It continues to amaze me that people list Baggage-Left-Behind detection as one of the shining examples of the power of video analytics. In fact, it has to be the biggest disappointment in the market.
However, the reason it has failed so often is not a reflection on bad technology, but the dangers of complex systems. It is a good lesson in knowing where and when to use new technologies.
First, it is important to say that there are hundreds of integrators now using video analytics with very positive results. They are going after the sweet spot, where analytics produce great returns on investment and solve real problems that would be difficult to solve any other way: detection of people where they aren’t supposed to be, perimeter protection, security for outdoor assets, remote guarding, storage and bandwidth savings, etc.
But we have heard so many stories of failed projects as a result of trying to make baggage-left-behind work that we have intentionally left it out of our product, and we regularly warn integrators of the dangers. I thought it would be worth sharing a little more information about it, to help others from falling into this trap.
If you want to see cases of proven failures, you can check out the lawsuit between Lockheed Martin and NYC:
http://www.nytimes.com/2009/04/29/nyregion/29mta.html?_r=1
Their problem wasn’t just about baggage-left-behind, but that was one of the applications that they simply couldn’t get to work. This doesn’t mean the technology couldn’t detect bags left behind. It means that even though it could, the system was unusable.
IBM made a study of baggage-left-behind years ago. I don’t see a public posting of the study that I can link to, but they went back over the last decade to study terrorist bombings. The question they asked was how much benefit would baggage-left-behind have delivered if it were installed at the sites that were bombed.
Their conclusion: Baggage-left-behind would not have helped a single one of the cases. No benefit at all. It wouldn’t have helped even prevent a single bombing or saved any lives.
We also had a recent discussion with someone from the I-LIDS group in the UK, which is a UK Home Office sponsored testing group for video analytics. They set benchmarks for a variety of video analytics requirements. Many have been effectively deployed. However, when it comes to baggage-left-behind, they told us that no vendor has come even close to meeting the needs of supplying the functionality needed to make the technology work as it would need to work to be successful.
The problem isn’t detecting a bag being set down or left behind. That’s the easy part. It is the complexity of the whole system and what is needed to make it practical.
Think about how often you might get an alarm if you detected any bag put down in a crowded airport. How often do people let go of their bags for a moment? How often do they walk away from their bags to throw a newspaper away in the trashcan, or leave their bags with a family member while going to the restroom? How often do people leave a newspaper behind or a lunch bag?
So, the first problem is that the system produces a ton of false alarms. Who wants to continue responding when false alarms are continuous and far outnumber real warnings?
But this is only one part of the problem.
The second part of the issue comes down to how often is a terrorist bomber going to leave their bomb out in the open in the middle of the floor? Even if they were crazy enough to do this, how long would terrorists continue leaving bombs out in the open once they knew baggage-left-behind was deployed everywhere?
Not many. Especially when it is so easy to put a package into a trashcan, or hide it from open view.
It is true that there have been cases of people leaving bombs behind under a seat or in a corner, but the moment word gets around that someone was caught by baggage-left-behind, the technology would be useless, as terrorists would soon stop leaving bombs in any visible place.
On top of these issues, you have the problem of accurately detecting objects that are left behind when you have a crowded area. When people are continuously walking in front of a bag, how long will it take before you detect it?
If the false alarm rate were really low, I’m sure some transportation facilities would still like to use it, even if the ability to detect a bag was low. However, when you add in the low, low likelihood of it actually catching anyone who is intentionally leaving a bomb, and the lower likelihood of it catching terrorists in the future, then the whole program simply becomes impractical.
This doesn’t mean it can’t be used some places effectively. I’ve heard of a couple. They were not crowded areas, and they were not places where people waited, but where people simply walked through, so they shouldn’t be leaving anything behind. But this doesn’t deliver the great promise that people imagine when they think of baggage left behind. They think of catching terrorists planting bombs in crowded areas, such as train stations or airports or bus terminals.
It’s such a tempting use of analytics, especially when it is so easy to demonstrate. It really isn’t that difficult to detect a bag being left in the middle of an empty platform. But when you start looking at the overall complexity of the application, how difficult it is to reduce false alarms, the problems with recognizing bags in crowded areas, and how easy it is for people to defeat the system by not leaving bombs in open areas, then you start to realize that this really isn’t such a great application for video analytics.
What is such a shame is that this application has gotten so much prime time attention, while the uses of video analytics that produce huge real-world benefits get much less discussion.
I think the big lesson here is the importance of thinking the whole system through. Detecting bags is the least of the problems. There are way too many bags and it is way too easy to plant bombs in areas that can’t be seen. The system turns out to be far more complex than it seems at first.
To counter my note of caution, I’d love to hear of examples where baggage-left-behind has been used effectively, and the key requirements needed to make systems like this successful.
