1. Industry background
There is a close correlation and wide application between big data technology and video surveillance. With the popularity and digitization of cameras and video surveillance systems, the amount of data generated by video surveillance systems is also increasing. Big data technology can help video surveillance systems better manage, analyze and utilize these data, improving the performance and value of video surveillance systems.
Big data technology can integrate and analyze video surveillance data with other data sources to provide more comprehensive information. For example, integrating and analyzing video surveillance data with other data such as traffic flow data and personnel entry and exit records can provide more accurate traffic situation assessments and safety risk warnings.
2. Plan Overview
Video resource network aggregation is the basic core capability of the video aggregation and fusion sharing platform solution. Only through effective networking to aggregate various video resources to form a unified data center, upper-layer basic applications and AI intelligent analysis can be built. Through deep learning algorithms, video data can be automatically recognized and classified, such as identifying specific targets such as faces and license plates, to provide accurate data support for relevant application scenarios. At the same time, big data technology can also provide more accurate behavioral predictions and early warnings through historical data analysis and pattern recognition.
The video aggregation and fusion platform LiteCVR supports multi-protocol and multi-type device access. It can integrate and manage video resources of different brands and different protocols in a unified manner, realize the aggregation of big data of video image resources in one network, and build a video data resource pool. By building a video resource directory, we provide rich, real-time, high-definition video resources for various business scenarios to meet diverse video resource scheduling and business usage needs.
3. Technology application
1) Video playback
Realize efficient basic services such as video collection, encoding, and storage, as well as video content concentration and structuring, and provide stable and smooth data services for each platform module and subsystem, thereby realizing video-based viewing, checking, management, control, and use. and other functions. The system can live broadcast the monitoring images of the channels in each area of the site, and managers can view them through various device terminals such as web pages, mobile clients, and PCs. The video images support multi-screen display, including 1, 4, 9, and 16.
2) Unified access and centralized management
The LiteCVR system can centralize video resources from various types of devices and independent platforms into the video aggregation platform for effective unified management. The protocols that the system can support include: national standard GB28181 protocol, RTMP, RTSP/Onvif, Hikvision Ehome, as well as Hikvision SDK, Dahua SDK, Huawei SDK, Uniview SDK, Lecheng SDK, EZVIZ SDK, etc. The types of devices that can support access include: IPC, NVR, video encoder, drone, vehicle monitoring, vehicle equipment, mobile law enforcement instrument, mobile individual soldier, handheld intelligent terminal, intelligent all-in-one machine, etc.
3) Video recording and storage
LiteCVR supports centralized and structured storage of video content centers. The platform supports 7*24h recording and provides functions such as recording, retrieval, playback, cloud storage, centralized storage, and disk array storage.
Big data technology can provide powerful data storage and processing capabilities and can carry large-scale video data. Various surveillance videos, images and other related data in the video surveillance system can be efficiently stored and managed through the big data platform to ensure the reliability and availability of the data.
4) Support face structuring/vehicle structuring
The system seamlessly connects to the AI algorithm center, and through real-time data processing and analysis, it can quickly discover and identify abnormal behaviors in video surveillance, and provide real-time monitoring and alarm services. For example, through facial recognition technology and behavioral analysis algorithms, abnormal situations such as crowd gatherings and illegal behaviors can be detected in real time and corresponding measures can be taken in a timely manner. AI algorithms can include face structured data, vehicle structured data, scene detection algorithms, industry detection algorithms, etc., covering AI algorithms in most fields and industries such as cities, construction sites, urban management, water conservancy, environmental protection, fire protection, communities, campuses, etc. Computing power requirements.
5) Third-party integration
The platform is simple to deploy, its functions can be flexibly and easily expanded, it provides standard API interfaces, supports independent calls and secondary opening, and can be easily integrated with third parties.
Big data technology is closely related and applied to LiteCVR video surveillance. Big data technology can provide data storage, processing and analysis capabilities, realize real-time processing and analysis of video surveillance data, provide accurate monitoring results and early warning services, and integrate and analyze video surveillance data with other data sources to provide a more comprehensive information support.