In the realm of big data security, one of the most direct applications is in the development of smart cities. As the volume of data generated continues to grow, it has gradually been used to build safer urban environments, particularly in the field of Digital Security Surveillance (DSS), which is primarily based on video monitoring. Cities today are filled with countless high-definition cameras that support public safety monitoring, command and communication, investigation and detection, law enforcement, and social services. The scale of video access ranges from thousands to hundreds of thousands, generating massive amounts of data every day. This complexity makes data analysis extremely challenging.
In early 2013, the Nanjing police needed to capture a fugitive suspect, and they mobilized over two thousand officers. At that time, most cameras were not connected to the internet, so they had to manually collect footage by visiting various communities, police stations, and buildings. At that point, the entire city could purchase storage, and almost all equipment was owned by the police. This case highlighted three key points: first, data must be networked; second, large volumes of data need proper storage; and third, these large datasets must be analyzed and mined to unlock their true value.
The process of building a safe city involves handling massive amounts of data. From analog to digital, from SD to HD, from DVR to NVR, and from traditional video surveillance to the Internet of Things, the big data revolution has already begun in the security industry. Advanced and comprehensive big data solutions should cover computing, networking, storage, security, and management platforms, making unstructured and fragmented data more manageable and valuable.
It is predicted that data will increase 44 times over the next decade, with 80% being unstructured. According to the China Internet Society, data from mobile communications, social networks, video surveillance, and environmental monitoring are all growing rapidly. These data types are characterized by their massive volume, diversity, and speed. Unlike traditional database data, they are harder to manage and analyze but also demand higher performance from the IT industry.
Intel's Big Data Solution for Smart Security
Intel's approach focuses on implementing end-to-end data mining, analysis, management, and transmission within the security industry. Its comprehensive big data solutions include computing, networking, storage, security, and management platforms to meet the diverse needs of the security sector. The computing platform includes entry-level Atom and Core processors, as well as high-performance Xeon processors. In networking, Intel offers Gigabit and 10 Gigabit network cards. As a key Hadoop partner, Intel provides distribution support for managing and processing massive data, enabling partners to integrate their innovations more easily on this open platform. By acquiring McAfee, Intel can offer reliable security solutions. Intel’s NM node management helps reduce energy consumption in back-office operations.
These Intel-based technologies are not only widely used in backend systems but also play a crucial role in DSS front-end and edge devices. The front end consists of numerous X86-based terminal devices, while edge servers handle access, and background servers perform storage and analysis. Through distributed file systems, massive data is structured, analyzed, and transformed into real-time databases, turning unstructured and fragmented data into something more manageable and valuable.
This end-to-end security solution helps DSS developers shorten product development cycles and reduce costs. Additionally, powerful computing performance and an open platform based on internet applications accelerate the security industry’s digitalization, high definition, and the pace of intelligent and networked development.
Application of Big Data Security in Intelligent Transportation
In the field of intelligent security, there are different opinions about where intelligence should be placed. Some believe in intelligent analysis through cameras, others suggest edge processing on NVR or DVR servers, while I think the background is the right place because the front end is cost-effective and reliable. Intel believes that smart applications can be implemented across all three nodes.
Take intelligent transportation as an example. Whether it’s abstract images or videos, there are many redundant and meaningless elements. Extracting valuable information and sending it to the background can significantly reduce bandwidth pressure and backend workload. According to IHS forecasts, by the end of 2017, the transportation system produced 457 PB of raw video data per day. Real-time video analytics can reduce this data by 60%, solving bandwidth and storage issues. More importantly, these extracted elements include personal features that provide input for future intelligent analysis, such as vector data.
Through video intelligence analysis, functions like license plate recognition, traffic statistics, and red-light violations can be achieved. While video intelligence is still evolving, the challenge lies in integrating it with embedded devices for efficient coding, compilation, and tuning. With the introduction of X86 architecture into the security industry, these tasks have become easier. In June, Intel released the fourth-generation Core processor series, significantly improving graphics (GPU) performance, computing power, and energy efficiency, making it suitable for connected, managed, and secure intelligent systems. The GPU comes with a media software development kit (SDK) to help leverage graphics performance. When hardware acceleration is utilized, the CPU can focus on complex operations. The SDK also helps engineers develop modular intelligent analysis software. Even as the Intel platform evolves, applications built using the SDK can be easily reused, saving costs through existing open-source code.
Working together with the ecosystem to build a safe city
In the DSS field, Intel has collaborated closely with ecosystem partners such as accessories manufacturers, middleware providers, system integrators, and solution providers to successfully serve major security projects like the Beijing Olympics, Shanghai World Expo, Guangzhou Asian Games, and Shenzhen Universiade. Companies like Bokang Intelligent Network Technology, Hikvision, Dongfang Netpower, North China Industrial Control, Kyushu Chuangguan, EVOC, and China Security have partnered with Intel to launch various intelligent digital surveillance solutions based on Intel architecture.
As the largest X86 system ODM manufacturer in China, Shenzhen Zhiwei Intelligent Technology Development Co., Ltd. (JWIPC) has completed the full industrial chain layout under the X86 architecture, including the intelligent security field. JWIPC aims to replicate the “Data Center + Large Network†system model in areas beyond IT, with its primary application being security. Its NVR series, based on Atom, Core, and Xeon processors, offers a first-mover advantage in new technology and customized development capabilities. Despite entering the security industry relatively recently, JWIPC quickly gained a foothold with its NVR products, meeting the rising demand for high-definition and intelligent security solutions.
The big data wave in the security industry has already arrived, and the integration of IT technology is set to transform traditional patterns. Intel is committed to working with partners to help build China’s “Safe City†initiative and create a better future for Chinese cities.
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