What was once a simple “sit and stare” strategy to identify criminal activity slowly adapted to provide more robust analysis and reporting. However, this growth wasn’t always promising. When video analytic platforms first came on the scene in the early 2000’s, the potential impact was quick to make waves. What security professionals quickly came to discover though was a clear deviation in accuracy and reliability, leaving many with lingering biases towards future developments. However, with recent advancements powered by artificial intelligence, video analytics have become much more accurate and reliable, offering a technology worth taking a second look at.

To better understand how these advancements are driving the industry forward, let’s take a look at the two main facets of artificial intelligence:

Machine Learning
Machine learning, in its simplest form, is the ability for a computer to learn from the data that it processes. By using algorithms created by human programmers, machine learning can recognize patterns in the current data set and use that information to make predictions when new data arrives. As it relates to video platforms, systems using machine learning techniques can sift through thousands of hours of video streams looking for a defined set of parameters within minutes, making it more efficient and reliable than the human eye. While human intervention is often required to produce these results, the need for a constant watchful eye is greatly reduced.

Deep Learning
Deep learning, a specialized subset of machine learning, expands the boundaries of artificial intelligence by analyzing data with a specific logic structure similar to how the human brain would process a set of data. By using a layered structure of algorithms, called an artificial neural network, deep learning creates the space for computers to actively learn on a deeper level with limited human intervention. By doing so, it can make smarter decisions and process information on a deeper level than machine learning alone. Many advancements in today’s world of video analytics are driven by this deeper form of learning. Many of us are exposed to deep learning every day. Just ask your Alexa!

So, what does this mean for video analytics? AI-backed advancements are being integrated in today’s video analytic platforms, making a technology that has faced many pitfalls in the past more appealing to security integrators and end users. Here are three benefits of using AI-based analytics:

Increased Accuracy and Reduction in False Alarms
One of the most widely agreed upon challenges of traditional video analytics has revolved around the lack of reliability and accuracy, specifically when distinguishing between objects and behaviors that humans would have no trouble identifying. With machine learning becoming more available among today’s video analytic platforms, these systems can now view scenes more intuitively. By having a human-like ability to view each scene holistically, cameras have become better at distinguishing the cause of an alarm and what should or should not be escalated. This awareness has led to a reduction in false alarms and less wasted time for response teams. Overall, the use of this technology can reduce human error and streamline monotonous and time-consuming tasks otherwise performed by a member of the security team while increasing overall safety within a building.

Smarter Search Capabilities
More powerful GPUs combined with machine learning capabilities have driven modern analytics to be more efficient when processing data. As a result, these platforms can now independently detect, recognize, and classify objects for easy searchability via a google-like interface. For example, by using natural language search terms such as “USPS Van” or “man in red shirt,” security teams are no longer tasked with sifting through hours of video streams to identify and support an alarm or event.

Enhanced Workplace Safety
Whether it’s monitoring safe habits like holding onto handrails, keeping socially distanced in the era of COVID-19 or identifying a potential gunman in a building, video analytics can identify and alert the proper party before a potential risk turns into a catastrophic event. To do so, analytic software uses artificial intelligence to measure live footage against “normal” workplace conditions that it was trained to identify. For example, if someone is traveling against the normal flow of traffic or a large mass is lying on the ground where there typically isn’t one, operators can be immediately notified of a potential risk.

More Intelligent Data Analytics and More Usable Business Intelligence
With the expanded availability of data, video analytics and AI can help support business-forward decisions and create a more efficient work environment. Using machine learning and deep learning to analyze historical data and mine insights to detect trends and patterns that answer business questions can take security from a cost-center to a value-add department. Questions such as peak times, how long employees congregate in a specific area, and office occupancy can be easily answered through high-powered analytics.

As video analytics continue to evolve, security professionals can anticipate another wave of developments previously thought impossible thanks to advancements in deep learning. Just one example of these bleeding-edge technologies is behavior analytics, or the ability to dissect a person’s intent as opposed to just their movements. These potentially powerful developments and benefits demand that we continue as an industry to have hard conversations about the ethics, accuracy, and potential for discriminatory outcomes.

Overall, video analytics have come a long way. Their presence and development have helped companies automate and enhance many video-related security tasks over the years to better protect employees, workplaces, and communities.

If you are considering replacing or enhancing your video management system or are interested in learning more about video analytics, check out our Comprehensive Guide to Video Management Systems or contact our team of experienced security consultants by emailing info@northlandcontrols.com.