Smart video analytics is a powerful research technology that processes and analyses video data to gain insights and make data-driven business decisions. With the rise of artificial intelligence (AI) and AI-driven features, smart video is becoming increasingly popular in Europe. Some 45 per cent of Dutch organisations say AI has already impacted smart video capabilities and will only continue to drive business optimisation.
AI is having a significant impact on smart video capabilities, especially when it comes to advanced system functions. When asked how AI has impacted smart video, 50 per cent of Dutch respondents cited change in costs. System efficiency (over 48 per cent) and data analytics (47 per cent) follow as other important factors.
Looking at company size, 56 per cent of large Dutch companies (with more than 500 employees) say they see the biggest change in terms of scalability. In contrast, small companies (up to 49 employees) often (78 per cent) indicate that AI affects data generated by surveillance systems.
Moreover, many respondents expect further AI-driven changes for smart video systems, especially in the areas of problem prediction (52 per cent) and AI-generated data (78 per cent).
To meet these new changes and keep pace with the evolution of cameras at the edge, advanced AI features and innovations in data storage, companies need to adapt and scale their smart video systems and data storage infrastructure accordingly, depending on the use case. Higher capacity and fast-performing storage at the edge, where 50 per cent of European companies' data resides, and at the core is becoming increasingly important, the survey shows. This is why the majority of Dutch research companies (43 per cent) choose HDDs with capacities between 13 and 22 TB.
"We see organisations' storage capacity needs doubling or even tripling as a result of media-rich, detailed data captured at a minimum of 24 frames per second (fps). More and more cameras not only record continuously (24/7, 365 days a year) in 4K and deliver multiple streams, but also support real-time device-level data analytics thanks to on-camera AI chips. To store, manage and enable deep analytics of the ever-increasing amount of data, European businesses need high-capacity and long-life storage solutions," said Coert de Ridder, Business Development Manager Netherlands at Western Digital.
One example is the retail sector. Here, intelligent cameras help in many ways: from shop design to improving the shopping experience by analysing in-store movements. With AI-powered insights, shops can record the exact number of people entering and leaving the shop. Further insights support business planning as well as optimal layout or positioning of merchandise. These usage scenarios show that more and more data at the network edge is becoming increasingly business-critical and needs to be stored reliably for analysis purposes. The longevity and reliability of a storage solution are essential to ensure business success through data-based analytics.
It is becoming by research clear that high-quality data streams require storage equipped with advanced features - not only at the network edge, but also in the data centre or cloud. The majority of Dutch companies surveyed prefer to store video data in the data centre (58 per cent), while on average only about one in two companies in Europe (48 per cent) store smart video data there. To support AI workloads at the core and enable Dutch companies to realise their full potential, data centres and cloud providers need robust storage that offers high capacity as well as high performance and low-latency connectivity.
De Ridder research summarises, "Each organisation has different requirements for their smart video storage, depending on the use case. However, what they all have in common is the need to meet the new capacity and scalability requirements of their systems for the future. Not surprisingly, the majority of organisations surveyed are increasingly opting for high storage capacities between 13 and 22 TB. This way, they can equip their systems for future data needs and optimise their businesses to meet the challenges and opportunities presented by AI."
