There is a saying that “A picture is worth a thousand words”. Therefore, we can say that a video which is nothing but a huge set of pictures is worth millions.
For businesses, one of the most powerful advantages of video is its applicability across many use cases in all industries. However, there are simply not enough eye balls available to monitor all this data. Keeping up with tens of thousands of hours of video can be a difficult task for any enterprise.
As a result, video feeds are the most important yet untapped resources in today’s world.
Video Meets IoT
One of the most incredible developments going on in the Internet of Things (IoT) domain is the use of video analytics, a means to tap into this untapped resource. Through applying machine learning algorithms to video feeds, cameras can now identify objects, people and situations.
Video Analytics has been around for quite some time. However, it was not that efficient. Video analytics used to comprise only basic motion detection, using features like pixel matching and frame referencing. With this capability, video analytics enabled the operators to be able to investigate only those feeds where something is happening instead of looking through the entire footage.
You are not supposed to find everything that moves interesting. You do not want to be told “something’s moving in front of the camera” every time it happens. This lack of “intelligence” in the alert generation capability led to creation of many false alerts. A flood of false alerts is worse than a dearth of true alerts, as it makes the operations team complacent.
IoT Video Analytics Yields Benefits
However, now a new era of video analytics has begun. Few of the recent advances which have got the industries excited about video analytics are:
- Increase in real-time processing capability – Today’s applications can process a high volume of video footage in real time which was not possible earlier. Due to this, business users can get real time detailed insights (the kind only possible with video) from factory floors and fleets.
- Increase in accuracy – Current video-analytics applications can recognize and ignore irrelevant motions that previously triggered false alarms, such as, a factory worker moving across the shop floor. Additionally, users can now program algorithms to detect specific visual patterns, such as, defects in glass, fire emergency etc.
- Development in Big Data analytics – Video is nothing but a stream of images. Each image comprises a lot of data in every pixel which means that video analytics deals with huge datasets, bigger than possibly any other business use case. With advancement of big data analytics and AI, video analytics is better equipped to give relevant business insights.
Transforming Business with Video Analytics and IoT Technology
These improvements have helped businesses recognize the value of video analytics across industries, from supply chain and logistics to manufacturing.
Global Video Analytics Market was valued at $2,745 million in 2016, and is estimated to reach $13,381 million by 2023, growing at a CAGR of 25.7% from 2017 to 2023. One of the reasons for this has to be the value addition to IoT.
IoT applications usually, offer more value when they incorporate video analytics. For instance, many IoT applications use Bluetooth beacons to transmit location data each time they connect with a consumer’s smartphone in a store. This data can help retailers with the count of visitors to their store. On the other hand, a video-analytics application can provide more detailed information on details like gender and age group of the shoppers adding a lot of value to the insight.
Emerging technology such as neural nets, deep learning and facial recognition are improving both precision and accuracy of the algorithms, paving the way for advanced capabilities and new use cases. And the best part is, we already have a vast amount of historic data that can be used to gain new insights.
Business Analyst – Digital Business Consulting, RapidValue