Urban phenology: Toward a real-time census of the city using Wi-Fi data

This paper develops a real-time census of the city using Wi-Fi data to explore urban phenology as a function of localized population dynamics. Using Wi-Fi probe and connection data accounting for more than 20,000,000 data points for the year 2015 from New York City's Lower Manhattan neighborhood - combined with correlative data from the U.S. Census American Community Survey, the Longitudinal Employer-Household Dynamics survey, and New York City administrative records - we present a model to create real-time population estimates classified by residents, workers, and visitors/tourists in a given neighborhood and localized to a block or geolocation proximate to a Wi-Fi access point. The results indicate that the approach has merit: we estimate intra-day, hourly worker and resident population counts within 5% of survey validation data. Our building-level test case demonstrates similar accuracy, estimating worker population to within 1% of the reported building occupancy.