Sensor Fusion and The City: Visualisation and Aggregation of Environmental & Wellbeing Data

The proliferation of miniaturized electronics has fuelled a shift toward environmental sensing technologies ranging from pollution to weather monitoring at higher granularity. However, little consideration has been given around the relationship between environmental stressors (e.g. air pollution) and mental wellbeing. In this paper, we aim at capturing fluctuations in momentary wellbeing and behaviour in response to changes in the ambient environment. This is achieved using a multi-sensor fusion approach that simultaneously collected urban environmental factors (e.g. including PM10, PM2.5, PM1.0, Noise, Reducing gases, NH3), body reactions (physiological reactions including EDA, HR and HRV) and users perceived responses (e.g. self-reported geo-tagged valence). Our approach leverages an exploratory data visualisation along with geometrical and spatial data analysis algorithms, allowing spatial and temporal comparisons of data clusters in relation to people's wellbeing. The effectiveness of our approach is demonstrated through a positive correlation between environmental factors and physiology reactions. By implementing spatial visualisation with our real-world data shows the potential opportunities to understand how the environment can effect mental wellbeing.

Automated summary

This study explores the impact of environmental factors on mental wellbeing by collecting urban environmental factors, body reactions, and users' perceived responses through a multi-sensor fusion approach. Using data visualization and spatial data analysis algorithms, the study highlights the potential opportunities to understand how the environment can affect mental wellbeing.