3 Frameworks for Understanding the Promise of Smart Cities
Marc BielasMarc Bielas
If you’re coming from my previous articles, What is a Smart City and Smart City Approaches in the Real World, you may be wondering how to begin building intuition about the Smart City industry. This article will present three different mental frameworks that you can use to understand a smart city:
These three Smart City frameworks can be applied at all scales from the macro, industry-level to the micro, technology- and solution-level. This list of frameworks—neither exhaustive nor exclusive—aren't the magic pills that dictate whether a specific action is worthwhile. Rather, you should use them as filters through which you can better understand aspects of the industry.
In an ideal world, smart city experts would use a combination of filters. These experts understand the balance-points upon which these filters rest when making decisions. For example, creating a more materially efficient system may not always be the most economically efficient and vice-versa. As we learn more about smart cities, it becomes increasingly important that we ascribe weights to individual filters—not only at a personal level (i.e. what we care about as individuals) but also at a societal level (i.e. what's good for our urban communities as a whole).
One of the most important ways to analyze smart city trends is to think about them economically. We should ask whether a particular implementation makes financial sense. At a macro level, Smart City technologies will result in an additional (and recurring) 2.6% growth in GWP (gross world product) over the next 10 years. On top of that, another $20 trillion of secondary economic benefits are expected to be seen from now until 2026, when GWP reaches $100 trillion (ABI Research).
While these sorts of economic forecasts point toward Smart Cities being a valuable investment, that doesn’t mean all Smart City projects should be financed. Smart City projects often require large capital expenditures and have long payback periods. Other times, the indirect economic benefits may significantly outweigh the direct ones. For example, a 2016 Columbia University analysis of whether New York City should electrify its fleet of 5,700 public buses found that after an increased capital expenditure of $300 thousand per electric bus, the city would realize $39 thousand in decreased spending on fuel per year over the vehicle’s 12-year lifecycle. When one includes secondary economic gains, such as the annual $150 thousand in public health benefits per bus from decreased greenhouse gas emissions, the payback period is significantly shorter. However, since neither NYC Transit nor the MTA directly realize the benefit this positive externality, they may not account for it in their economic analyses.
Economic models in the smart city industry can also get creative. In the private market, for a number of firms able to absorb the high capital costs of infrastructure, there's a significant opportunity to offer guaranteed savings plans, which minimize the upfront cost to end users. These plans are contractual obligations to minimize a client’s recurring costs by a certain percentage that's lower than the actual savings offered by a Smart City solution. Any savings above the percentage agreed upon is captured by the provider. For example, if a startup had a $100 smart waste monitoring solution that could minimize cost by 25 percent a year and found clients who spent $1,000 on waste management a year, instead of selling the device directly to the consumer, they could guarantee the consumer a 10 percent reduction in their waste management bill a year and be turning a profit after the first year in business.
As with both the guaranteed savings plan and the electric bus examples, there are many different opportunities to make Smart City solutions economically viable. Some analyses may require non-traditional thinking. Learning about and applying both traditional and expanded economic approaches to proposals will increase your ability to understand where a true opportunity exists.
Another great approach to thinking about many opportunities within Smart Cities is that of efficiency. Ask yourself the following question: Will this solution allow me to get more output for the same or less resource input? At a macro scale, cities are an extremely efficient use of space, with more people packed into smaller areas (population density). This higher population density means that humans can interact with each other more directly and also reduce the physical impact on the natural world by concentrating anthropogenic destruction (urban households consume 78 percent of the energy that suburban households do).
Within the Smart City industry, there are already many examples of projects that leverage efficiency to make a difference. One such example is vertical farming, in which urban warehouses are converted into high-tech farms to feed the nearby population. Companies like Aerofarms in New York or Plenty in San Francisco grow 130 times and 350 times the amount of food per year that similarly sized conventional rural farms do respectively. Not only are these solutions more efficient in terms of land use; they also recycle water. In Plenty’s case, it allows them to use 1 percent of the water conventional farming consumes while harvesting crops year round due to lack of seasonality, which increases output per unit of time—our greatest resource (Fast Co.).
One can imagine a future in which most of the food sold in cities comes from local vertical farms. Those farms will have the added benefit of lowering the amount of energy spent on transportation while also increasing the resilience of our cities by decreasing our dependence on refrigeration and complex food supply chain networks, many of which are international.
Another great case study in efficiency is the trend toward automated recycling, exemplified by the sprawling recycling network of the Songdo business district in Korea. In Songdo, trash moves from private apartments and public bins into underground sorting facilities through a system of interconnected pipes. Rather than congesting streets with garbage removal trucks and requiring hundreds of waste management personnel, everything is handled by an automated computer vision system. It requires just seven employees to run operations for the city of 100,000.
In most cases, efficiency can be a huge driver for smart city development and will often have significant overlap with both economic and environmental benefits.
By popularizing both energy efficient technologies and distributed environmental sensing via IoT, Smart City solutions often help increase the quality of life in urban areas. For many municipalities, distributed networks of environmental sensors that measure humidity, air quality, and temperature will allow for quick analysis of health and safety impacts. Land-owners can begin developing energy-focused building management systems since buildings account for 39 percent of global carbon emissions. Leveraging pre-existing artificial intelligence and IoT solutions, we can build systems that decrease energy use dramatically.
A recent case study with Deepmind, a popular AI company owned by Alphabet, led to a 40 percent reduction in energy use (over human control) for cooling Google’s data centers (Deepmind). Utility providers are also demonstrating early promise in this field. They're allowing customers to sign up for energy-conscious plans that automatically shut down heating, ventilation, and air conditioning systems during peak loads. They'll sometimes even include forecasting to pre-cool or pre-heat a home when energy is most available and in coordination with residents' everyday rhythms.
As technological development trends toward sustainable solutions such as clean energy and resilient infrastructure, urban areas reap great benefits. Smart cities are those that are prepared for the uncertain environmental future resulting from climate change. Actions such as dedicating green spaces, which both increases surrounding property values and betters urban air quality, will become ever more important in future cities. Palo Alto, CA has determined that it’s fully-cataloged 37,500 trees create upwards of $17.5 million dollars in benefits a year for citizens. Trees also capture rainwater and are able to replenish aquifers. This initiative represents a huge opportunity in California and in other drought-prone areas.
While we can analyze economic efficiency and environmental benefits within their respective frameworks, those analytic frameworks really serve us best when viewed as compounding filters layered onto the smart city landscape. For example, it's likely that an environmentally conscious solution will also be more resource efficient. With enough creativity, the entrepreneurs and bureaucrats driving those decisions will be able to build an economic case as well.
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