As populations grow, insight into population patterns will become increasingly more valuable
“It was possible to map unusual behaviour and we could see how the large population was behaving”
was possible to map unusual behaviour, and because we had an idea of the aggre- gated movement of about a third of the mobile phones in the country, we could see how the large population was behaving”. Now before we go any further, I’ll stress
that the data INRIX has access to is care- fully anonymised and aggregated. They don’t get the phone numbers or personal details of people on their partner network, or even the details from the phones them- selves; it’s a by-product of technology used by the network to connect phones to the network. And while the data gives a loca- tion, you cannot, for example, identify a particular house or car that a phone might be in, just the general area. The mobile data became much more
powerful when combined with other accu- rate sources of location data, such as that collected from connected cars (for which INRIX deals with eight of the top-ten con- nected car manufacturers in the world).
What Tim realised is that the technol-
ogy INRIX was now developing, was perfect for Origin-Destination analytics and understanding population behaviour as a whole. Because the sample size was effectively so big, you could track how and when anonymous groups of people were to travel, say, from Manchester to London – how long they take, their routes, break points, mode. Or how and when groups of people travel to and from Wembley for a
“They valued INRIX’s experience and knowledge in the transport sector and they viewed our expertise as a way to help them enter new markets”
26
smarthighways.net
sold-out football game. Dynamic informa- tion for real-time, or historical, uses. What it also is useful for is a highly-
accurate historical analysis of how groups of people visit a venue such as Wembley, the NEC or a shopping centre, which can be used for future planning purposes, or to see how groups of people act during unplanned events such as cases of public disorder like a riot or the aftermath of a bombing. So how does it work? “In laymen’s terms,
there are two ways to categorise groups of people at any time” explains Tim, “ Active and inactive. They’re either active peo- ple who’re using their phones, who give a highly granular but anonymous amount of information, but are a relatively small sample size, and the passive users who give
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