University of Illinois Urbana-Champaign
Towards connecting occupant behavior to residential water use in a permanent supportive housing context
Abstract
dc:descriptionThe quantification of residential water end uses is an important component of improving the sustainability of urban water infrastructure. Disaggregation and classification methods based on statistical learning are used in research and practice to extract meaningful insights from smart water meter data. These insights can also reflect individual behaviors within the built environment, enabling end-user activity detection from water consumption patterns. Exogenous environmental factors can also affect the composition of end-uses in a residential setting. In this study, an initial framework was created for classifying residential water end-uses in a permanent supportive housing context and assisting with discerning between perceived typical and atypical human behavior from water use patterns. Classification schemes, based on fine-resolution temporal flow data, incorporated baseline activity to inform what typical water use was for individuals while also considering general trends in specific end-uses such as showers, toilet flushes, and leaks. This study found that while atypical activity based on end-use duration and frequency might fall outside the normally-distributed expected value for a period of interest, it need not be the case for all atypical activity. Defining atypical activity based on prescriptive guidelines might not align with what is normative behavior for an occupant transitioning into housing. Additionally exogenous variables can impact occupant behavior regarding water fixture end-use and this impact should be accounted for. Findings from this study can specifically inform supportive services provided by stakeholders responsible for the well-being of individuals in their care via non-intrusive, privacy-respecting insights on occupant behavior. These signals established a broader water behavior pattern used to screen for irregular activity that left unattended (or unnoticed) could contribute to adverse outcomes.
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Civil Engineering
- Grantor
- University of Illinois Urbana-Champaign
- Year dc:date
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Khan, Hassaan Ahmed
- Contributors dc:contributor
-
- Stillwell, Ashlynn S
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- Copyright 2025 Hassaan Khan
- Language dc:language
- en, eng
Identifiers
dc:identifier.*- Handle dc:identifier
- https://hdl.handle.net/2142/129610