“By analyzing the content of each image, correlating different images, and creating new layers of information, we could help cities and other users not just identify risks – like floods, heat islands, or environmental degradation – but understand why these risks exist and how they evolve over time,” he says. The compute power that AWS provides means that such analysis has gone from taking many months, involving a bunch of experts, to something “cities can do in mere hours.” This powerful combination is already yielding real-world results. “Naples has used the system to map urban heat islands in order to prepare for days of extreme heat, while Helsinki has used the data to monitor greenery in the city and plan green infrastructure to help mitigate urban heat waves. It has reduced peak temperatures in some urban areas by an average of two to three degrees Celsius,” explains Volpe.
“Meanwhile, urban planners in Milan were able to identify critical infrastructure risks within 48 hours of looking at the data.” These new ways of working have not been without challenges for traditional town planners. “Shifting from manual processes to AI-based, data-driven decision-making requires a change in mindset and often resistance is encountered due to unfamiliarity with the technology,” says Volpe. Integrating satellite data with local data sets also proved a challenge, as did fusing the insights from AI with existing systems. Working with AWS has allowed the firm to develop, train, and deploy machine learning models at scale.
“These models process terabytes of data, providing insights to city planners and infrastructure managers in a fraction of the time traditional methods would take,” says Volpe.
With cities operating on tight budgets, the upfront costs of the system can seem prohibitive, but Volpe believes that using AI can slash the costs associated with manual data processing by up to 60%. One of the aspects of the platform that is proving most useful is predictive modeling. “Cities can simulate different scenarios and forecast the impact of climate change, making informed infrastructure planning decisions,” explains Volpe.
Future projects include the creation of digital twins of urban environments. “These virtual models will simulate the future impact of current urban planning decisions, helping municipalities and governments visualize how infrastructure changes or new developments will interact with environmental conditions over time,” he says. “The computational power and real-time data handling capabilities of AWS will play a pivotal role in building and maintaining these digital twins, providing cities with a constantly updated virtual replica for decision-making,” he adds. Latitudo 40 also wants to integrate its satellite data analytics with Internet of Things (IoT) sensors that are deployed across urban environments, allowing cities to monitor real-time conditions, such as energy usage, traffic flow and pollution levels.
“We're helping cities lower peak temperatures, monitor sustainability goals, and protect against climate threats.”
“With AI on AWS, Latitudo 40 is shaping a future where data-driven insights can guide us towards a more sustainable planet for generations to come.”
