Tracking Human Behavioural Consistency by Analysing Periodicity of Household Water Consumption

@inproceedings{Quinn2019TrackingHB,
  title={Tracking Human Behavioural Consistency by Analysing Periodicity of Household Water Consumption},
  author={Se{\'a}n Quinn and Noel Murphy and Alan F. Smeaton},
  booktitle={SSIP 2019},
  year={2019}
}
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. [] Key Method 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 LoRa-enabled sensors and a Low Power Wide Area Network in order to validate a…
2 Citations

Figures and Tables from this paper

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

The use of algorithms of different nature that approach the problem of anomaly detection from different perspectives that go from searching deviations from typical behavior to identification of anomalous pattern changes in prolonged periods of time are proposed.

Dynamic Study of Intelligent Traffic Behaviour Based on Multiple Traffic Modes

The research in this paper can reveal the relationship between bimodal power-law distribution and spatial characteristics in complex systems and help solve social traffic problems effectively in social reality and provide practical planning guidance for the behavioural integration of multiple traffic in smart cities.

References

SHOWING 1-10 OF 19 REFERENCES

Smart homes for the elderly dementia sufferers: identification and prediction of abnormal behaviour

Recurrent neural networks are used to predict the future values of the activities for each sensor in the home by means of equipping their home with a simple sensor network to monitor their behaviour.

Using periodicity intensity to detect long term behaviour change

24 hour accelerometer data is used to illustrate the new way to analyse and visualize quantified-self or lifelog data captured from any lifelogging device over an extended period of time, showing how changes in human behavior can be identified.

Behavioral Periodicity Detection from 24 h Wrist Accelerometry and Associations with Cardiometabolic Risk and Health-Related Quality of Life

The framework demonstrates a new method for characterizing behavior patterns longitudinally which captures relationships between 24 h accelerometry data and health outcomes, and the most notable periodicity was at 24’h, indicating a circadian rest-activity cycle.

Care Coordination/Home Telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions.

Routine analysis of data obtained for quality and performance purposes from a cohort of 17,025 CCHT patients shows the benefits of a 25% reduction in numbers of bed days of care, 19% reduction of numbers of hospital admissions, and mean satisfaction score rating of 86% after enrolment into the program.

Periodicity intensity for indicating behaviour shifts from lifelog data

  • Feiyan HuA. Smeaton
  • Computer Science
    2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  • 2016
This paper proposes several metrics to estimate the intensity of periodicity, longitudinally and explores periodicity intensity calculated from two real lifelog datasets using “big” data consists of low-level accelerometer data and another one is high level athletic performance data.

Structured telephone support or non-invasive telemonitoring for patients with heart failure

A recent Cochrane review demonstrated that both non-invasive telemonitoring and structured telephone support offer statistically and clinically meaningful benefits to people with heart failure.

Sleep disruption in Parkinson's disease. Assessment by continuous activity monitoring.

It is hypothesized that in mildly to moderately affected patients with PD, levodopa or dopamine agonists cause sleep disruption by their effects on sleep regulation, and in more severely affected patients, the beneficial effects of these drugs on nocturnal disabilities that causeSleep disruption in PD prevail.

Stability, precision, and near-24-hour period of the human circadian pacemaker.

Estimation of the periods of the endogenous circadian rhythms of melatonin, core body temperature, and cortisol in healthy young and older individuals living in carefully controlled lighting conditions has revealed that the intrinsic period of the human circadian pacemaker averages 24.18 hours in both age groups, with a tight distribution consistent with other species.

Long-Range IoT Technologies: The Dawn of LoRa™

Some of the most interesting LPWAN solutions are discussed, focusing in particular on LoRa™, one of the last born and most promising technologies for the wide-area IoT.