Mexico City Smart City initiative, Digi Mart USA News (Mexico City): The installation of AI-based smart traffic lights is one of the first measures of the Mexico City government in its push to become a Smart City, with mobility as a priority. Juan Pablo De Botton Falcón, the capital’s secretary of administration and finance, made the remarks during his participation in the México IA+ event.
The new systems will no longer follow a fixed color-change cycle. Instead, they will detect vehicle loads to adjust the timing of signal changes, which is expected to produce better traffic flow and reduce travel times by up to 20 percent.
“The idea is to apply technology to save people time,” De Botton Falcón said.
The traffic lights will also be able to give priority passage to public transport units, through systems that will cover trolleybuses, Metrobús, the light rail and RTP buses. Technology will be used in other mobility areas as well, including digital twins that can project impacts in real time, such as those of planned renovation work on the Mexico City Metro.
“It serves to experiment, run simulations, and see the impact a construction project will have on traffic,” he said. He added that the city aims to minimize disruption, citing its intervention on Line 3 as an example, which is being carried out with the fewest possible effects on riders.
De Botton Falcón explained that becoming a Smart City “is not only about digitization; it has to do with how inhabitants interact in the physical world with technology or artificial intelligence.” He acknowledged that the public has not been sufficiently informed about the scope of AI, and said the risks and benefits of these technologies must be understood for them to be accepted.
The city is also advancing digitization efforts to obtain data, including plans to digitize the land registry. De Botton Falcón said the city already has an Oracle database that was not well linked to maps, and that work is underway to correct this.
Brenda Olivas, Senior Solutions Architect at NVIDIA, cited the example of the French national rail operator SNCF, which used connected digital twins to assess maintenance, train tracking and energy consumption based on captured data. “We have to understand and look for patterns in the data that are truly useful to us,” she said.
