Digitally enhanced cities that use data gathering tools to improve life within cities
This essay is part of a futurism series focusing on creating long-form wikis of futurism topics. Futurism’s definition: the study of trends and technologies that will create the future. Essays in this series are designed as wikis to answer key questions about a variety of futurism topics. If you already know about a section, skip it and move on to the next.
The term “smart city” is loaded with hyperbole and is typically used when referring to cities of the future. But it’s rare to find a concrete definition of a smart city with details on what they actually are. This essay breaks down the components of a smart city to develop a definition for what makes a city “smart” and lists key challenges with updating city infrastructure to live up to the hype.
What is a Smart City?
The bottom line is that cities become “smart” by collecting massive amounts of data on city systems and then use the data to improve the city infrastructure. Smart cities take the strategic and longterm view that data collection and aggregation will lead to more effective management strategies.
As a society, we are at a point of convergence where independently useful technologies can be used in harmony to address city challenges and increase the quality of life for inhabitants.
The rise of mobile technology not only changed the way people access the internet but changed the way cities operate. Mobile solutions such as ride-sharing and micro-mobility help to curb congestion. But some of the on-demand elements of mobile ordering also increased congestion in key areas. Cities began to adopt mobile technology in order to move away from coin-operated parking meters towards the more logistically friendly parking apps.
Cities such as New York are beginning to implement mobile payment options for subway systems to increase the speed with which users can interact with the system. The smartphone is becoming an increasingly important aspect of everyday life. Cities that are attempting to gather more data on their populations will need to treat smartphone interactions as a critical area of growth moving forward.
Why do cities need to gather data?
Cities gather data for a multitude of reasons but primarily do so to provide proper infrastructure to support the lives of inhabitants. By collecting data on residents, infrastructure use volume, visitor information, etc., city governments can properly allocate resources to create and enforce a safe and consistent environment or residents.
No one likes to be taxed but most people will agree that it’s necessary to fund public services. In order to be efficient with spending tax dollars, cities need to make data-informed decisions to ensure that urban planning is proactive as opposed to reactive. Residents want to know that their tax dollars are being spent for sustainable and longterm solutions, not put to projects that have limited use cases and inconsequential value.
As an example, by cross-referencing data from micro-mobility services with parking app information, a city can determine if underutilized parking spaces would be better utilized as bike lanes.
How are cities currently gathering data on inhabitants?
Cities use many methods to gather data but in an increasingly digitized world, the ability to collect different types of data is growing. Traditional methods of data gathering include census surveys, metro smart cards, and taxation to name a few. These types of data gathering are very human-centric, meaning that the data is captured by the city actively engaging the populace to provide specific information about themselves.
Cities also perform passive information gathering strategies such as monitoring traffic volume with “road tubes”. Road tubes are a set of black wire-like tubes that are placed in the road at a set interval to measure car axels that pass over them. They measure average daily car volume on a specified road and in some instances, they can be used to monitor average speed.
Road tubes have been an effective data gathering method but have several real downsides such as lack of permanence, man-hours required for setup and risk of injury for the installers.
Road tube installations are one example of a data-gathering process that cities are targeting for disruption using permanent IoT devices.
How will “smart cities” gather data?
Smart cities are looking to take advantage of the connected device revolution that is known as the Internet of Things (IoT). Like the hype surrounding smart cities, IoT as an industry often has a lot of hyperbole and false narratives surrounding it. In the context of smart cities, think of IoT as the ability for cities to integrate small sensors throughout city infrastructure to gather and aggregate data. These embedded systems are partly a result of the innovations in the semiconductor industry that allow for quality data gathering at scale with a sense of permanence that is not currently available.
Examples of IoT implementation include permanent road sensors measuring traffic volumes, speeds, real-time parking space availability and accident reporting. Transportation improvements include electronic tolling equipment such as E-Z pass, mobile-enabled metro passes, and systems to differentiate between resident and non-resident access.
A major benefit of IoT is the ability of these sensors to come with built-in hardware necessary for internet connection. This will provide for real-time analysis and faster reaction times to typical issues such as traffic congestion and emergencies. It is expected that the global demand for IoT devices will grow at a CAGR of 21% through 2026.
Regardless of the hype, IoT devices alone will do nothing to improve city conditions. For these devices to be useful, cities will need to take a comprehensive approach to update digital infrastructure.
What cities need to facilitate data gathering at this scale?
Cities will need to implement 5G or 5th generation telecommunications networks and take advantage of 5G’s three main attributes to enable IoT devices at scale.
5G network infrastructure attributes include the speed by increased upload/download capabilities of connected devices, increase the network’s ability to support large numbers of connected devices and provide the improved latency needed to support massive IoT infrastructure. Think of latency as the ability for devices to remain connected without service interruptions, this is essential for real-time reporting.
Once cities have effectively implemented the IoT system, they will have massive amounts of data to sort through and develop actionable insights from. The problem is that most cities struggle to attract and retain top technical talent. What this means is that cities will need to focus on contracting out work and developing Public-Private Partnerships to develop and implement Artificial Intelligence (AI) and Machine Learning systems. These systems will be essential to make sense of all the information gathered in real-time.
Think of artificial intelligence systems as resources that are able to gather information and take actions based on a set of pre-programmed rules. With preset guidelines, AI systems can operate in the absence of a human handler. This is especially important for cities that struggle to attract and retain the type of talent needed to regularly make sense of data. In addition to standard AI, cities will want to systems that include machine learning so that the software can predict, model and test improvements to the city.
As these systems become more robust, cities will look to interact with residents through services such as AI chatbots to ensure a baseline of service as well as to gather, model and make sense of additional resident data.
What are the challenges associated with these types of upgrades?
There aren’t enough skilled workers to address all the needs of the cities that are out there. Competition for skilled labor is fierce and can be viewed as a zero-sum game. Some cities will benefit at the expense of others. Because of this, companies that position themselves to contract out their skilled labor with cities that want to upgrade will be well-positioned to profit from the smart city revolution.
The implementation of city infrastructure upgrades will take a significant amount of time and money. There is no framework or ideal model of a smart city to follow. Cities are charting their own path and add components of data tracking on an incremental basis as funds become available. Because of the incremental nature of the changes, there will be incremental improvements from these upgrades. This is a key element of breaking up the hype around smart cities.
Much of the IoT gadgetry that is expected to drive value for smart cities is still under development. It doesn’t exist yet.
There is no real timetable for the rollout of across the board infrastructure for cities. What’s clear is that it will take the better part of a decade to roll out the complex 5G network, install IoT components and develop frameworks and processes for utilizing this massive dataset.
As with any internet-enabled data-gathering initiative, there are major privacy and security concerns. Determining what are the appropriate levels of data gathering and the security measures cities take to prevent theft and improper use of the data will vary on a city by city basis. Cities will need to properly allocate resources behind new security measures and enforce digital systems that are patchable to adapt vulnerabilities such as DNS attacks.
Cities will also need to develop data management best practices that are applicable now and scale for future needs. As more “smart” systems come online the data management processes will need to effectively scale to the new demand.
City-data will need to be treated as a public good or utility. Data will need to be made available to the public which in turn will require systems and processes for releasing the data in a usable but secure way. Moving forward, new cabinet-level administrative positions will be required to monitor and manage city data lakes to protect and cultivate this value for city residents.
Examples of companies building technologies for Smart Cities
Big Data: SAP, Oracle, Azure Data Lake, and many more
Cloud Infrastructure: Amazon Web Services, Microsoft Azure, Adobe, Kamatera
5G: American Tower, Qorvo, Ericsson, Verizon, Qualcomm
AI/Machine Learning: Google Deepmind, IBM Watson, Amazon AWS Machine Learning, OpenAI, Nvidia and many more
Smart city models and what they mean for residents and visitors
Smart cities will use technological upgrades to gather better data on the people and systems. The information and insights gathered within their boundaries will help to develop value for all within the city limits. City upgrades will require considerable expenditures and will impact the privacy of visitors. Although there are negative aspects of these changes, they aim to reduce challenges associated with congestion, pollution, and nearly all other forms of public services provided.
Cities that go through these changes can expect a lot of hype and lofty expectations surrounding new initiatives. Inquisitive residents can be skeptical of any short term claims as many of the infrastructure upgrades will take most of the decade to fully implement. With that in mind, expect changes to the quality of services to be gradual but valuable. Ultimately, the adoption of digitized data gathering will make help to improve the quality of life within and should be championed by residents.
Definition of what a city is:
A city is an area of land that is characterized by the large population of people that reside within the area. Because of the large numbers of people in close proximity, traditional housing is limited, high rise buildings are common and there is typically little to no agriculture within the city area. The UN reported that as of 2018, there were 531 cities with a population of more than 1 million people and estimate this number will grow to 701 by 2030. The same study indicates that 1 in 5people or roughly 23% of the world population lives in cities of greater than 1 million.
The bottom line is that cities are expected to grow considerably in number and size over the next 10 years.
Cities are under constant transformation, characterized by infrastructure development and planning that is unique when compared to rural land.
Construction creates new buildings, construction repairs pre-existing infrastructure and construction installs new technologies. Simultaneously, populations come and go at rapid rates. Older cities around the globe are a latticework of old and new infrastructure and the merged components are what defines modern cities. The patchworked infrastructure can at times be both impressive but also bizarre and frustrating to residents.
As the information age continues to blossom, cities are transforming their latticework infrastructure from purely physical to a hybrid model including digital elements in many ways. The purpose of this transformation mimics much of the rationale behind all digital transformation. It brings increased connectivity, allows for the aggregation of data and ultimately improves the experience for city dwellers. The changeover to digital infrastructure signals the “smart” in the term smart city.
To give some perspective on the significance of this changeover, CB Insights estimates that nearly $1.4 trillion will be invested in upgrading global city infrastructure over the next 6 years alone. But this dollar amount is meaningless without the context of the type of infrastructure required to maintain a city.
What services does a city government offer?
Government infrastructure exists to provide services that address the challenges caused by collective action issues within communities. This includes garbage removal, public sanitation, wastewater treatment, stormwater drainage, maintenance of public spaces like parks, sidewalks, art and cultural sites.
Cities also conduct urban planning through zone permitting, creating regulations and budgeting for current and future city needs.
Cities provide safety services such as police, fire & rescue operations and support public health through hospitals. They support transportation by planning and funding airports and rail networks, support urban renewal initiatives, conduct taxation and manage power plants along with other utilities.
Other areas of public works include street cleaning, installation of traffic lights, street lights, libraries, and ensuring there is affordable housing.
These service offerings are fundamental to a well-run city and when they are effectively managed, a city thrives. When poorly managed, the city falters. The digitization of many aspects of these urban planning and service-oriented initiatives are fundamental components to understanding how new technologies are enabling “smart cities”.
But before its possible to understand how new technology can help a city effectively manage itself, its important to understand the unique challenges that these activities entail.
What challenges do cities face?
City areas have dense cores with surrounding areas described as urban sprawls. The size of a city and its development of the surrounding land leads to challenges that are unique from rural zones.
As a direct result of the massive size and scope of cities, one of the biggest challenges is implementing logistical systems. Challenges arise from transporting goods and services to and from the city which are required at a constant rate to support the population. As this “freight” comes from outside the city to centrally located distribution points it enters what is referred to as the “last mile” in supply chain logistics. The coming and going of these goods creates congestion, environmental concerns such as air and noise pollution, and potential safety issues.
Congestion is an increasing challenge to city management as e-commerce shipments and direct to consumer shipping have grown exponentially over the last few years. The desire for speed of delivery with initiatives by Amazon such as same-day delivery will increase the number of freight movements necessary to keep up with the demand. This increase exacerbates preexisting challenges.
Increased congestion leads to crowding and general health concerns.
Smog is a great example of a challenge that densely populated regions with large amounts of industry face. The air pollution levels are a significant contributor to the declining health of the city population, reduced visibility triggering travel delays and direct impacts on global warming.
Cities are also vulnerable to a variety of natural disasters depending on their location. Disasters cause considerable damage to city infrastructure, loss of wealth and life of those living within the regions of the disaster. Natural disasters have been shown to correlate directly with population decline. And when residents leave one city, they go to another.
Cities also struggle to stay relevant under changing commercial environments. The history of a city such as Detroit is a story of a meteoric rise in tandem with the auto industry followed by a fall into dilapidation as the auto industry struggled. When a city’s industrial complex becomes obsolete, it drives population decline.
As city populations continue to rise as is expected, the challenges cities face in delivering their services will also increase. Cities are trying to take “smart” approaches to adapt their systems and infrastructure to address these challenges.