Samehra Malik, Senior Channel Marketing Manager at Seagate Technology, looks at the impact AI could have on the future of surveillance systems.
In the rapidly evolving landscape of security and surveillance systems, the integration of artificial intelligence (AI) has ushered in a new era of efficiency and effectiveness.
AI-driven surveillance systems are transforming how organisations monitor, analyse and respond to security events.
Central to this transformation is the critical role of data storage solutions, which must not only accommodate the vast amounts of data generated but also support the intensive processing demands of AI analytics.
The proliferation of connected devices and the Internet of Things (IoT) has led to an exponential increase in data generation.
By 2025, it is anticipated that an average connected individual will interact with connected devices nearly 4,800 times per day, equating to an interaction every 18 seconds.
This surge is further amplified by the expected installation of an additional 26 billion sensors worldwide, underscoring the escalating reliance on real-time data.
In the realm of surveillance, this translates to an overwhelming influx of video data from myriad sources, requiring advanced analytical tools to extract actionable intelligence.
AI-powered surveillance systems leverage machine learning and deep learning algorithms to discern patterns, detect anomalies and predict potential security threats, thereby transitioning from reactive monitoring to proactive intervention.
Data analysis is expected to grow substantially in the next few years.
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 time.
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 pre-emptive action.
Instead of reviewing countless hours of typically uneventful video, like a car moving in the parking lot, AI allows security integrators and end users to identify specific events and triggers in the footage, such as, a blue bike riding south or a grey-haired man walking towards the building with a dog.
The ability to capture scene footage with this knowledge and insight enables more accurate alerts and forensics, dramatically reducing the time to act and analyse the video manually.
The integration of AI into surveillance systems increases the demands on data storage infrastructures.
Traditional storage solutions, designed primarily for sequential write operations, are ill-equipped to handle the concurrent read-write operations characteristic of AI workloads.
AI applications require storage systems that can support high throughput, low latency and rapid access to vast datasets to facilitate real-time analytics and decision-making.
The seemingly unlimited demand for data and the sheer amount of video being captured by surveillance systems are driving the need for more advanced and cost-effective storage options that are optimised for machine learning, deep learning, high-resolution video, advanced analytics streaming and much more.
End users and systems integrators alike are looking for reliable, high-capacity drives that are purpose-built for surveillance systems that support multiple cameras, 24/7 availability and the capability to maximise streaming and frame rate performance.
Given the increasing criticality of video for security and other uses, deploying the right recording and storage solution for the right purposes is critical.
Organisations simply can’t afford to lose any data or video integrity, which AI surveillance systems hinge their accuracy and predictive powers on.
Additionally, storing more data for longer lengths of time is necessary for AI systems to become “smart,” increasing their predictive analytic capabilities.
With all these factors in mind, there are a few best practices integrators can employ to ensure they are selecting the most appropriate hard disk drive for a particular customer application – and the workload associated with it – to ensure long-term success.
To fully harness the potential of AI in surveillance systems, organisations must adopt best practices in selecting and deploying storage solutions:
The ever-growing datasphere has led to advanced and creative uses for the video and data generated by connected devices.
Analysing this virtual sea of data can generate actionable intelligence in real time to enable proactive actions that can mitigate or prevent a security issue from occurring, streamline operational processes, improve customers’ retail experience and much, much more.
Among all this data, video plays a key role, and AI-enabled surveillance storage solutions enable the faster, more accurate analysis organisations need to quickly adapt to achieve their security and business objectives.
However, all storage hard drives are not created equal, and it is vital that integrators carefully evaluate solutions based on the criteria that will impact their performance for the workload specifications of each customer and application.
Purpose-built drives with advanced technologies to allow both video streaming and AI analysis ensure the best possible drive reliability and performance, while delivering optimal TCO and the most valuable, actionable intelligence possible.
This article was originally published in the May edition of Security Journal UK. To read your FREE digital edition, click here.
