A study by the US National Center for Atmospheric Research (NCAR) in 2008 found that the impact of routine weather events on the US economy equates annually to about 3.4% of the country’s GDP (about $485 billion). This excludes the impact of extreme weather events that cause damage and disruption – after all, even “ordinary” weather affects supply of and demand for many items, and the propensity of businesses and consumers to buy them. NCAR found that mining and agriculture are particularly sensitive to weather influences, with utilities and retail not far behind.
Many of these, disaster management included, are the focus of smart city innovations. Not surprisingly, therefore, as they seek to improve and optimize these systems, smart cities are beginning to understand the connection between weather and many of their goals. A number of vendors (for example, IBM, Schneider Electric, and others) now offer weather data-driven services focused specifically on smart city interests.
The Climate-Smart Cities program at The Trust for Public Land is designed to help cities overcome barriers through a holistic, urban planning approach, bringing a broad range of traditional and non-traditional partners together to develop a common understanding of the needs and opportunities in their communities through the strategic deployment of green infrastructure. We believe that inter-agency and cross-sector collaboration can unlock hidden resources for multiple-benefit, climate-smart green infrastructure for the benefit of the communities who need it most.
The California economy is currently seeing a spillover of the newest technological innovations from Silicon Valley, into the Central, San Joaquin and Salinas Valleys; adding to the existing base of advancements in precision irrigation, spectral imaging, genomics, environmental, animal and plant sciences, and dozens of other areas of practice. Many of the applications in use in today’s cities will likely find their place on the farm or vineyard, especially when it comes to IoT (Internet of Things) technologies.
The smart city is meeting the smart farm, but the nature of technology necessitates this relationship will be symbiotic not unidirectional. Increasingly, the smart farm will be impacting the smart city.
Steven Hawking recently commented that artificial intelligence (AI) would be “either the best thing or the worst thing ever to happen to humanity”. He was referring to the opportunity that AI offers to improve mankind’s situation, set alongside the risks that it also presents. These same competing possibilities apply no less when AI is considered in the context of smart cities and the planet’s growing urbanization. With smart cities, though, this is not just some abstract balance: there is a genuine choice of path to be made as smart cities and AI evolve together. This article explores the choice.
DigitalC aims to begin to address this need by developing the Midtown Tech Hive located at 6815 Euclid Avenue in Cleveland’s Midtown neighborhood. The Midtown Tech Hive will house Cleveland’s first neighborhood innovation space anchored and operated by DigitalC, an organization dedicated to making Cleveland a thriving hub of innovation and digital inclusion. The Hive will provide vibrant workspace, feature robust 18-hour programming, and a commitment to a diverse user base.
Brownfields are sites that are vacant or underutilized due to environmental contamination, real or imagined. There are brownfields of some kind in virtually every city and town in the U.S., usually related to a gas station, dry cleaner, auto repair shop, car dealership or some other ubiquitous local business that once benefited the community it now burdens with environmental hazards or old buildings.
In addressing this issue, technology has not been effectively deployed to promote redevelopment of these sites and catalyze community revitalization. We find that the question around the use of technology and data in advancing the redevelopment of brownfields is twofold:
How can current and future technology advancements be applied to upgrade existing brownfield modeling tools? And then, how can those modeling tools be used to accelerate transformative, sustainable, and smart redevelopment and community revitalization?