Mobile Phone Companies Can Predict Future Movements of Users by Building Lifestyle Profiles

Mobile Phone Companies Can Predict Future Movements of Users by Building a Profile of Their Lifestyle

• Your future location is calculated using data from your phone
• University of Birmingham team made location predictions of users with an error margin of just 60ft
  
• If developed, it can be used for personalised marketing, but has been accused of invading privacy

August 19, 2012

Daily Mail - From telling us when our train is coming, helping us when we're lost and letting us watch our favourite TV shows, there seems no limit to how involved our smartphone is with our day-to-day life.

Now the gadget promises something so advanced it verges on the supernatural: it will know exactly what we're doing tomorrow.

Scientists have found a way of predicting an individual's future movements by analysing information their mobile phone. A team of computer scientists at the University of Birmingham successfully predicted future locations with an error margin of just 60ft, which has fuelled fears of privacy invasions.

While mobile phone networks can already track where a handset is in 'real time', the scientists have developed an algorithm - or formula - to forecast our future movements. They compared data from one individual and their closest social network to predict a person’s future location based on places and areas visited in the past and the frequency of contact between those studied, The Sunday Times reported.

For example, if two individuals who have close contact visit a particular restaurant, it is highly likely that this is where they will be the next time they are both heading towards the area where the restaurant is.

This means that mobile phone providers will be able to predict the future whereabouts of their customers .

The study used mobile phone data from a group of 200 people living in the vicinity of Lausanne in Switzerland.

Dr. Mirco Musolesi, who led the study, said: ‘Information extracted from the usage of a mobile phone is an intriguing source of data about people behaviour.' He added:

‘We have shown that the accuracy of the prediction of an individual’s future locations could be improved if his or her previous movement and the mobility information of his or her social group are taken into account.’

He said that the formula may not reflect the general population and would be more accurate in cities where people’s moves tend to be synchronised.

Although it will be of great help to marketing companies and possibly law enforcements, privacy groups such as Big Brother Watch fear it will invade privacy.

‘This development highlights huge privacy concerns’, Emma Carr, deputy director of Big Brother Watch told the Sunday Times.

Mr Musolesi tweeted plans of releasing the algorithm as an API (application programming interface) which would open up commercial possibilities for app-wizards and mobile phone service providers.

In terms of marketing it means that advertising agencies will be able to target individuals with personalised advertisements using information about where the person has been and where he or she might be going. But it could also be a tool for third-party apps offering discounts and other offers where the app would be able to provide real-time deals available at venues and areas where a person is predicted to beat a specific time and day.

The team also expressed hopes that their algorithm could be used by the police force in prediction of the future location of criminal events.