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Big data and the big opportunity for smart cities

Although the term big data has been around for years, its promise continues to fascinate people around the world, writes Martin Howell, the director of external affairs at Cubic Transportation Systems (CTS). It’s a promise to transform lives, improve services, make communities more efficient and children safer. There are thousands of projects underway that aim to do just that in a multitude of ways, from identifying buildings most prone to catastrophic fires in New York, to helping crime reduction in London.

Perhaps nowhere is the need for big data projects felt more acutely as it is in transportation. Currently, many transport networks are struggling to cope with rapidly growing populations, leading to congestion, pollution and very often – road rage.

In London alone, the equivalent of a Tube train full of people arrives in the city every week and needs to be accommodated on the transport network. A report by Urban Insights, Cubic’s subsidiary, has shown that despite London’s smart card penetration rate being at saturation level, the city has a below-average rate of traffic-related fatalities and boasts dynamic and efficient public transport sector operators. However, its urban mobility index still stands at only 53.2 out of 100 against other cities. While globally it’s an above average score, it shows significant potential for improvement. The argument stands valid for other cities too – on average, less than half of the potential of urban mobility systems is unleashed today. Action is needed, and fast.

Big data, when complemented by deep analytics and applied to a centralised, account-based mobility system could open up opportunities to make those networks much more efficient and I’m convinced it will play a central role in keeping our cities moving 50 years down the line. The rise of the sharing economy has already enabled many cities to stretch their existing infrastructure – opening up new means of transportation, such as car-pooling, and encouraging more socially and economically acceptable combinations of transport modes. Applying big data analytics to the mix will help even further – by using analysed and predictive data, we will be able to revolutionise life in the city. Traffic authorities will oversee increasingly efficient urban highways, and the rise of the connected and autonomous vehicle will revolutionise life – the aged and infirm could be out and about, children could be dropped safely at school – the need to escort them from door to door now gone.

We’re already in the midst of this transformation by changing how we interface with transportation systems. We’ve gone from interfacing with equipment like vending machines and kiosks, to mobile payments and location-based services. In the future, we will be able to rely on digitised personal assistants that are able to provide predictive services based on a rich understanding of our habits and preferences. By having a single travel account, people will be able to yield data about their movements and in return, receive critical intelligence that enables them to save time and cost, for the city to simply work better.

At the heart of this scenario will be an overall, connected transportation management system that would define how efficiently the roads are used and that would be able to integrate a number of different information feeds, all of which have a bearing on road usage to the benefit of the traveller. Observing all the data on how a city’s population is moving and applying actionable analytics to the information gathered, yields real insight into travel patterns. When incidents inevitably occur, their consequences will be better understood and action taken, before problems become unmanageable. This is the Holy Grail for data analysis – truly predictive intelligence.

However, such a connected system cannot exist in isolation. It would require travellers to opt-in to share their personal travel data – something we’re already well accustomed to, when one thinks of the number of ways we interact with sharing economy applications and services. Shopping deliveries through services such as Ocado, ride pooling through Uber, transport applications like Citymapper, smart bikes and even the Oyster card already gather plenty of transport information that has the potential to empower commuters to make smarter, more informed travel decisions. By feeding it all into a centralised system and thus providing a view of a city’s entire transportation architecture, we could realise the promise of a smart, efficient, commuter-friendly city much quicker.

We need to make the case now with economically proven examples and then map out the route forward. We could be reaping rewards within a year or two – better managed roads, more intelligent use of public transport and best usage of connected vehicles. But, there is a nagging doubt in my mind that although the technology is proven and available, we will still see people talking and prevaricating in five years’ time. And the worrying thing is, these problems aren’t going away. They will only become more expensive and more difficult to fix, as each year passes.