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3 Ways AI is Improving Video Analytics Software

Video monitoring is one of the latest fields to feature Internet of Things (IoT) devices, applications, and systems. Like much data-gathering technology, video’s benefits come from monitoring and analyzing the footage it gathers. To date, these benefits have been largely reactive since humans are able to watch only a limited set of screens for a limited time, whereas the rest is analyzed after the fact.

This is quickly changing with artificial intelligence (AI). Video analytics supercharged with machine learning and deep learning capabilities is adding a brain to video surveillance’s eyes. Here’s how AI is taking video analytics software to the next level.

1. AI Overcomes Human Limitations

At its core, AI is the science of getting computers to act and learn like humans do. With this capability, they can be assigned tasks previously done by humans. And, as machines, they can do these tasks for longer periods of time with fewer errors.

Studies show that detection rates of humans screening video footage are about 85 percent when only one screen is monitored. The rate drops to 45 percent when 9 screens were monitored.¹ The quality of detection, then, will continue to decrease as more cameras are added to an ecosystem. Plus, humans can only perform at these rates for short periods of time before their attention span lapses.

Machines won’t get tired. They can also monitor and analyze huge amounts of data from numerous video feeds at a given time.

2. Faster, More Effective Analysis

Equipped with machine learning and deep learning, video analytics software can learn as it sifts through large quantities of data. It learns to distinguish between normal activities and anomalies, which allows video footage to be processed faster. Crimes or security breaches are spotted in real-time, alerting human monitors or authorities to further investigate the situation as it is happening.

Further, AI will enhance other video capabilities. Facial recognition has been around for a few years. But AI will allow for faster, more accurate detections even in poor lighting or obstructed views. The same benefits come with object and event identification. With such features, video will be able to flag and track suspicious activities and the people who may be involved in the crime.

3. Better Business Intelligence

Much of today’s video technology is used to survey activity within target spaces – be it a city, a retail store, a school campus or a warehouse. But with AI technology, video will move beyond surveillance.

It will instead be used for new and innovative use cases that can be used to make effective, business decisions. For example, a retailer can use video analytics to monitor shopping patterns, determine a more efficient layout of their store and how to improve product placement and more. Some organizations are already using video analytics software for similar business intelligence needs.

AI is Growing and Complementing Human Monitors

Still in its nascent period, the future of AI-enabled video technologies will open up municipalities, CSPs, and businesses to new opportunities. It won’t replace human monitors, who will always be needed to review final video footage and make judgment calls, but it will relieve pressure on your staff, making them more effective in their roles.

Turn cameras into IoT sensors with real-time video analytics software.


Referenced Sources:
¹ http://chicagosmartlighting-chicago.opendata.arcgis.com/

Case Study: IoT is redefining the customer experience. Nokia case study.

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