Tracking Human Behavioural Consistency by Analysing Periodicity of Household Water Consumption

Abstract

People are living longer than ever due to advances in healthcare, and this has prompted many healthcare providers to look towards remote patient care as a means to meet the needs of the future. It is now a priority to enable people to reside in their own homes rather than in overburdened facilities whenever possible. The increasing maturity of IoT technologies and the falling costs of connected sensors has made the deployment of remote healthcare at scale an increasingly attractive prospect. In this work we demonstrate that we can measure the consistency and regularity of the behaviour of a household using sensor readings generated from interaction with the home environment. We show that we can track changes in this behaviour regularity longitudinally and detect changes that may be related to significant life events or trends that may be medically significant. We achieve this using periodicity analysis on water usage readings sampled from the main household water meter every 15 minutes for over 8 months. We utilise an IoT Application Enablement Platform in conjunction with low cost LoRaenabled sensors and a Low Power Wide Area Network in order to validate a data collection methodology that could be deployed at large scale in future. We envision the statistical methods described here being applied to data streams from the homes of elderly and at-risk groups, both as a means of early illness detection and for monitoring the well-being of those with known illnesses.

Detection of Anomalous Patterns in Water Consumption: An Overview of Approaches

“…Determining anomalous behaviors in water consumption is also a major task in water analytics. For example, in [7], changes in household water consumption are identified from water usage readings with the aim of detecting anomalies that may lead to the discovery of manipulated meters. Similarly, [8,9] propose two different approaches for determining anomalous behaviors in water consumption: punctual anomalous consumption and anomalous changes in behavior of water consumption, respectively.…”

Dynamic Study of Intelligent Traffic Behaviour Based on Multiple Traffic Modes

“…Considering the influence of interest change factors on human behaviour, Han et al [12] proposed an adaptive interest-driven model. Quinn et al [13] analyzed the periodicity of water consumption readings collected from water meters of prominent households every 15 minutes for more than eight months and found that periodicity also existed in people's water use behaviour.…”