SimCity or Smart City?

This post was created automatically via an RSS feed and was originally published at http://businessvalueexchange.com/blog/2015/10/07/simcity-or-smart-city/

I was playing one of the games in the SimCity series recently when it struck me that this and similar games are a very good model for what we want from Smart Cities. Let me explain what I mean.
All of the services, businesses and people in city simulators are connected. This is a really critical element. Without the data collection everything that the city manager does will be based on guesswork or “gut feeling”. What is interesting is how many businesses, and almost all cities, are information-poor; meaning most decisions are based on limited, or out-of-date data, and therefore relies on the experience of people.Connectivity

In many ways city simulators could be thought of as the nirvana for the Internet of Things since the data encompasses data about a wide range of public and private services as well as citizen data about how they feel about the city. So there is a real Open Data model at work here with public and private agencies sharing data.

Visibility

For the city manager the most important feature of SimCity is that you can immediately and in real-time see a huge amount of information about your city.

What is important is that the data comprises both quantitative and qualitative data about the simulated city. The opinions of the residents are very important since perception is as important as the reality of the situation. So, for example, people’s perception of the danger of crime can have a major impact on their view of their neighbourhood.

Insight

Having a view of the data itself is not enough and here we begin to depart from many of the city simulation games and more into the realms of the real-world GIS simulators, e.g. ESRI ArcGIS. However, at the current time I do not believe that these have the power, connectivity or sophistication that will be necessary for truly Smart Cities.

There is a critical need understanding of the cause and effect model linking the symptoms, for example pollution in an area to the long-, mid- and short-term causes which, in this example, could include traffic, industry, weather, etc. In practice, the outcomes will be more complex that this, for example, making a city more “liveable”, or making a city more attractive to business, will bring together a number of areas of management.

What is important here is to have the context data that can help explain changes in the key indicators. For example, suppose you have a small store in the middle of a city. An analysis of your sales data reveals that you have three key shopping times during the day, morning rush when your customers are commutes on the way to work, midday when people are purchasing lunch and doing errands and the evening rush which is people going home and people coming into the city for the evening. Based on your analysis you can arrange to have the right stock delivered and on your shelves for each shopping time. However, if you also have simple context data, for example if it will be raining or if there is a major cultural event you can adjust your stock to better serve the needs of the people during each shopping time, for example, having more umbrellas and rain wear on display if it will be raining. This provides a key level of refinement to your business model.

A key feature of this insight is also understanding the time-series of the cause and effect. For example, making a change, for example, changing traffic light phasing does not have an immediate effect. Rather the change will gradually affect the traffic conditions. I think of this as the “time-value of information”, for example, it is no use to a commuter to know that they are in a traffic jam. If they could have been given this information before they got into the traffic jam then it would have had more value. This becomes increasingly difficult when you are dealing with a complex system like a city where there will be multiple overlapping causes and effects.

Actionability

This is a critical need, it’s not enough to just know what is happening in our cities. We need the ability to actually take action based on our insights that will change the way the city operates. But it’s also important that we are not just reacting to symptoms, but responding appropriately based on the insight we have developed.

This is where the time-value of information comes into play, rather than dealing with traffic jams once they have happened is not ideal. The optimal position would be to recognize the causes of a jam in a particular place beginning so that traffic lights can be re-phased, lane priorities changed and commuters informed of suggested changes to their route. Incidentally, linking this kind of traffic system to autonomous vehicles would provide a really powerful way to manage traffic. Just extending this example a little further, traffic jams are also one of the causes of pollution, so solving them becomes part of making the city a better place to live; increasing the happiness of citizens and so on.

Another key feature of actionability is not overreacting and certainly not chasing the changing values; which runs the risk of creating a hysteresis loop.

Feedback

I don’t believe the kind of cause and effect models I describe here will spring fully formed from the minds of planners. Instead there will be a need for a system that can learn and adapt as the understanding of cause and effect increases. For example, the Victorian engineer Joseph Bazalgette, in response to the “Great Stink” of 1858, made major improvements to the London sewer system to improve health. At the time the belief was that the smell caused illness; the miasma theory. As luck would have it, the work he did actually did help improve public health because it got rid of the putrid conditions that bred bacteria. So it is important to always keep checking your cause and effect models because they may be based upon spurious correlation.

The other key aspect of feedback is reporting back to citizens about the improvement in services. Creating citizen engagement and demonstrating that their issues are being addressed is a critical step in the Smart City evolution.

Conclusion

So, SimCity as a model for Smart Cities, yes I do think that works as a vision and a goal. However, I think that we have a long way to go before we really can do this. Finally, it is important to remember that other city simulation games are available.

Also by Mateen Greenway

Mateen GreenwayMateen Greenway  was a HP Enterprise Services Fellow, CTO and Innovation Lead. Before that he was chief technologist for the Europe, Middle East and Africa (EMEA) Public Sector, Defence & Healthcare Industry where he was responsible for overall strategy, technical direction, innovation and leading the senior client facing technical leaders and key Account Chief Technologists in this major Industry. Prior to this role he was chief technologist for the global manufacturing Industry where he was responsible for overall strategy, technical direction, innovation and leading the senior client facing technical leaders and key Account Chief Technologists.

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