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CHANGING THE SHAPE OF CITIES

Leveraging big data will change how cities are designed, what forms of transport are available, and give us smarter spaces to work with

Cities are badly designed. By which we mean they’re archaic. Little consideration has been given to the increasing number of people travelling to ever-sprawling urban areas, even though we all know what that looks like.

It looks like congestion. It looks like stationary traffic, and raised blood pressures, and increasingly fragile mental health, because there’s only so long you can endure that situation before it begins to get to you. But proponents of big data have plans for cities that involve leveraging information to alter how traffic affects… well, everything.

Roads are veins

‘Sitting in traffic’ affects far more than you might expect. It affects the people who constantly navigate it, it affects the productivity of companies (for myriad reasons), it affects the environment, and it affects governments, financially and in other ways. You need to cope with being in traffic, companies have to deal with late workers who are already stressed when they arrive at the office (plus, goods and services need to be delivered), burning fossil fuels have obvious affects, and governments need to manage and maintain those roads, deploying law enforcement as needed.

It’s no exaggeration to liken roads to a city’s veins. If they become congested, the life that needs to flow to parts of a city cannot get there, having massive knock-on effects everywhere. Rerouting that traffic via other places stresses systems that would otherwise work with fewer issues, potentially causing even more problems. It’s not just an unpleasant experience, it’s a potential disaster always waiting to happen. And that’s why governments and companies like Microsoft, Google and others have begun to leverage the data they have at their disposal to try and alter cities.

Improving circulation

WWhether you realise it or not, you already make use of ‘big data’ – Google Maps runs on traffic information gathered from Android phones that are stuck in traffic, letting you know which areas to avoid on your way home. But proper implementation, at a city-planning level, calls for more information than just the stuff stored on various servers. Efficiency information from

In order to clear up traffic in wide-ranging ways, there are three required items

public transport (which is still a daydream for South Africa), open data from sources of traffic information, and time-and-date details from the cameras you may have noticed at intersections can be combined to do something remarkable.

Data proponents are able to collect and collate this info – and the more of it the better (which brings with it various privacy challenges) – to make cities function more efficiently. It might make sense to permanently close down some streets to traffic, if it clears up more congestion than it causes. New public transportation routes can be planned and implemented, with modifications to its route (in the case of buses or taxis) possible at greater speeds than was previously possible. And lesser-known influences, like the situation three suburbs over every third Tuesday of the month, can be accounted for all around the city. You’d be surprised at how many factors influence traffic density. Here at home

Which sounds a little like magic to us South Africans, but it is something that’s taking place in cities in Italy, Canada, Spain, China, the US and the UK. South Africa has designs on being part of the fourth industrial revolution (4IR), but we’ve got a way to go yet. We face several challenges before we can start modifying cities without ripping up streets.

In order to clear up traffic in wide-ranging ways, there are three required items. Access to data (which is already being collected from all sorts of sources), extensive funding, and the ability to implement changes suggested by data analysis are all must-haves. They’re also not readily available here. Yes, open data exists but SA isn’t generating much of its own info. We’d have to track buses and minibus taxis, combine that dataset with traffic heatmaps of a given city, and identify what to do about our traffic from there. After that, somehow funding and then executing the proposed changes without causing even larger problems becomes the next hurdle.

But it could well be worth taking the chance to do so. Because those datasets, collected for alleviating traffic, will eventually connect to other compilations of information (say, for more effective 5G cellular coverage) to eventually integrate into a smarter city – one that responds to humans rather than forces humans to respond to it. That’s the dream, anyway.