Powering the "Conscious City": How Data Drives the Electric Mobility Network

Installing EV chargers in our cities without managing the data they produce is like building roads without traffic lights. The gap between a smart, digital urban landscape—one that breathes in real time and acts ahead of the curve—and an old-school analogue version relying on historical records can be life-altering. It affects everything from air quality and public transport to how easily we access vital services.

Santiago Garcés, CIO for the city of Boston, views urban data as “data products.” This is the strategy the US city council uses to ensure every department is on the same page, making it much easier to analyse trends and provide better public services.

The ultimate goal of modern local government “shouldn’t be for the citizen to learn how to navigate the bureaucracy, but for the system to adapt to the citizen.”

The response from city agencies has been to “open up their own systems and share more information, meaning automated data connections (ETLs) have tripled to nearly 900.” Breaking down these information silos in the public sector—and across many private organisations—is no longer a pipe dream.

The ultimate goal of modern local government “shouldn’t be for the citizen to learn how to navigate the bureaucracy, but for the system to adapt to the citizen,” adds Santiago Garcés. This is the paradigm shift that AI is introducing into municipal management, with the potential to transform everything, including electric vehicle charging infrastructure. Welcome to the Conscious City.

The first hurdle is getting hold of high-quality info. Boston is currently working with the startup Cvyl, which uses smart vision—boosted by LiDAR and high-resolution photography—to harvest data for a digital twin. This virtual model then helps sharpen the way public policies are tested and refined.

It is a very similar approach to the one Detroit used to get back on its feet after going bankrupt in 2013. Today, the city has a centralised hub of information, including projects like Detroit Street View, built on the idea of “mapping everything.”

The perks of smart data management often crop up in unexpected places. For instance, research in New York found that pedestrians and cyclists are three times more likely to be killed or seriously injured by a vehicle turning left (19%) than one turning right (6%). Armed with that insight, the NYC DOT rolled out the Left Turn Calming programme at 1,101 intersections, leading to a 33% drop in serious injuries.

In the age of smart cities, the ability to quickly pull together multimedia data from CCTV, Internet of Things (IoT) sensors, and social media creates both massive opportunities and challenges. New “super-resolution” techniques use clever algorithms to clean up grainy footage. Cameras are no longer just “eyes” watching the street; they are becoming the “brains” of the operation.

The second big challenge is accessing and making sense of information as it happens. Generative AI is creating a whole new world for urban mobility, as data once trapped in departmental silos is finally being brought into the light and integrated into central platforms.

Linking traffic models with air quality data in the Belgian region allows for the simulation of the effects of local traffic measures on mobility and the environment.

The DUET project in Flanders created a traffic model that predicts exactly how many cars will flood onto surrounding streets if one or more roads are closed. This highlights the third big win for innovation: joining the dots between different sectors. Linking traffic models with air quality data in the Belgian region allows for the simulation of the effects of local traffic measures on mobility and the environment.

Stephen Goldsmith at Harvard has suggested merging classic statistical models like CompStat (used for real-time crime mapping) and CitiStat (which tracks the state of public facilities) into a single concept: StatGPT. These act as the city’s dashboard. Combining them creates a new “brain” for the city, moving the authorities from a reactive “wait and see” approach to a proactive, more efficient way of working.

This approach is now a vital tool for managing energy demand in real time—the “missing link” for cities trying to make their EV charging networks actually work. This spring, two EU-funded projects will wrap up, both aimed at helping cities stop guessing based on old stats and start acting on what is happening on every street corner, right now.

One of these, UrbanMind, is based in Kranj (Slovenia) and Pula (Croatia). It uses micro-location tech to spot when a massive traffic jam is about to hit a high-pollution area, allowing the city to divert traffic before it happens. This doesn’t just save time; it prevents a localised public health crisis.

If we apply this to the electric car network, a Conscious City equipped with predictive analysis can steer drivers toward charging points that will be empty the moment they arrive, preventing queues and keeping traffic moving.

Chargers must be placed where the data says they are needed. By looking at traffic flows, heat islands, and pollution levels, a city can encourage people to charge in areas where we need to swap out old engines for cleaner ones to improve local air quality. It is about moving from passive charging to smart, active management.

This is the path being taken by ACCIONA Energía. Beyond its network of 1,300+ charging points in Spain, it is heading up projects that explore new ways to fit electric mobility into the city. These include the Vicálvaro hub—the biggest public renewable-powered station in Madrid—and V2X tech, which lets cars feed power back into the grid or into buildings to help balance the load.

The company is also trialling a smart dynamic balancing platform to manage charging points more efficiently. This system links charger data with building management systems to tweak power use based on demand, cutting out expensive spikes. Because it works like a smart grid, it can even reverse the flow, sending electricity back when the grid needs it most to keep things stable.

Urban logistics account for over 25% of transport emissions in our cities. Europe is currently pushing for urban “micro-hubs,” where goods are moved onto smaller, cleaner vehicles like cargo bikes. This is exactly what the DECARBOMILE project is doing at the San Blas Market in Logroño. Meanwhile, Bologna (Italy) has been testing light electric delivery vans, and Athens (Greece) is betting on shared EVs and smart lockers.

For on-demand transport services, the number of vehicles on the road is usually dictated by the morning and evening rush, meaning many sit idle for the rest of the day. This surplus capacity is a huge opportunity for vehicles to take on other jobs.

Tests in Cambridge (USA) and San Sebastián have looked at using the same vehicles for both passenger trips and food deliveries. The results show that this “multi-tasking” approach can significantly shrink the overall size of the fleet.

Better data-gathering, treating that information as a standard “product” to help officials coordinate, and the power of AI are set to transform our EV charging networks. We are starting to see that the payoff for building this infrastructure goes way beyond just ditching fossil fuels; it is about making our cities healthier, cleaner, and better places to live.

Sources:

Eugenio Mallol is a journalist specializing in technological innovation. He created the INNOVADORES supplement in El Mundo and La Razón, which he directed for 11 years. He is currently Director of Strategy and Communications at Atlas Tecnológico, as well as analyst and coordinator of the Science and Society Chair at the Rafael del Pino Foundation. He is a columnist for Forbes Spain and contributes to digital outlets such as InnovaSpain and Valencia Plaza. He is also the author of books and reports on technological innovation and a frequent speaker.

Information on data protection