Data Analytics

Agent-Based Modeling of Pedestrian Mobility in the City From Research to Opportunity: Unlocking the Value of Pedestrian Flow Data

Understanding and predicting pedestrian flows across a city is critical for smarter urban planning, infrastructure investment, and business decision-making. Traditional data collection is expensive, fragmented, and limited in scope, making large-scale insights difficult to obtain. Our solution: a city-scale Agent-Based Modeling (ABM) platform that combines high-resolution spatio-temporal and GPS-based walking data with advanced Machine Learning […] Read More >