Can You do Intelligent Video Analytics?

Video is a risingsource of data, and with consumers’ increasing preference for image and video content, it is time you became aware of the importance of intelligent video analytics (IVA).

To get insights and make decisions based on video usage, you’ll need to become familiar with machine learning and deep learning models along with high performance query capabilities once the videos have been analyzed, tagged, and annotated. We are seeing enterprises deploying the technology across various applications to create new opportunities for monetization and improving operational efficiency.

One need not look too far to see how IVA is shaping day-to-day life. Let’s consider the simple scenario of making a trip down to your workplace as an example. You may use an app to check the traffic conditions to avoid traffic congestion on your way to work or find an open parking spot easily. This is where IVA comes into play. Powered by video analytics tools such as traffic cameras, governments and parking operators can deliver real-time traffic updates to users. The data collected also helps traffic management companies, parking operators, and governments alike to understand traffic patterns and take actions to ease congestion, especially during peak periods.

A real-time map widget displaying the kind of extreme data a city can generate (Source: Kinetica Connected City Demo)

Besides monitoring traffic conditions, the data captured by these video analytics tools can also help combat security and terrorism challenges. IVA plays a critical role in security intelligence: It detects security threats after sifting through massive volumes of video data in real-time. As it deviates from the traditional method of security personnel viewing 20 CCTV cameras on a single monitor, IVA is able to significantly reduce human error and false alarms.

The volume of video data will continue to grow over the next couple of years, especially in Asia Pacific. It is imperative for businesses to move beyond analyzing any and every form of data they have collected. Instead, they will need to extract the right information from their data lakes for analysis in order to gather relevant and actionable insights and make decisions based on those insights. Companies powered by data in today’s Extreme Data Economy will become the winners.

In this day and age, legacy technologies built only for CPU-based computing will no longer work. To keep up with the increased unpredictability of data and complexity of analysis, sophisticated, GPU-powered insight engines will be fundamental in enabling enterprises and governments to process the worlds exponentially growing data volumes as well as IVA at scale. Some key considerations for enterprises looking to implement such insight engines include the capabilities to streamline machine learning and run models for image and facial recognition; conduct high-speed, cross-data analytics; perform simpler and user-friendly queries to analyze video metadata; scale for large amounts of data as well as for compute-intensive workloads; and most importantly, unify human and machine perspectives.

Enterprises that are able to turn the relentless data analysis revolution to their advantage will reap benefits including devising data-driven business strategies and increasing differentiation from their competitors. Governments, on the other hand, will be able to increase urban planning efficiency and further push their nations towards Smart Nation development.