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Like any smart system, a Smart City is one in which sensor-driven data collection and powerful analytics are used to automate and orchestrate a wide range of services in the interests of better performance, lower costs and lessened environmental impact.
Smart Cities are evolving along a number of paths, but one of the more common aspects is in the area of traffic management. The advent of autonomous cars is creating an opportunity to connect a wide range of roadside devices — everything from traffic lights to lane markings — in an effort to optimize traffic flows.
For instance, an autonomous car receiving a signal from a traffic light as to when it will change color will allow the car to speed up or slow down almost imperceptibly to avoid coming to a full stop, reducing fuel consumption and avoiding traffic tie-ups.
Eventually, this could evolve into the abolition of traffic lights and stops signs altogether as autonomous vehicles learn to avoid each other at reasonably high speed, even through complex intersections.
Meanwhile, the data collected from sensors can be fed into central computers to look for patterns that contribute to poor traffic flow and other issues, allowing city planners to first test and then implement repairs and alterations to streets, highways, bridges and other municipal structures.
This same technology can be used to improve a vast array of other city services, including:
Machine learning can be used to improve the efficiency of triage and tracking of disease and infection. AI can be used to increase the precision of robot surgeons, and virtual nurses can be used to assist human ones in their tasks. AI can be used as well for streamlined billing, after-care, pharmaceutical processes and more;
Improved service delivery and conservation, and greater insight into infrastructure health. Together with satellites, AI can predict soil moisture and nutrient levels on farms to grow more crops with less water.
More efficient utilization and streamlined introduction of wind, solar and other renewables through the application of AI-controlled smart power grids;
Predictive analytics can provide better insights into pressing issues to improve the efficiency through which they are managed. Better outreach to those in need, and coordination of resources and an overall reduction in bureaucracy.
AI-powered solutions can collect and analyze building data coming from many data points such as power, humidity, CO2, temperature, light and many more. This data can be used for improved analysis of short- and long-term trends, upgrade/repair requirements, waste reduction and reduced energy consumption.
Neural networks can predict traffic in all locations by employing mathematical models that solve spatio-temporal correlations between different areas. In turn, this can be used for improved tracking of crime patterns, potential hazards and response data.
Smart technologies are also expected to vastly improve citizens’ access to services, in large part by streamlining communication between citizens and government agencies. We’ve all endured the long lines and complicated processes in, say, the Department of Motor Vehicles.
With smart technology like natural language processing and neural networking, citizens should be able to conduct a wide range of basic activities through an automated call center or web portal, vastly reducing wait times for those in need for more complex services.
At the same time, a steadily growing municipal knowledge base will be able to deliver the right information in a timely manner as to exactly what is required for any given result — no more waiting in line for hours only to find that you don’t have the right forms in hand.
With urban populations on the rise, smart cities are seen as the key to enabling safe, vibrant environments on a sustainable basis. Much of the technology is still evolving and the vision of a smart city is still rather vague, but the idea has firmly taken root in the public consciousness.
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