This paper describes a prototype of the ExpoLIS system, which aims at: (1) informing citizens regarding the air quality of their surroundings and how to cope with it (e.g., choosing commuting routes according to a health model); and (2) gathering dense spatiotemporal air quality data to support the empirical work of environmental experts. The system is composed of: (1) an affordable and custom vehicle-mounted sensor network for air quality monitoring; (2) a server to store, process, and map all gathered geo-referenced sensory data; and (3) a set of user-centred visualisation and prediction services tailored for citizens and environmental experts. Experimental validation of each component of the proposed system shows that the current prototype is capable of tracking spatiotemporal air quality changes and of providing users with access to these events via a set of interfaces. The results show evidence of a strong correlation in static situations (R2 of 0.96 for PM2.5) between the proposed low-cost all-weather system and a high-cost equipment with no weather protection. The results also show a weaker correlation (R2 of 0.57 for PM2.5), but still satisfactory, in dynamic settings. In short, this paper presents experimental evidence that supports the claim that the ExpoLIS system is feasible and valuable to both citizens and environmental scientists.

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Air pollution,Air quality,Human exposure,Mobile sensor networks,Scientific data visualisation,Awareness

• Computer and Information Sciences - Natural Sciences
• Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
• Environmental Engineering - Engineering and Technology