In the BBC Radio 4 Thinking Allowed podcast on smart cities, a discussion on what it means for a city to be ‘smart’ is examined through multiple examples. To guide our discussion, we will use the definition of smart cities as set out by Townsend as “places where information technology is combined with infrastructure, architecture, everyday objects, even our bodies to address social economic and environmental problems” (Townsend, 2013: 15), though this definition does have its limitations.
One example explored in the podcast is the traffic in Calcutta; here the infrastructure cannot reliably handle the volume of traffic in the city. (Taylor, 2018) A ‘smart’ solution to such a problem will differ based one the very urban environment in which it is occurring. Miller points out that we have increasingly moved toward a world where information is stored in non-narrative and decentralized databases. The advantage is that theoretically the information contained in these databases can be endlessly reconfigured and reinterpreted, as they are consistent of units of information that variable and constantly transforming, as opposed to information stored in “old media” (Miller,2011: 14).
However, this aspect of the digital age also brings with it its drawbacks. As Miller points out, reducing and reconfiguring information into a digital space, ultimately means that context surrounding that very information is lost. As Miller puts it “where a narrative would provide a context, a cause, a reason, or a story, a database provides a temporary relationship.” (Miller, 2011: 24) The implication being that smart solutions based on traffic data gathered in one place, are unlikely to be applicable universally.
In the podcast it is pointed out that Calcutta’s traffic situation would be more easily remedied by a better public mass transport system, whereas solutions that are often hailed as ‘smart’, like driverless cars, might be a better solution for congestion and pollution in other cities. This illustrates that there is more to a city being smart than just gathering and processing information, it is ultimately also dependent on where and by who the increased information is processed.
This can also be seen in the example of noise pollution on one busy street in Barcelona. Here local residents campaigned to reduce local nighttime hubbub. It was not until they banded together and created a network of low-cost sensors that fed back-on and quantified the problem that they were able to enact change. Through this network they proved that the sound reached “well above UN guidelines.” (Taylor, 2018) It was there very ability to amass and interpret information that brought about substantive social change.
This does raise an issue that might impact a city’s ability to become ‘smart’. As Townsend puts it for cities to become truly smart a “new civics” will be needed, “we need to take back the wheel from the engineers and let people and communities decide where to steer.” (Townsend, 2013: 14) The residents in this example had the means, technology and infrastructure to put the requisite sensors in place – but this is not going to be an option for every community. Socio-economic factors and access to developing technologies are always going to impact on how we can interact with a smart world. No surprise then that Townsend opts to focus on “what do you want a smart city to be?” (Townsend, 2013: 15), rather than what it is.
Miller, V. (2011) ‘Understanding Digital Culture’ Key Elements of Digital Media London, Sage publications. pp 12-21.
Taylor, L. (2018) ‘Smart Cities’ Thinking Allowed podcast 25th July 2018. BBC Sounds accessed 10/02/2020: https://www.bbc.co.uk/sounds/play/b0bbr3zn
Townsend, A.M., (2013) ‘Smart Cities’, New York: W. W. Norton & Company. xi-18.