Poster Abstract: Sniffing out the City - Vehicular Multimodal Sensing for Environmental and Infrastructure Analysis

Assessing urban infrastructure and environment quality at scale remains a challenge. This work presents a multimodal sensing framework that integrates computer vision-based infrastructure analysis with mobile air quality monitoring to explore urban conditions beyond the camera’s field of view. A vehicle-mounted system captures video data for semantic segmentation of roads and buildings while an air intake unit collects temperature, humidity, CO2, TVOC, and AQI levels. A preliminary test drive in Ann Arbor demonstrated expected correlations between CO2 and TVOC spikes in dense urban areas, providing a proof of concept for linking environmental sensing with visual urban analysis. Future work will refine sensor calibration, adaptive sampling strategies, and predictive modeling to improve accuracy and scalability.