Sienna Cacan, Global Enterprise Segment Marketing Manager at Axis Communications, spotlights the potential for Deep Learning to boost data centre security and enrich the region’s industry advantage.
Around the world, digital infrastructure is set for massive growth thanks to the increasing demand for electronic services. Case in point, the Middle East data centre market is expected to generate colocation revenue of over US$12.365 billion in 2024. Much of that infrastructure powers the day-to-day services that the region has come to rely on, but a huge part of the growth in demand comes from the next generation of service provision: the world of AI.
Public and business perceptions of AI have changed dramatically over the last few years. Generative AI (GenAI) has triggered significant disruptions across entire industries and, in the Middle East, ongoing investment in the technology presents an opportunity for growth.
But that is just one kind of AI.
Predictive AI – built not to generate data but to analyse and draw conclusions from it – has received a more muted public reaction. This is despite its potential to extract valuable insights from sound, images, and most importantly, video beyond anything we could ever hope to achieve with humans alone.
The power of AI and video data
AI is not just a growth driver; it’s a growth enabler. As data centres expand in size and become more complex, and as their locations spread to meet global demand, AI will play a vital role in simplifying the local and remote management of data centre sites. As power draws increase – GenAI alone is expected to require an additional 38GW by 2028 – AI will help find new efficiencies and discover sources of waste. As data centres enter their critical entity era, AI will play a crucial role in supporting the essential security and safety functions of these sites.
Video data is now a rich resource for AI analysis. A camera is potentially the strongest sensor a business could employ, generating millions of data points multiple times every second. Every pixel can be isolated and analysed, a single camera view split into numerous points of interest to allow one camera to perform multiple jobs at once. Object-based analytics can detect, track and classify items within a scene, and trigger automated processes based on easily defined rules. Cameras are versatile, and their applications are almost limitless.
Leveraging existing technology for new opportunities
If a camera can see something, AI can act on it. Through Deep Learning, it is possible to develop custom reactive applications that offer new solutions to old problems or identify new problems before it is too late to act. In contrast to the heavy AI workloads that underpin the rapid growth of data centres, properly trained AI models allow such analytics applications to run directly on the network Edge, within the very camera hardware they rely on.
That means a camera already in use for security could enhance its abilities, using AI analytics to identify unauthorised personnel in sensitive areas and automatically sound the alarm, or detect and alert operators to suspicious activities like loitering or break-ins. But it also means that same camera could do more – it could integrate with an access control system to detect tailgating, or work in tandem with a thermal camera to offer operators a live view of any hot spots and even automatically trigger additional cooling.
The latter application is critical for a region like the Middle East, where temperatures exceeding 50% in summer seasons can impact energy efficiency.
Applying analytics to physical security
AI’s creative potential means analytics applications can be moulded to fit the unique needs of the data centre environment. Object detection, for example, might be tuned to seek out banned items like water bottles. Cameras can be configured to detect visual or, through their microphones, audible signs of server failure or degradation. Analytics can be trained to watch for environmental hazards like leaks and ensure that upkeep and maintenance are adequate to prolong the life of the equipment.
As data centre customer numbers grow – increased cloud computing adoption in the Middle East and Africa (MEA) region is driving demand for space to host services – video analytics can offer colocating clients visual verification of the precise status of their physical servers or help to optimise energy use through automatic lighting and cooling systems based on detected occupancy.
Even Disaster Recovery can benefit from AI analytics. A camera detecting smoke could automatically trigger loudspeaker alerts, while cameras, intercoms and readers catalogue the precise numbers and location of personnel to streamline evacuation procedures.
Achieving an industry advantage
Data centres are the cornerstone of tomorrow’s technology and are already a critical industry for the Middle East. However, the rapid expansion of digital infrastructure is never easy. Local operators need every advantage they can get, be that saving money, saving energy, or just running facilities as cleanly, efficiently and safely as possible.
Many data centres in the region are adopting green building principles, prioritising energy efficiency and sustainability, which can serve as a case for the global industry.
AI analytics offer all of these advantages and more, all as an extension of hardware, which would be required for security functions regardless of whether analytics are used.
