Osprey recently launched a new type of exception-based activity alert. Our goal was to cut down on the false alerts that are common when using motion-based video analytics in outdoor environments.
False alerts are a significant industry problem: When too many false alerts are sent, users tend to shut out all alerts, which defeats the purpose. Our idea was to apply our cloud-based computer vision (a type of artificial intelligence that recognizes objects or activity in an image or video) to verify the presence of a vehicle, person or both in the video analytics-generated alert before sending it.
As part of this initiative we also implemented a new feature allowing customers to define and edit their own alerts.
Going through the data in detail we found remarkable results. The computer vision (CV) filtering cut down on false alerts by 70%, also by improving the way we track vehicles and people across multiple cameras at a site, we have reduced the total volume of alerts by 90%.
Osprey’s customers are noticing the difference as well:
“I want this on all my sites (…) much better experience”
– Security Lead, major oil and gas producer“This is great. Please put all our sites on the new alerts right away”
– Control Centre Manager for midstream oil and gas company
This is just one example of how we can integrate, train and deploy computer vision algorithms to solve real industry challenges.
For more information on what Computer Vision can do for you, please visit: https://ospreyinformatics.com/computer-vision
1 (844) 590-0824