A tenfold categorisation for smart cities, and the contribution each of these strands could bring to issues like air pollution.
We did a series of events in China last week on smart cities, one with Tsinghua University, another with the smart cities department at the Tongheng Urban Planning & Design Institute - a 900 strong team of city planners and researchers, a third with Intel and the Beijing government (focused on air pollution) and another with the China Executive Leadership Academy Pudong (CELAP) in Shanghai.
The discussion has become polarised between an overly technology-determinist approach pushed by tech companies (which has achieved surprisingly little, relative to the hype) and increasingly vocal critics (who sometimes appear to suggest that none of the smart city ideas will achieve anything).
We’re convinced that digital technologies have a great deal to offer cities, and that China is likely to be a particularly interesting case in the next few years. Over 190 cities are taking part in a government sponsored programme on smart cities, experimenting with new uses of GIS, remote sensing, information infrastructures, cloud centres, data sharing etc.
Some of the elements are fairly predictable (for example, on improving transport management or city administration), others much less so: like the Mycity government Wiki in Beijing, or Qingdao’s role as a pioneer of administrative data sharing, or the Mobile Lab in Beijing organising large scale use of PDAs by officials.
As in the West, the discourse is shifting away from the cruder technology push ideas to an interest in intelligent problem solving and even wisdom. The session with Intel on air pollution exemplified this, bringing together policy makers from the Beijing municipal government, and people from big tech firms, with technology entrepreneurs and social innovators.
In our presentation, we suggested a tenfold categorisation for smart cities, and the contribution each of these strands could bring to issues like air pollution.
Sensing, adjusting, delivering efficiency: waste bins, water use, energy loading, transport flows (eg Barcelona water management, Songdo in South Korea, Living PlanIT’s Urban Operating System, Rio de Janerio’s Operations Centre)
Floods, weather, crime, health (eg PARR++)
Home management (eg Samsung Smart Home)
Engagement platforms, crowdsourcing ideas (eg BetriReykjavik)
Health/care, high risk people and areas, Intellipedia models
AR for planning, collaborative development
We also prepared the graphic below to summarise what we think is a more sensible approach combining bottom up and top down tools. Building on our previous work in China, we’re planning to follow up with more detailed research on the Chinese smart city experience over the next couple of years.
It’s still remarkable how little hard evidence there is in this field – marketing wins out over measurement, but hopefully this will change soon.