Smartphones have become pretty popular these days (to put it lightly), and aside from the obvious benefits they provide, the data that trickles out of them has been able to benefit us in all kinds of different ways.

Whether its easing traffic jams in our cities or helping to eradicate heart disease, smartphones do an awful lot of good, but what about those countries where smartphones aren’t so widely used? In most developing nations, particularly Africa, the majority of people can’t afford the luxury of a smartphone, but that doesn’t mean they have to miss out on the benefits of Big Data.

It’s easy to forget, but ‘regular’ mobile phones generate a fair whack of data in their own right, particularly ‘location-based data’ that shows where people are located whenever they place a call. One of the problems in harnessing this data from simple phones is that it’s only available to carriers, and most telecommunications firms like to hog this data as much as possible, only giving it out under special arrangement, or if law enforcement agencies request it.

Luckily, not all carriers are being quite so possessive about their data. In what it claims is the largest ever public release of mobile phone data, Orange made over 2.5 billion anonymized call records available from over five million cell-phone users in the Ivory Coast, as part of a research challenge called Data for Development.

The challenge was open to anyone, and as Technology Review’s David Talbot reports, it proved to be particularly appealing to the researchers at IBM, whose team have come up with a new model for optimizing urban transport systems based on the data collected.

IBM’s research centered on Abidjan, the capital city of the Ivory Coast. Like any African metropolis (or any big city, for that matter), the transport system in Abidjan can be pretty hectic to say the least. Ivory Coast’s capital doesn’t have the benefit of mass transit systems either – it has to make do with 539 buses, 5,000 odd mini-buses and 11,000 shared taxis to whisk its citizens around its dusty streets.

Abidjan’s public transport services leave a lot to be desired, but can Big Data make the ride a bit smoother?

Orange’s data set was pretty disorganized too, but IBM’s researchers used analytics software to determine which calls were made by commuters, and consequently, work out the various routes operated by Abidjan’s buses and taxis. From the data they gleaned, they then came up with a transportation model called AllAboard, which identified no less than 65 potential improvements that authorities could make optimize the city’s transportation system. IBM’s team calculate that these measures will shave off around ten minutes from the average person’s daily commute.

The improvements have yet to be tested out, but IBM’s Francesco Calabrese told Technology Review that the potential impact was huge:

“This represents a new front with a potentially large impact on improving urban transportation systems. People with cell phones can serve as sensors and be the building blocks of development efforts.”

However, as Talbot points out, there could be unforeseen side-effects if IBM’s solution is actually implemented. The main concern is that if one or two routes are freed-up of traffic, everybody will start taking it, creating a brand new problem that authorities need to deal with.