2013 · 87 citations · 12 references
Public HealthEnvironmental SciencesUrban HealthAir PollutionEnvironmental HealthMobile ComputingAir PollutantsAir Pollution MeasurementAir QualityCollaborative MappingMobile SensingParticulate MatterAir Pollution MappingGranularityLow-cost Air Quality SensorsPersonal Exposure MonitoringReal-time ProcessingSpatial GranularityUrban Air Quality MonitoringUrban Sensing
This paper describes our experiences with building and deploying a low-cost participatory system for urban air pollution monitoring in Sydney. Though air pollution imposes significant health costs on the urban community globally, today's published data on pollution concentrations is spatially too sparse, and does not allow for sufficiently accurate estimation of exposures for (potentially mobile) individuals in order to make medical inferences. The HazeWatch project described in this paper uses several low-cost mobile sensor units attached to vehicles to measure air pollution concentrations, and users' mobile phones to tag and upload the data in real time. The greater spatial granularity of data thus collected enables creation of pollution maps of metropolitan Sydney viewable in real-time over the web, as well as personalized apps that show the individual's exposure history and allow for route planning to reduce future exposure. We share the insights we obtained from building and trialling such a system in Sydney, and highlight challenges that can be addressed collaboratively by groups developing similar systems world-wide.
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Prabal Dutta, Paul M. Aoki, Neil Kumar et al. · 2009 · 382 citations
Public Health, Environmental Sciences, Environmental Social Science +17
Karl Aberer, Saket Sathe, Dipanjan Chakraborty et al. · 2010 · 117 citations · Full text
Micro Sensor Node for Air Pollutant Monitoring: Hardware and Software Issues
Sukwon Choi, Nakyoung Kim, Hojung Cha et al. · Sensors · 2009 · 103 citations · Full text
Engineering, Environmental Engineering, Environmental Sciences +15