A single city video camera recording nonstop for one year will produce 8,760 hours of video. Those 8,760 hours contain crucial information about traffic accidents, crimes, and other problems that law enforcement and city officials need to see.
But will officials actually see what they need to? Traditionally, municipal video feeds are monitored by people – and people miss things. Research shows that a person monitoring video continuously for just 12 minutes will miss up to 45 percent of screen activity. After 22 minutes, they can miss up to 95 percent¹.
Imagine how that affects cities with hundreds or even thousands of video feeds coming into a single video management system. For example, the city of Bristol in the United Kingdom already has 700 cameras in operation. That’s a lot of video, and a huge potential for human monitors to miss important information.
It’s a problem that companies like Nokia are trying to fix with artificial intelligence.
4 Problems with Traditional Video Management Systems that AI Can Solve
Video management software has been used to organize video surveillance feeds for years, but it has always grappled with serious problems, including:
- Reliance on full-time human monitors
- An increasing volume of video feeds
- High cost for video storage
- Privacy concerns from citizens
Cities like Bristol, with 700+ cameras, often struggle with these issues. They shoulder an increasing financial burden for recording, monitoring, and storing their videos, along with doubts from citizens. And problems will only get worse as cities expand, adding more cameras to their networks.
But growing cities may be able to scale their video monitoring systems and alleviate public concern with artificial intelligence. When incorporated into a video analytics system, artificial intelligence can drastically reduce the amount of video human monitors need to watch as well as the hours of video that need to be stored long term.