US Department of Homeland Security: Big Data and making borders safer

US Department of Homeland Security: Big Data and making borders safer

How the DHS uses Big Data in practice

Generally, security screening relies on one-to-one screening carried out by human agents who are face-to-face with travellers. Immigrations and Customs Service officers are highly trained to spot the tell-tale signs that a person may be lying about their intentions. However, as with anything involving humans, mistakes do happen.

Research has shown that there is no absolutely certain way for a human to tell whether someone is lying simply by speaking to them. Also, humans inevitably get tired or distracted. None of this is a problem to a computer.

The AVATAR system uses sensors that scan the passenger’s face and body language, picking up tiny variations of movement or clues which may raise suspicion. In addition, a computerised “agent” with a virtual, human face and voice asks several questions. The person’s responses are monitored to detect fluctuations in tone of voice, as well as the content of what exactly was said.

This data is compared against a database, and matched against factors that indicate someone may be lying, based on previous experience. Should it match a “suspicious” profile, the subject is highlighted for further inspection by a human agent.

As well as on the US–Mexico border, the AVATAR system has been cleared for use in several jurisdictions in the US, and it has been trialed in some European borders.

 

The technical details

AVATAR is a kiosk-based system with everything needed for operation included in one unit. Three sensors are built into the kiosk: an infrared camera that records data on eye movements and pupil dilation; a video camera that monitors body language; and, lastly, a microphone that records voice data. This data is combined with a database of cues that can give insight into whether the interviewees acting suspiciously.

 

Ideas and insights you can steal

Given the right data and algorithms, machines have the capability to detect whether humans are lying far more accurately than people can. Indeed, there are many tasks that machines can perform more effectively and consistently than humans, from detecting lies to spotting signs of an imminent breakdown in equipment. Companies that can capitalise on such technology are likely to see huge operational improvements.

You can read more about how organisations are using Big Data to drive success in Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results


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Written by

Bernard Marr

Bernard Marr is a bestselling author, keynote speaker, and advisor to companies and governments. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topics of intelligent business performance for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation have millions of readers.

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