Distributed sensor networks are increasingly used to collect high-resolution environmental data over extended time periods. However, it is unclear how to best design a sensor network to capture temporal and spatial variability of environmental factors in urban areas. This paper presents a real-world study to collect particulate matter and meteorological data via handheld sensing devices. The results show the power of mobile sensing networks in collecting spatially dense data and demonstrate their potential to capture temporal variability. The contributions of this work include a novel mobile sensor study design and affirmation that mobile sensing is worthwhile for urban data collection.<\/p>\n","protected":false},"excerpt":{"rendered":"
Distributed sensor networks are increasingly used to collect high-resolution environmental data over extended time periods. However, it is unclear how to best design a sensor network to capture temporal and spatial variability of environmental factors in urban areas. This paper presents a real-world study to collect particulate matter and meteorological data via handheld sensing devices. 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