Video Analytics Beta Lab

What is the Video Analytics Lab?

Video Analytics is analyzing video content to detect and determine temporal and spatial events and use this data to create alerts or automate workflows. Arcules uses the latest Artificial Intelligence and Machine Learning technology to develop industry-leading video analytics solutions. To do this, we’ve launched a Beta Lab to give customers early access to our technology so our systems can learn and improve from real-world data.

What does "Beta Lab" Mean?

We are continually testing and perfecting our Video Analytics across many data points and scenarios. We have customized our algorithms for video surveillance, but they get even more accurate as we add more and more cameras and learn what our customers' camera views are like.

We're a modern technology company, so rather than researching in an incubation lab with imaginary data, we release early to customers and learn from real-world data. We release our analytics while they're in research mode and let our customers try them out and give us feedback.

You can use all the analytics in our Beta Lab, but you should not use them for critical scenarios where utmost accuracy is required. They should be suitable for most common video monitoring scenarios, but we cannot guarantee their suitability or functionality.

How does Arcules Video Analytics work?

Arcules Video Analytics uses the latest Artificial Intelligence and Machine Learning technology. AI/ML solutions are entirely based on technology developed during the last years known as Deep Learning.

Arcules does not need to support legacy systems based on technologies that predate the advent of Deep Learning. Many of the legacy systems have limited effectiveness since they are typically designed to solve specific constrained scenarios.

Deep Learning methods, on the other hand, get better (much better) over time. Their effectiveness keeps improving with more and more data. With Deep Learning, we often need more data instead of more software to improve the quality of results.

Another advantage of our approach is that our technology is hosted in the cloud. This means that any time we improve or develop new technologies, you don't have to change any hardware to take advantage of these new technologies.

How can I make my Analytics results as accurate as possible?

This will help train our solutions to match your video imagery requirements. We encourage this continuous and open feedback, and it is one of the reasons we've developed an early adopter Beta Lab approach.