Video Surveillance Applications
The global video surveillance market was valued at $42.94 billion in 2019, and is projected to reach $144.85 billion by 2027, registering a CAGR of approximately 14.6% from 2020 to 2027. Increasing concerns about public safety and security, growing adoption of IP cameras, and rising demand for wireless cameras are factors driving the growth of the video surveillance industry.
The massive amounts of data being collected by cameras and IoT devices has led to advanced and creative uses for the video and data being generated by these devices. Analyzing this data can generate actionable real time intelligence for multiple environments.
Big Data and AI are becoming key to developing surveillance technology with real-time predictive capabilities. By 2025, an average connected person anywhere in the world will interact with connected devices – computers, mobile devices, smart TVs and more – nearly 4,800 times a day. That’s essentially one interaction every 18 seconds. In the next few years, an additional 26+ billion sensors will be installed worldwide to help manage, monitor and improve our daily lives. The ability to store and process this data rapidly has become an essential element of any strong surveillance solution.
Explosive Data Growth
IDC estimates the amount of data generated worldwide that is subject to data analysis will grow by a factor of 50 to 5.2 zettabytes by 2025, with the amount of data that is “touched” by cognitive systems growing by a factor of 100 to 1.4 zettabytes in that same timeframe.
The ultimate value of all this data that is generated will be directly tied to our ability to analyze and distill it into actionable intelligence that can be used to increase security and improve operations. This requirement for analysis paves the way for a new set of technologies including machine learning, natural language processing and artificial intelligence to be deployed in intelligent surveillance systems, capable of storing and processing massive amounts of unstructured information.
Collectively, machine learning, AI and natural language processing are referred to as cognitive systems, and they are capable of taking unstructured data, and probabilistically processing the data in order to interpret that information, organize it and offer explanations as to what it means, which then augments our ability to take strategic action and make better informed decisions. Cognitive computing is already being used to assist with health care, banking, insurance, customer service, robotics, autonomous vehicles, flight systems and transportation, just to name a few. These evolving cognitive computing models provide a good glimpse of some of the ways these system applications will enhance and transform human lives across CGS in the years ahead.
From a security standpoint, AI opens the door for intelligent real-time video analysis that can transition today’s ultra-high-resolution video from a tool used primarily for reactionary, post-incident investigation to a more proactive tool that enables preemptive action. AI allows security integrators and to identify specific events and triggers in the recorded footage. The ability to capture scene footage with this knowledge and insight enables more accurate alerts and forensics, dramatically reducing the time to act and analyze the video manually.
High Performance Surveillance Storage
From a video storage solutions perspective, these trends have instigated a shift from primarily write-only applications toward constant, ongoing deep learning and analysis that produce and process unstructured data. Until recently, these systems relied on the processing power of cloud data centers to manage this analysis, but that model is burdened with issues around latency.
To overcome these latency issues, AI is now being built into more NVR (network video recorder) systems to enable them to process, analyze and recognize patterns on-site in real time at the edge, rather than dealing with the latency associated with transferring data and video off-site to a datacenter for analysis. What has spurred this AI evolution, particularly in edge video surveillance applications, is significantly cheaper and faster GPU’s with practically limitless storage. Hard drives must be capable of writing and reading data at very high speeds to keep up with these AI applications and simultaneously support both AI and video workloads. Solid State Disks, unlike other storage devices, are able to process this data very quickly and are ideal for these types of surveillance solutions, in whole or as part of a hybrid storage system solution.
Selecting the Right Storage Solution
The massive amounts of video being captured by surveillance systems and smart devices are creating the need for more advanced storage options that are optimized for machine learning, deep learning, high-resolution video, advanced analytics streaming and more. Systems integrators are looking for reliable, high performance drives that are purpose-built for surveillance that support multiple cameras, 24/7 availability and the capability to maximize streaming and frame rate performance.
Centon Electronics provides a broad portfolio of storage products and technologies that deliver the right combinations of performance, capacity, and reliability to meet the unique needs of today’s surveillance solutions and AI-enabled intelligent video recording systems.