@article {14328,
	title = {Disaggregated water sensing from a single, pressure-based sensor: An extended analysis of HydroSense using staged experiments},
	journal = {Pervasive and Mobile Computing},
	volume = {8},
	year = {2012},
	month = {2012/02//},
	pages = {82 - 102},
	abstract = {We present an extended analysis of our previous work on the HydroSense technology, which is a low-cost and easily installed single-point sensor of pressure for automatically disaggregating water usage activities in the home (Froehlich et~al., 2009~[53]). We expand upon this work by providing a survey of existing and emerging water disaggregation techniques, a more comprehensive description of the theory of operation behind our approach, and an expanded analysis section that includes hot versus cold water valve usage classification and a comparison between two classification approaches: the template-based matching scheme used in Froehlich et~al. (2009)~[53] and a new stochastic approach using a Hidden Markov Model. We show that both are successful in identifying valve- and fixture-level water events with greater than 90\% accuracies. We conclude with a discussion of the limitations in our experimental methodology and open problems going forward.},
	keywords = {Activity sensing, H1.2, H5.2, Infrastructure-mediated sensing, Sensors, Water usage},
	isbn = {1574-1192},
	doi = {10.1016/j.pmcj.2010.08.008},
	url = {http://www.sciencedirect.com/science/article/pii/S1574119210000842},
	author = {Larson,Eric and Jon Froehlich and Campbell,Tim and Haggerty,Conor and Atlas,Les and Fogarty,James and Patel,Shwetak N.}
}
@article {14330,
	title = {Fast track article: Disaggregated water sensing from a single, pressure-based sensor: An extended analysis of HydroSense using staged experiments},
	journal = {Pervasive Mob. Comput.},
	volume = {8},
	year = {2012},
	month = {2012/02//},
	pages = {82 - 102},
	abstract = {We present an extended analysis of our previous work on the HydroSense technology, which is a low-cost and easily installed single-point sensor of pressure for automatically disaggregating water usage activities in the home (Froehlich et al., 2009 [53]). We expand upon this work by providing a survey of existing and emerging water disaggregation techniques, a more comprehensive description of the theory of operation behind our approach, and an expanded analysis section that includes hot versus cold water valve usage classification and a comparison between two classification approaches: the template-based matching scheme used in Froehlich et al. (2009) [53] and a new stochastic approach using a Hidden Markov Model. We show that both are successful in identifying valve- and fixture-level water events with greater than 90\% accuracies. We conclude with a discussion of the limitations in our experimental methodology and open problems going forward.},
	keywords = {Activity sensing, H1.2, H5.2, Infrastructure-mediated sensing, Sensors, Water usage},
	isbn = {1574-1192},
	doi = {10.1016/j.pmcj.2010.08.008},
	url = {http://dx.doi.org/10.1016/j.pmcj.2010.08.008},
	author = {Larson,Eric and Jon Froehlich and Campbell,Tim and Haggerty,Conor and Atlas,Les and Fogarty,James and Patel,Shwetak N.}
}
