Authored by: Sanjay Rohatgi, APAC Senior Vice President and General Manager, NetApp
The future of surveillance is here. Since the onset of the pandemic, 30% of businesses globally are seeing an increase in attacks on their IT systems. Cybercriminals are leveraging the economic downturn and the public’s anxiety to enhance their social engineering tactics by using COVID-19 as a cover for their attacks. In Singapore, the Cyber Security Agency of Singapore (CSA) reports of an increase in malicious cyber activities locally, with threat actors using the pandemic to lure potential victims by exploiting their insecurities and fears during this unstable time.
This is alarming as nearly fifty billion devices will be interconnected to the Internet of Things (IoT) by 2022. Now, more than ever, there is a great need for public safety and increased government oversight as the growing reliance on such devices becomes greater. IDC forecasts that the global video surveillance camera market is expected to grow to $44 billion in the next five years.
The technology growth mentioned can be attributed to the advancements in software, specifically in the areas of algorithms, neural networks, deep learning, and artificial intelligence (AI). Deep technologies can provide a significant improvement to the performance and accuracy of surveillance and facial recognition. AI allows organisations to analyse data in real-time, enabling law enforcement and physical security including checks on exposure to biological threats.
Complexities of a Data Storm
Prior to the pandemic – coupled with smart nation initiatives and digitalisation efforts, investment into surveillance has seen a significant increase in the last few years.
From CCTV cameras to body cameras deployed by traffic personnel, video surveillance has resulted in a data storm. It is estimated that a single day of video surveillance footage collects more than 500 petabytes of data – and this sheer quantity of data collecting opens numerous points of access for cyberattacks with costly repercussions.
Today, with the pandemic looming, businesses across the industries, and the public and private sector are constantly disrupted, with business leaders struggling to find ways to modernise their technology hardware and protect their business from downtime and infiltration. As such, facial recognition and other biometric technologies like fingerprinting, voice printing, and retina, hand, or eye imaging may offer possible solutions.
With the immeasurable amount of video surveillance data, organisations need reliable, scalable, and affordable storage solutions without complexities. Businesses require storage solutions that allow non-disruptive upgrades and enable a centralised storage infrastructure that is easier and more efficient to manage, protect, and grow.
The Need for Video Surveillance Data Infrastructure
Analytics is key in video surveillance and for quick output, the storage at the back end needs to be extremely swift too. Today’s high-resolution cameras capture extensive detail in a wide range of conditions. However, high-definition videos not only require higher capacity storage but also demand more bandwidth. This contributes to the need for storage space.
Sectors like the public sector, education, and healthcare are expected to invest heavily in video surveillance solutions. With that said, this is where storage area network (SAN) comes into play. SAN block storage is the ideal solution for video surveillance storage, unleashing the power of seamless modular scalability, optimised data security, and increased reliability. SAN enables enterprises to scale incrementally - to record high-definition videos from thousands of cameras as well as add more cameras, on demand.
Take for example, a fire department is increasingly reliant on video footage to assist in forensic work whenever there is a fire outbreak. By adding extra video cameras, this could increase fire detection by a ton in the future. What will result would be an exponential increase in the fire department’s storage requirements. Minutes, even seconds, of downtime could mean the difference between catching an arsonist or the spark from a power line. The SAN solution deployed can ensure an immediate and efficient fire detection capability regardless of additional capacity. It could scale from 100 to 500,000 cameras by adding capacity in any increment—one or multiple drives at a time—without any downtime.
The Power of the Cloud
Organisations cannot afford to be slow in their approach – as millions of cameras and other security devices are being connected to networks, this makes the cloud one of the most notable element in a highly digitalised and IoT-centric world. Cloud promises the benefits of efficiency, flexibility, cost-effectiveness, and security. Coupled with the acceleration of cloud adoption, security system integrators are utilising the economies of Video Surveillance as a Service (VSaaS). Such an act is an opportunity to strengthen their business models. Cloud also enables metered usage, enabling businesses, especially small and medium enterprises, to distribute costs.
It is predicted that there will be increased use of video analytics to drive surveillance. Storage is the backbone of today’s video surveillance systems that have evolved beyond security and into intelligent video applications. With the digital shift, the cloud revolution is paving the way for a future that is embedded with analytics, deep learning, and computer vision, where cameras will not only record data but analyse them in real time, allowing businesses to make real-time decisions.
To help organisations meet today’s on-demand economy requirements, organisations will need to start thinking of ways to utilise technology to gauge situations and save human lives. With all this becoming a reality in the future, we will soon witness an eruption of yottabytes of data – and only a well-managed hybrid IT model will be the key to success.