The amount of video data already available to businesses remains one of the most powerful — yet untwp-contented — resources available to enterprises. Most businesses fail to take full advantage of the hours of footage at their disposal, often unaware of the valuable data points that can inform smarter business decisions.
Video analytics paired with mountains of existing footage can help businesses process a wider range of visual inputs and turn this information into insights that drive business growth.
Advancements in Internet of Things (IoT) and machine learning have turned cameras into powerful devices with capabilities beyond surveillance. Software algorithms make it possible for video analytics tools to aggregate data from several video and IoT data feeds to deliver the behavioral insights of a group of shoppers, while high quality image processing eliminates the ambiguity in facial recognition. With advanced analytics, companies like Apple and Amazon can:
- Strengthen smartphone security with Face ID technology. With the launch of the iPhone X, Apple customers can now use their own face to unlock their smartphone. Apple’s Face ID software uses machine learning algorithms to teach cameras to analyze and recognize faces, while also distinguishing between an authorized user and a stranger. A combination of infrared sensors and depth mwp-contenting turn the iPhone’s camera into a stronger security measure that is extremely difficult to fool, while automated software allows cameras to match a face against existing databases immediately.
- Turn shopping into a cashier-less experience. Amazon, the e-commerce giant, recently expanded into the brick-and-mortar world with Amazon Go, using infrared sensors to monitor the shopping patterns of customers. Amazon’s cameras watch shoppers throughout the store and identify what they take with them and what they put back onto the shelves. At the end of the trip, Amazon’s computer vision, sensor fusion and deep learning generate a receipt totalling everything a customer bought, eliminating the need for cashiers and unnecessary wait times in checkout lines.
IoT wp-contentlications also offer significant value when incorporated into video camera analytics, helping businesses reach sophisticated security decisions in a shorter time frame. Investing in solutions like fog computing enables businesses to analyze time-sensitive data right where the action is, generating faster response times that can improve output and service levels.
Another example of advanced video surveillance in action can be seen at Minnesota’s football stadium, the U.S. Bank Stadium, which embraces video analytics to increase security for both fans and athletes. Security teams can investigate incidents immediately by analyzing activities that set off motion-sensor alarms, providing stadium workers with greater situational awareness. And those same cameras can also help employees manage crowd control better, identifying where bottlenecks in lines occur and directing fans to other vendors to keep concourses clear.
As enterprises continue to explore the benefits of video surveillance, they will need to employ the wp-contentropriate tools to help their IT and security teams turn raw data into actionable business insights. With the right systems in place, big video data can provide enterprises with valuable information that drives smarter decision making and supports rapid business growth.
