In PHASE 2 OF AI4CITIESINSIGHT SIGNALS combines social science with data science to create a digital twin of a city that can help municipalities address the challenges of modern mobility and help them shift to cleaner transportation. Insight Signals sees itself working in the context of the ‘New City’ which aims to be livable, clean and net-zero emissions by 2050

While cities are currently working with static digital twins, Insight Signals has developed a dynamic digital replica of a city’s transportation system. This replica simulates users’ mobility at micro levels, and calculates mobility-related CO2 emissions, thereby providing mobility managers with detailed mobility patterns. The model is customisable to any city. 

To develop the city replica, Insight Signals combines two digital twins. The first one is an Infrastructure digital twin, whose goal is to determine a list of itineraries, categorised by means of transportation, between all departure and destination points. The second digital twin is a digital replica of a city’s individual mobility users. Its goal is to generate a set of ‘digital mobility users’ with their own attributes and behavior, which could potentially help predict citizen behaviour. Insight Signals emphasises that this does not rely on individual citizen data, and that it is GDPR compliant. 

#By simulating the mobility activities of each digital user, for each day of the year, and combining that with a probabilistic simulation, based on the user’s own set of activities and mobility preferences, Insight Signals can create a database recording municipal mobility patterns and the resulting Co2 emissions. With this information, municipalities can make adjustments in their real infrastructure. In addition, they have the opportunity to use the model for scenario testing and predict how different decisions could have different effects on CO2 emissions. (link to the article from the AI4CITIES)

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