Where is a Smart City? (Part One)


In which Hannah and Ben discuss where we can find a smart city, and whether it can be defined by physical location.

HK: On the first blog, ‘What is a Smart City?’, Gary asked

‘‘How might a Smart City be defined around the globe?’’

There are a couple of discussions I’d like to have over ‘Where is a Smart City?’ Is it digital, or physical? What are the integral elements of a ‘Smart’ environment, and who has it? What does a city space mean for migrant or minority populations? (We’ll cover these in later blogs)

Who knew ‘where’ was such a loaded question!

BK: The definition of ‘Smart City’ is heavily dependent on how we talk about a ‘City’ – I had thought that was moderately well understood – but, thinking about it, whilst a lot of people do live in city centres, it isn’t by any means the only pattern.

HK: And ‘City’ has become a pretty relative term. Does it include where people commute from, suburban to urban? Does it include the resources used by a city, or its tourists, and their origins?

Being a country-bumpkin myself, I’m resistant to an urban-centric approach to global development: megacities can be a huge drain of youth and resource to relatively small spatial areas. ‘Smart’ investment is best focused on people, money and skills capable of moving around not only efficiently but effectively – these aren’t necessarily place-bound resources.

However, the sheer number of connections, digital and physical, in close urban environments makes them a crucible primed for the injection of innovative technologies. There are a huge number of problems of safety and efficiency to solve just by the sheer frequency of their occurrence. And a city-state like Singapore is a living lab: living space is dense, it’s politically pretty stable, the island is covered by a well integrated mesh network both physical and digital.  Smart solutions can be tried and tested through tightly woven populations and scaled upwards and outwards quickly and adapted to specific microcultures and needs. But, what works for Singapore might not work for urban models insulated by isolated rural populations, as in parts of Australia, Ecuador, India, and the US.

BK: Hmm, I’d like to pick up on those terms: scale up and scale out:

Scale up in this case is to test in a known environment and expand within that environment.  This is in one sense the ‘easy’ version. House not big enough? Build another floor on top. Computer processor not fast enough? Buy a faster processor. This tends to hit limits – the foundation of the house isn’t strong enough; the silicon simply can’t go faster even with water cooling.

Scale out is to test in one environment then propagate between environments whilst maintaining some level of co-ordination and control. Farmhouse not big enough? Grow to a hamlet, village, town, city. Computer not fast enough? Spread and divide the load across multiple computers.  The big advantage of scale-out is that if done well it can go much, much further than scale-up. The challenge is that it needs some system to distribute load – roads, power, water for a town; complex intelligent load allocation for large ‘cloud’ systems.

Scale-out to allow smart development across multiple environments requires a considerable degree of smart!

HK: Perhaps, but scale up builds on what you already have, scale out adapts through the environment. Smart Cities work on both trajectories – which is why the term is used pretty broadly to describe cities around the world investing in any degree of ‘Smart’, based on their current needs and resources. Small, rural, huge, high-tech city arenas are making use of the technology they already have, like streetlights and public transport, and building on it, then adapting metadata and learning outcomes to different environments and expanding those in response. This is because these cities face precise and localised problems, like gun violence, isolated communities, disrupted transport, poor water supply or heavy pollution.

BK: You’re saying ‘Smart’, then, isn’t a pinnacle to reach or a line to cross, because even the definition of a ‘city’ is malleable, let alone the definition of ‘smart’. It’s a scalable, continuing process.

HK: Exactly. And the next great thing about ‘Smart’ endeavours, of course, is global scale-out: different cities with variant cultures can still stand to benefit from solutions put to use by various ‘Smart’ solutions. Solutions that work in one arena might work effectively in another in a different part of the world: smart solutions to gun violence, such as gunshot detection and police response in New York, might be useful in Rio de Janeiro. The ‘Where’ of a Smart city, then, is also the pragmatic sharing of working solutions. The scale-up and scale-out models demonstrate the importance of ‘smart cities’ being situated at both specifically local and potentially international scales of development.

BK: Then again, this flexing of inter-city and international boundaries raises the issues of digitally outsourced economies: microjobbing apps, popularised by companies such as Uber, move a lot of economic flow out of cities – the money ‘jumps’ from payer to uber to provider, which removes (disintermediates) the middle local economic tier – the taxi companies and bus companies – in favour of a remote technology company.  Conversely, crowdfunding programs such as Indiegogo and Kiva allow loans to be made and monitored outside an individual’s immediate and potentially financially restricted network, giving them access to resources around the world.

Through different models, we can consider the perspective of ‘where is a city’ differently, from urban density to digital transactions. So in this case there is a ‘boundary’ problem – and that is interesting in all sorts of ways. Including whether a smart city’s needs actually correlate to physical boundaries at all… (To be continued)


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