The Covid-19 pandemic demonstrated vividly the need for cities to be able to collect and act on data. Bad information, both about the pandemic itself and its relationship to cities proliferated online and in the media, while a lack of data hampered efforts to combat it. Even when good data was available, cities were slow to act on it. As the number of companies and products in the “smart cities” space proliferates, it will become more important to make the data collected the basis of policy actions, otherwise it’s an academic exercise.
While the disorganized, half-hearted and even counter-productive efforts of state and federal governments didn’t help, it is possible that better utilization of Covid-19 data by cities could have prevented the need for lockdowns and the long-term disruption of our local economies. The model here must be East Asia, especially Taiwan, Singapore and Thailand. These countries and their cities used Big Data to implement contract tracing and get tests manufactured, distributed and processed rapidly.
In the United States, meanwhile, cities like Boston were getting analyses of wastewater data showing a massive increase in cases, even before testing. They took this valuable data and did nothing. The lockdowns, however, did dramatically show the influence of the automobile on air quality, as well as how fragile our cities are in terms of needing workers to commute in, as well as where our basic goods and foodstuffs come from.
Then there’s the data cities already collect, but don’t analyze. According to Strong Towns, few cities know their true financial pictures — not only do they not keep track of how many acres of infrastructure they might own, but they’re often unsure of the taxes each parcel produces per unit of area. This is vitally important data for cities to determine their financial position and outlook.
Unfortunately, even the clearest, bluest skies many people had ever seen failed to make an impact in policy. Transit agencies across the country have been left by Congress with limited funds for the coming fiscal year, forcing drastic cuts in service that will result in more driving. Policy is also fixated on electric cars and driverless cars. While electric cars will reduce some localized carbon emissions, the paint, plastics, tires and batteries continue to be sources of lifecycle environmental damage and the vehicles churn up matter on the roads. Driverless vehicles are still decades away from being a practical reality.
Moreover, neither electric nor driverless vehicles actually solve any of the problems caused by excessive driving. They still take up too much space, promote inefficient land use and require a huge infrastructure investment they don’t come close to paying for. Reducing both driving and future infrastructure commitments by supporting walking, biking and transit and building narrower streets are the strategies supported by the data.
Political leaders must have the courage to develop policy based on the data smart cities technologies can capture, rather than attempting to justify existing policies as “smart” with special pleading or cherry picking.