The need for instant accessibility and comprehensive analysis of surveillance data will only intensify as video data finds its home in the cloud, says Lance Kelson, CEO of Tiger Surveillance.

The data problem

As the digital age continues to drive the transformation of video surveillance systems, the challenges and opportunities brought forth by higher-resolution cameras have never been more apparent.

With clearer, sharper images come vast amounts of data – a struggle that modern organizations grapple with daily.

A recent report from IHS found that the amount of daily data generated by video surveillance cameras installed worldwide in 2015 was 566 petabytes.

Estimates now show that by the end of 2023 alone, security cameras will be generating more than 5,500 petabytes of data… on a daily basis.

Several factors are driving this transformation; namely the advent of state-of-the-art cameras, the implementation of AI for insightful video data analytics and constantly evolving legislative mandates dictating how data must be managed, where and for how long.

However, this astronomical growth in video data is double-edged.

On one side, it promises unparalleled insights into everyday operations, security and behavior patterns. On the other hand, it can also bring nuanced challenges.

Most organizations expanding their storage capacity to adapt to increasing levels of video data have already faced logistical barriers such as physical data center limitations, rising electricity and infrastructure costs, environmental impacts and maintenance challenges.

In fact, according to a 2021 survey conducted by DataCenter Knowledge, 65% of organizations reported that space constraints were a significant factor impacting their data center expansion plans.

The cloud, with its vast storage and accessibility, has emerged as a unique and promising solution.

However, early attempts to leverage the cloud for storage often encountered complications due to networking and connectivity challenges and complicated deployments.

A few organizations have ventured into leveraging the cloud for storage through bolt-on file systems, separate data silos and hardware gateways.

However, these ad-hoc approaches have too often been marred by complex workflows, or worse, the video management system (VMS) losing association to recordings, resulting in data being permanently unretrievable after an internet outage.

This can lead to legal implications tied to video data retention and preservation, especially when serving as critical evidence in lawsuits or accident investigations.

The need for storage solutions that aren’t just scalable but also offer robust recovery capabilities is highlighted by the insatiable desire to retain more and more recordings.

Organizations today therefore stand at an inflection point: should they amplify their existing on-premises storage, make the leap to a video surveillance as a service (VSaaS) paradigm, or seek refuge in a more adaptive, non-disruptive hybrid approach?

At first glance, VSaaS might appear as the logical next step. VSaaS offers scalability and remote accessibility but often involves complete retooling expenditures, staff retraining, limited feature set with decreased performance, plus higher data recovery concerns coming from internet outages.

Compromises to the user experience are typical as data hairpinning for viewing operations increases bandwidth requirements while wasting available bandwidth.

The easy button

In this intricate blend of challenges and opportunities, Tiger Surveillance provides a comprehensive solution with its innovative Surveillance Bridge. Our approach is safe, functional and reliable.

By offering a direct conduit between the existing file system and any cloud provider, the full power and benefit of the cloud for storage is harnessed without disruption, unexpected costs, downtime or extensive staff retraining.

Tiger Surveillance addresses the top cloud adoption challenges outlined by the Flexera 2023 State of the Cloud Report. Best of all, this infrastructure transition can be set into motion within a few minutes.

The standout feature of Surveillance Bridge isn’t just its role as a software gateway; it’s the intricate comprehension of more than two dozen leading VMS platforms including those from Avigilon, Axis Communications, FLIR, Genetec, Hanwha Vision, Milestone Systems, Qognify, Salient Systems and VIVOTEK.

We have meticulously profiled each VMS to ensure flawless functionality while maintaining access to long-term, low-cost archived data.

The solution is completely non-disruptive to all VMS operations. Surveillance Bridge also protects against potential VMS failures if internet accessibility is ever compromised.

Surveillance Bridge addresses two critical infrastructure challenges: disaster recovery and storage extension.

Operating as a disaster recovery enabler, it guarantees an optimal recovery point objective and recovery time objective (RPO/RTO).

For seamless capacity expansion, the solution allows organizations to dynamically set the on-premises to cloud ratio while maintaining immediate data access and optimizing local and cloud storage costs.

Meanwhile, older recordings as defined by each customer’s workflow are streamed in real-time from any immediate cloud storage tier.

For extended retention periods, the cloud archive tiers provide significant cost benefits and Surveillance Bridge offers an intuitive user interface for continued access to data.

Enter AI and the cloud

So, what does the future hold and how can Surveillance Bridge help facilitate a smooth transition during this race to integrate AI into surveillance workflows?

In a world that’s increasingly driven by AI – visible in everything from home automation to advanced video analytics – the true potential lies in deep-diving into vast archives of data, searching for valuable insights as one would for a needle in a sprawling haystack.

However, the days of expensive AI compute in data centers are numbered.

The future we see relies on live AI in cameras, with abundant and less costly on-demand AI in the cloud.

The key challenge is to provide seamless integration, cost controls and intelligent access to available services.

Cameras with embedded AI provide real-time insights, identifying threats or anomalies as events unfold, enabling timely interventions and streamlining storage by efficiently filtering and discarding irrelevant footage.

However, with the influx of video data from diverse sources, forensic analysis becomes increasingly vital because of its capability to reveal intricate patterns and details that might have eluded detection during live events.

A study by Frost & Sullivan in 2022 found that AI-powered video analytics solutions were expected to grow at a compound annual growth rate (CAGR) of over 25% from 2022 to 2027, underscoring the growing significance of AI in the field.

Exciting next-generation AI tools utilize a blend of natural language processing and computer vision methods.

These tools offer advanced search and summarization techniques with minimal or no training.

Not only do they provide a succinct overview of a video’s content, but they also enable the pinpointing of specific segments.

This streamlines the discovery of relevant information. As a result, investigators can swiftly navigate vast repositories and promptly zero in on specific events or subjects.

Data analysis

With tools like Surveillance Bridge facilitating immediate integration with the cloud, organizations are well-positioned to address the dual imperatives of real-time monitoring and in-depth forensic exploration.

Instead of heavy investments in physical computing infrastructures, organizations benefit from the cost-efficiency of the cloud where high capital expenditures are replaced by a flexible operational model.

Whether one needs to process a day’s footage from a single camera or extensive city-wide surveillance recordings, the cloud’s dynamic computing resources are up to the task.

Yet, it isn’t just about powerful processing or the latest technology. The global accessibility of the cloud is fostering an environment of collaboration.

Stakeholders, regardless of their geographical location, can access evidence remotely from a centralized and extremely durable cloud, thus expediting the decision-making process.

As AI, machine learning and large language models (LLM) evolve, video analysis will become smarter, faster and more commonplace.

By allowing recordings to safely reside in the cloud, organizations are not only addressing current data protection needs but also preparing for the future with AI.

This proactive approach not only protects data in the best possible way, but also adds incalculable future value to the data being protected.

An added benefit for infrastructures that reliably support having only cameras on-premises, Surveillance Bridge continues to greatly reduce operational costs.

Running the VMS in a cloud compute environment with direct access to cloud object storage is the only meaningful way to control costs.

In addition, Surveillance Bridge enables direct access to associated AI services from the cloud provider.

In this way, excessive cloud block storage is all but eliminated in place of immediate and archive object storage tiers while preserving efficient on-demand AI workflows.

In summary, Surveillance Bridge is quickly setting the tone for the future of surveillance data management.

By bridging the power of existing, on-premises VMS infrastructures with the limitless potential of the cloud, video surveillance customers are now equipped to address the demands of our interconnected, data-driven world while maintaining a fully featured, non-disruptive and cost-optimized solution.  

About the author

Lance Kelson is an industry veteran with over 30 years of experience in strategic product and business development focusing on media, metadata and hybrid data storage solutions.

He is the CEO of Tiger Surveillance – a software development company powered by Tiger Technology and specializing in on-premises-first data management and protection for video surveillance workflows.

Prior to the launch of Tiger Surveillance in 2021, he was an Executive Board Member and Executive Vice President of Tiger Technology.

This article was originally published in the October edition of Security Journal Americas. To read your FREE digital edition, click here.