Most simple definitions of Smart Cities include goals along these lines:
- Improving transportation
- Enhancing sustainability
- Promoting economic development
- Improving public services
- Improving quality of life
There can be more, or fewer goals (I have compiled a non-exhaustive list of 78 that fall under the smart city umbrella) in part because smart cities mean different things to different people:
- For a politician, a smart city address the challenges facing urban areas, improves the quality of life for its citizens, creates new economic opportunities and drives economic growth and development. It also provides an opportunity for politicians to demonstrate leadership and innovation by using technology to improve the lives of citizens.
- The economist sees an integrated approach to urban planning and development that uses technology and data-driven approaches to improve performance and sustainable economic opportunities, growth and development with new business and investment opportunities, and improved competitiveness.
- Civil engineers may see improvement in the performance and sustainability of the city’s infrastructure.
- The planner, a way to identify and address key urban challenges and optimise the functioning of the city’s systems and services.
A dummies definition:
Smart Cities use technology to make cities more livable, efficient and sustainable.
But wait – these goals have been the aim of city administrators form time immemorial. The only difference is the addition of “technology”, and the use of technology in very specific ways:
- Measuring things that matter in a way that allows for timely and rational decision making.
- Providing meaningful access to information for citizens and stakeholders.
The introduction of technology and data analytics in a smart city setting allows for the implementation and achievement of city goals in a more efficient and effective way. It allows for informed policies and programs leading to better infrastructure decision making based on a more accurate understanding of the city and its needs.
Technology and data analytics in smart cities can also allow for better monitoring of progress towards goals, and improved transparency and citizen engagement.
So Smart Cities are simply those that find ways to achieve their goals through the application of technology.
Except it’s not simple.
No single project has the necessary budget to implement enough smart city technology to achieve its own goals. Traditional project funding arrangements do not yield smart cities. They give “projects with cameras”. The city part of Smart City is the key. To achieve a smart city all projects and activities, large and small, need to have a city-wide focus. Where there is opportunity to extend a protect to further the technological goals of a city’s progress to smartness, these opportunities must be seized and exploited. This can generate significant organisational stress, as funding priorities are analysed. A playground that gives 100% fun may need to give 80% fun, and 20% smartness – a difficult pill for some to swallow; and 20% smart might not be enough for the boffins, so they have their own bitter pills. This internal stress requires strong policy and leadership if a smart city state is to be achieved, and “smartwashing” avoided.
Smartwashing, like greenwashing, and other washings, refers to “projects with cameras” being presented as achieving smart goals for political and grant funding reasons.
Leadership, understanding, and communication pave the way to rational decision making through adoption of appropriate technologies, leading us to a smart city.
Digital twinning in the context of asset management and smart cities refers to the creation of a digital replica of our heroes of physical infrastructure, such as buildings, transportation systems, or pumps, with the goal of simulating and analysing asset and system performance.
In fiction, the “evil twin” is an identical copy of our hero, but with malevolent, or prankster intentions. Like an evil twin, the digital twin initially appears helpful or friendly, but as the story progresses, their true malevolent intentions become clear. The evil twin tries to manipulate thinking by posing as Our Hero and causing distrust and confusion among those who know and love them. The Evil Twin suggests things that don’t seem quite right, but friends and families accept them; the Evil Twin is very plausible.
These suggestions are increasingly divergent from Our Hero’s true nature, yet family and friends continue to accept them, even as the results place everyone in an increasingly perilous situation.
Eventually there is a confrontation between Our Hero and the Evil Twin, where the true nature of both is revealed, and Our Hero prevails… Or the story ends in tragedy for all.
Digital twinning is a great tool for asset managers and for supporting smart cities project implementation, but it essential that the twin is understood for what it is, simply a tool. Putting the tool in place will not solve any problems. The interpretation and analysis of the tool is where value lies. Twinning our assets in a generic way is unlikely to yield future benefits. The need to understand our assets and systems remains key.
Know what matters. Measure what matters. Analyse what matters. Integrate what matters. Do this, or you may create an Evil Twin that misrepresents assets and misleads decision makers.