Abstract: The utility usage of a particular individual occupying a residence may give insight into the individual's current cognitive health and/or to enable provision of various services within the facility for the individual, particularly when monitoring patterns in utility usage over time. To enable accurate and non-invasive utility monitoring, a single-point utility sensor may be secured relative to a utility supply line, and generated signals may be utilized to monitor utility usage and to distinguish between utility fixtures. A centralized computing entity may identify frequency characteristics within the generated data, and may automatically generate one or more machine-learning algorithms to distinguish between utility usage events, without requiring substantial user input.

Abstract: The utility usage of a particular individual occupying a residence may give insight into the individual's current cognitive health and/or to enable provision of various services within the facility for the individual, particularly when monitoring patterns in utility usage over time. To enable accurate and non-invasive utility monitoring, a single-point utility sensor may be secured relative to a utility supply line, and generated signals may be utilized to monitor utility usage and to distinguish between utility fixtures. A centralized computing entity may identify frequency characteristics within the generated data, and may automatically generate one or more machine-learning algorithms to distinguish between utility usage events, without requiring substantial user input.