Amenity counts significantly improve water consumption predictions.

ABSTRACT: Anticipating the increase in water demand in an urban area requires us to properly understand daily human movement driven by population size, land use, and amenity types among others. Mobility data from phones can capture human movement, but not only is this hard to obtain, but it also does not tell where the population is going. Previous studies have shown that amenity types can be used to predict people's movement patterns; thus, we propose using crowd-sourced amenity data and other open data sources as reasonable proxies for human mobility. Here we present a framework for predicting water consumption in areas with established service water connections and generalize it to underserved areas. Our work used features such as geography, population, and domestic consumption ratio and compared

SUBMITTER: Dailisan D 

PROVIDER: S-EPMC8932610 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature