Smart Cities Require Much More Than Smarter Devices
There’s been a great deal of buzz over the last few years about smart cities, which can be broadly defined as cities that are using data-driven technologies to meet the challenges faced by today’s rapidly growing urban communities.
With over 50% of the world population now living in urban settings and 68% projected to be residing in urban centers by 2050 , it’s imperative that cities across the globe find innovative solutions to relieve the strains on resources, infrastructure, and public services that come with this unprecedented growth. Many city governments are rising to these challenges by employing smart technologies that generate massive amounts of real-time data – collected and shared through ever-expanding networks of IoT devices – to increase responsiveness, augment resiliency, maximize efficiency, and enhance the quality of urban life for all who reside there.
The (seemingly) obvious benefits of connected infrastructure, e-government, and massive-scale analytics will require, however, a lot more than impressive technologies before they materialize. Yes, there are numerous smart city initiatives that are showing great promise; but a decade after the first smart city initiatives were launched, driven by enthrallment with the efficiencies gained by simply installing digital interfaces into existing infrastructures, the smart city movement still faces many technical challenges as well as non-technical hurdles before its benefits to urban society can begin to be fully realized.
In short, smart cities require a lot more than “smarter” devices.
Essential Elements of a Successful Smart City
If the goal of a smart city is to leverage data and digital technology to enhance responsiveness and make cities more livable, then what does it take for a smart city initiative to achieve these goals?
At the foundation of any smart city solution is the integration of information and communication technology (ICT) with IoT to create an infrastructure of sensors that collect data, and devices such as smartphones that can talk to each other over high-speed communication networks. But this interconnectivity, along with the increasingly sophisticated devices used to access it, represents only the first step in the development of smart city infrastructure that can meet the challenges faced by today’s booming urban centers. Other elements that are proving essential to transformative smart-city technologies include central databases, application interfaces, open data portals, and AI-driven analytics.
Here, we highlight some smart city initiatives that showcase different elements needed to attain the ideal of a truly smart city.
Chicago’s Open Data Portal
The importance of transparency and open access to the massive amounts of data that are being captured cannot be overstated, and cities that provide this are ahead of the curve in regard to scaling up smart city technology.
Since anyone with access to the internet can browse Chicago’s open data portal , for example, it can empower everyone from educators teaching analytical skills in the classroom to entrepreneurs developing new products to local activists advocating for change.
New York City Listens for Gunshots
New York City’s ShotSpotter system provides a good example of machine learning technology that enhances government responsiveness in the realm of public safety. Using a network of strategically placed audio sensors that can identify the signature sound of a gunshot, the ShotSpotter system monitors certain areas of the city for the sound of gunfire. When microphones pick up the noise of gunfire, the system transmits detailed information such as the location and number of shots fired and the speed and direction of the bullets to an acoustic expert. If the information is confirmed as accurate, the system accesses the city’s databases of surveillance videos, addresses, location crime histories, police warrants, and gun permits and delivers all the relevant data to the responding police officers to have on hand when they arrive on the scene.
Although this proprietary system is incapable of monitoring all areas, currently covering only about 20 percent of New York City, it’s giving police a substantial advantage in fighting violent crime.
Moscow Scans for Tumors
Moscow’s smart city efforts include a system that maintains e-health records and directs patients to the closest clinic; an AI-driven project that examines MRI and CAT scans, as a participant in GitHub’s open-source research library RadIO, looking for signs of breast and lung cancers; and another AI-based program that predicts virus outbreaks in the city’s schools so measures can be taken to prevent them from actually occurring.
Taiwan Predicts Harmful Air Quality Incidences
Another ambitious smart city initiative tackling public health issues is Taiwan’s program to monitor air quality. This system generates three-day predictions that allow citizens to take action to prevent exposure to harm, based on data gathered by some 140 monitoring stations that the government began installing back in 1993.
Technical Challenges to Smart City Implementation
Behind every smart city success lie the challenges that cities face to achieve that success. And given the scope and complexity of the digital networks driving smart city solutions, the technical challenges can be quite daunting. For instance, traditional data management systems designed for corporations need to be transformed and scaled to citywide proportions. Along with this, the underlying technology needs to be scaled for massive data throughputs and storage capacity.
The need for careful planning, cost-effectiveness, timeliness, and maximum uptime for government-funded projects also present major technical challenges for companies providing smart city solutions.
Non-Technical Hurdles to Achieving the Smart City Dream
There are also several major non-technical hurdles to overcome in order to create a truly smart city. Policymakers must be savvy about how they employ sensors, ICT, artificial intelligence algorithms, and other technologies needed to deliver on the promise of making cities work better for their constituencies. Tensions between data collection and personal privacy must also be addressed, as without buy-in from city management, law enforcement, and the public, advances in surveillance technologies will only cause these tensions to escalate.
Thus, careful analysis, dialogue, public input, and consensus – not simply smarter devices – are key to transforming the smart city dream into a reality.