuously passes through multiple intersections, the system can display all the information of the vehicle in the time series according to the license plate number and the license plate color according to the license plate number and the license plate color in the specified time range, and the parallel electronic map is displayed. Presenting its driving trajectory for automatic behavior analysis.
In the process of public security case handling, the image investigation and judgment subsystem has been highly praised in the public security industry because it allows the police to handle the case from the massive data. The image detection research and judgment subsystem performs data information flow according to the graph investigation and judgment process, and various intelligent image processing softwares perform unified transcoding, abstract processing, video editing, video feature extraction and image sharpening processing on video images, and at the same time, the warfare method and process The organic combination forms a complete set of technical warfare application methods, and completes the rapid analysis and comparison analysis of the case under different circumstances, so that the police can intelligently locate the key points in the massive information, maximize the processing results, and shorten the video analysis time. Thereby effectively reducing the time for manual viewing of video, reducing manpower input, intelligently promoting the rapid development of video analysis of cases, providing an important method and basis for the cracking of cases.
Big data test storage capacity
From the current security system architecture, security big data transmission channels are mainly network, generally adopt networked aggregation, hierarchical storage mechanism, the network is generally Gigabit network, storage is also based on general disk array storage. In order to meet the requirements of security information integration, security data analysis and information mining, security systems gradually tend to be interconnected and integrated, and security data information is gradually converged and integrated, and 10G network centralized aggregation management appears, and cloud storage is used as video. The trend of image data storage platforms. At present, cloud storage has become the core technology of security big data, and various manufacturers are also making efforts to improve their research and development capabilities.
Compared with traditional storage devices, cloud storage is more than just a piece of hardware, but a complex system consisting of multiple parts such as network devices, storage devices, servers, application software, public access interfaces, access networks, and client programs. Cloud storage can provide bare space services like disk arrays, as well as specific services based on storage. For example, cloud storage can provide storage services for multiple subsystems in the safe city system, including video surveillance, bayonet alarm, image resource library, and graph analysis analysis. It can complete the daily video recording resources, the video and picture resources involved in each case, and the unified storage of resources such as vehicle capture pictures generated by the bayonet police.
From the perspective of application architecture, the difference between cloud storage systems and traditional distributed storage systems is not obvious, and its more essential difference is the entity's internal software architecture. The cloud storage system adopts a large-scale distributed parallel file system, based on a large number of servers and storage devices, builds a large-scale storage cluster, provides storage capacity of hundreds of PBs, and can expand capacity online, thereby building a large The overall cost of a capacity storage system is much lower than that of a traditional storage architecture, and it has good scalability and flexibility.
The cloud storage system uses an asymmetric architecture separated from metadata and storage data to achieve a transmission rate of up to tens of Gbps and a storage capacity of hundreds of petabytes under normal hardware conditions through load balancing and data concurrent access policies. The trend of user application development, online dynamic expansion as needed. Different from the file system of a single machine, the distributed file system does not put the data on a disk and is managed by the upper layer operating system, but is stored on a server cluster. The servers in the cluster do their best to cooperate and cooperate. Provides services for the entire file system.
The cloud storage system has built-in object-based data management strategy to ensure data security and reliability in the event of partial system failure, completely eliminate single point of failure in the storage system, and combine automatic fault detection and fast fault recovery technology to ensure users' Applications continue to run steadily while reducing the difficulty of deployment and management. Take the cloud storage system as an example. Traditional storage devices usually use RAID to perform redundant backup. When a hard disk is damaged, the RAID reconstruction time usually takes more than ten hours. If the hard disk is broken, the data cannot be used. Recovery, so maintenance personnel need to rush to the site to replace the hard disk in the first time, 7 × 24 hours standby; cloud storage uses a distributed file system, data storage and backup no longer rely on the ability of a single device, when the hard disk is broken The rest of the hard drive will be automatically rebuilt to recover the damaged data. It only takes ten minutes. The maintenance personnel only need to check the damage of the hard disk regularly and replace the new hard disk. The maintenance is very simple.
Opportunities and challenges coexist
The data is getting bigger and bigger, and the more business information accumulated, the greater the value. Big data, which is characterized by massive, diverse, and fast, is not as easy to manage and analyze as traditional database data. It brings opportunities to the entire IT and communications industry, but it also raises higher requirements.
For example, security issues, data security is a problem in the entire IT industry, and in the security field is no exception, security threats and various damages and attacks encountered in the IT field will also be encountered in the security field. For the security field, the amount of data is large, the amount of information contained in image information is more, and it also involves personal privacy, public safety and other issues. Therefore, system security cannot be ignored, but related technologies and countries of equipment vendors The legal norms cannot be achieved overnight.
At present, the security industry has entered the big data era with one foot, but it has not yet fully entered. The reason for this is that the current data volume of security systems is indeed expanding, the emergence of high-definition video, the continuous advancement of security system networking and integration, the improvement of storage technology and capacity, resulting in huge data volume, highlighting the characteristics of big data. Such a security system is destined to be a large collection of data, but currently a large amount of video data is still independent and fragmented. The video recording data is spread in various industries and independent systems. It does not play a real network and share, and the industry has not formed a general method for data mining and utilization.
In addition, in the relevant IT infrastructure, intelligent analysis and retrieval of video image information, the organization and management of security data, data analysis and mining algorithm modeling and implementation, it is necessary to fully introduce innovative technologies. While security systems and applications are well-established, security companies need to strengthen their internal strengths, improve their R&D capabilities, strengthen their technology reserves, cope with the impact of greater data volumes, and improve their ability to handle and utilize big data, especially at the moment. The improved video intelligence application and the accuracy of video intelligence analysis are all issues that the security industry needs to solve before entering the big data era.
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April 22, 2023