This screen capture shows live CCTV footage using a face and vehicle recognition system in Beijing. Advances in technology are making it increasingly possible to detect and solve urban problems in real time. (Gilles Sabrié/for The Washington Post)

Many urban planners, artificial intelligence researchers, civil engineers and public officials aspire to create “smart” cities. Their goal is to deploy advanced technology to better study, monitor and manage urban growth and infrastructure, thereby helping cities become more livable, safe and sustainable, more functionally and economically efficient.

Making cities smarter is not a new idea. But with digital computers now able to store, process and interpret increasingly large amounts of data, and with significant advances being made in automation and artificial intelligence (AI), the potential for understanding, analyzing and taking quick action to enhance how cities operate has grown.

Geographic information system (GIS) technology was the first computer-based tool for achieving smarter urbanism. Envisioned in the 1960s, GIS evolved and gained widespread use beginning in the 1970s. Users could generate multiple highly detailed maps of urban or suburban areas, with each individual overlay displaying a specific layer of collected data.

GIS maps are useful for planning purposes because they go far beyond showing only jurisdictional boundaries, transportation networks, topography, cultural landmarks or tourist destinations.

Layers of GIS maps can show patterns of property ownership; household occupancy and income; property values and tax assessments; social and ethnic demography; types and locations of employment; building types, sizes and structural conditions; historic resources; utilities and public service networks, such as fire hydrants, streetlights and traffic signals; trees and vegetation; water and soils; and even meteorological data.

GIS maps contribute greatly to informed analysis and data-based decision-making by planners and politicians. But a stack of GIS maps is still a multilayered snapshot in time, a one-time picture describing a city’s composition and complexity at a particular moment.

To be truly smart, a city needs a dynamic, real-time information-gathering system, which is what “smart city” advocates envision. This necessitates installing throughout a city strategically positioned sensors — many of which would be video cameras — along with automated control devices linked to sensors.

I would call this a “geographic action system,” or GAS, to complement GIS.

GAS would continuously transmit real-time data about current city conditions — in video, symbolic or written form — directly to control devices or to human or robotic monitors. Monitors could immediately respond, initiating appropriate actions to alleviate or solve problems. GAS also could communicate directly with citizens, a task facilitated by citywide interconnectivity — public WiFi or satellite-based.

Traffic congestion, a persistent problem, could be addressed more dynamically using advanced technology. Transportation engineers have long proposed equipping urban roads with sensors enabling real-time monitoring and management of traffic conditions.

Why not continually adjust traffic-control signals to relieve congestion and improve vehicular flow, depending on time of day or week, weather, local events and shifting traffic volume? As cars and trucks become more technically sophisticated, GAS technology could suggest alternate routes of travel instantaneously to vehicles on the road.

We already have GPS navigation systems in cars and on smartphones — such as Waze and Google Maps — showing real-time traffic conditions, along with locations of gas stations, restaurants, hotels, shopping and other destinations. Parking garages can now display at their entrances the number and location of available spaces. Likewise, GAS could report on available public parking spaces throughout a city.

Cable communication companies can locate and repair network breakdowns, and Pepco can pinpoint systemic electrical outages, if they are paying attention. Similarly, a city could monitor, detect and rapidly respond to breakdowns or lapses in public services.

GAS could be on the lookout for flooding, blocked storm drains, icy roads, potholes, fallen trees, uncollected or spilled trash. It could dispatch crews as well as issue alerts, as D.C. does now for road closures, temperature extremes, fires and crimes, which often are recorded by privately installed CCTV security cameras as well as by cameras installed by the police. In London, with reportedly more than 500,000 CCTV cameras conducting surveillance only to detect law-breaking, the city could become much smarter by using its cameras to look for much more than criminal activity.

Whether in D.C., London or any other city, a continuously monitored metropolitan network of sensors would further augment public safety; would quickly identify city problems; and would remedy problems by more efficiently deploying city resources.

Of course, privacy questions arise. Today, if you carry a smartphone, your location is already detectable, and you are captured visually every day by countless security cameras. But GAS, like GPS, would require no personal information other than how to communicate with you.

Is Washington today a “smart city”?

The city has gotten a bit smarter in recent years, but it has a way to go. Constraints include lack of necessary advanced technology and cost. Even with tens of thousands of video cameras and sensors installed today, the city cannot afford the many trained employees needed to continuously monitor and respond to all that goes on.

Achieving a really high degree of urban smartness will depend on evolving AI and automation technology. What’s needed are robots that can reliably process data from thousands of sensors, and that do not need to be paid, fed or housed.

Roger K. Lewis is a retired practicing architect, a professor emeritus of architecture at the University of Maryland and a regular guest commentator on “The Kojo Nnamdi Show” on WAMU (88.5 FM).