The fully realized smart city is rapidly taking shape. Bloomberg New Energy Finance reported an increase in major public-private smart city technology deals to 35 global cities in 2017, up from eight in 2016. Blockchain will further accelerate that progression. Smart cities started in the early 2000’s with broadband and progressed to solution architectures such as LED lighting systems, where now digital services using predictive analytics built on the Internet of Things generating Big Data are becoming prevalent.
Now we are entering an era where, thanks to blockchain, there will be a way to keep a running tally on transactions to provide frictionless financial settlements, claim processes, energy generation, and so much more.
As a general prediction, while there is no single rationale for a smart city, certain themes such as efficiency and cost, environmental impact, and the ever-intangible quality of “livability” have historically predominated. They will continue to so, simply because there is no reason for them to change – they reflect common-sense concerns that cities and their citizens continue to have. However, as smart cities invest in the underlying IOT and analytics technology, I predict that two other goals will increasingly join them.
Use cases abound for everything from installing a myriad of sensors in urban areas, to monitoring everything from traffic patterns to air quality, to the health of critical infrastructure. A key challenge of installing strain sensors on a bridge or highway overpass is sourcing the power required for them to operate. Nikola Labs technology can address this challenge by harvesting power from nearby power lines, radio and TV towers, and cell phone communication hubs. When consistent power is provided, long-lived sensors can provide the rich steams of data necessary to generate PdM insights; thereby avoiding catastrophic failures and permitting municipal departments to focus their attention on infrastructure most in need of repair.
Where smart city projects require departments or agencies to collaborate and share money and data in new ways, they may be just be asking the physically impossible; or they may impose a zero-sum calculation on those entities – the more collaboration, the less power, budget and funds, and the less reason for the separate existence of each entity. Said differently, in organizational and political terms, smart cities are fundamentally unnatural.
The ecosystem concept, once confined to its biological origins, has found new life in the smart city.
When natural systems begin to evolve, there is at first low diversity and complexity. Over time, diversity expands, system interactions get more complex, and cooperation is necessary to ensure the success of the community.
Similarly, early smart city programs consisted of a limited number of participants and technologies. Many were top-down efforts that emphasized using technology to help city systems operate more efficiently. Over time, communications networks and the Internet of Things (“IOT”) expanded connectivity across sectors, assets and citizens. Accordingly, the range of smart solutions and participants has skyrocketed, and smart city silos are giving way to collaborative arrangements across sectors, solution providers, stakeholder groups and infrastructure assets.
The impact of new technologies won’t be measured in social media “likes” or page views like before, they’ll be measured in lives saved and children fed; parents educated and renewable megawatts generated. Technologies like artificial intelligence, big data, virtual reality, and robotics are simultaneously coming into their own. Each will be as important as the waves that came before, but when you stitch them together, you get game changers like self-driving cars or security-providing drones.
Smart grid has been enabled by the IOT, in this case in the form of networked meters and sensors, coinciding with the revolution in energy generation and storage technologies. Transmission and distribution systems can be monitored and managed more effectively. But most importantly from a city point of view, distributed energy resources (DER) such as wind and solar or energy from waste, perhaps integrated with energy storage on microgrids, and perhaps supported by demand response (DR), are augmenting or replacing traditional energy sources from central generation plants. These newer sources are often on a neighborhood, city block or single property scale, and are poised to grow even faster once electric vehicle batteries are added into the mix. The IOT has enabled the near real-time control and management required for these innovations, as well as more granular monitoring of consumption (or generation) by consumers combined with billing and supporting data, through AMI.
LI is a crucial component of city planning and state and local government response. In emergencies, real-time monitoring can provide instant information to responders, in situations ranging from fires to crime or hurricanes. It can help aid workers distribute their social services in areas where they will have the most efficacy. After floods, like in Houston, city officials could determine which areas are worth rebuilding and which neighborhoods are too dangerous to continue to invest money in after multiple losses.
In the first article in this series, I argued that cities are complex, urban ecosystems that exist at multiple spatial and temporal scales and that do not permit the kinds of decomposition or systems engineering on which technology is based. Because of this, until we have a deeper understanding of what really makes the city a living entity, our progress on smart cities will be inherently superficial and of limited impact. In this article I ask: if we want to develop an understanding of how cities work, how would we go about this?