Smart Meter Load Profiling for e-Health Monitoring System

Kelati, Amleset; Plosila, Juha; Tenhunen, Hannu

doi:10.1109/sege.2019.8859936

Cited by 7 publications

(5 citation statements)

References 10 publications

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“…On the other hand, irregularities or fluctuations in energy usage may signal changes in health status, behavioral patterns, or environmental factors. By detecting deviations from the established routines, caregivers can proactively intervene to address emerging issues or provide necessary support [ 34 , 35 , 36 ]. The interpretation of activity levels and regularity assessments enables the detection of subtle changes that may signify alterations in health or behavior among elderly individuals.…”

Section: Discussionmentioning

confidence: 99%

A Lifestyle Monitoring System for Older Adults Living Independently Using Low-Resolution Smart Meter Data

Mathunjwa,

Chen,

Tsai

et al. 2024

Sensors

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Background: Monitoring the lifestyles of older adults helps promote independent living and ensure their well-being. The common technologies for home monitoring include wearables, ambient sensors, and smart household meters. While wearables can be intrusive, ambient sensors require extra installation, and smart meters are becoming integral to smart city infrastructure. Research Gap: The previous studies primarily utilized high-resolution smart meter data by applying Non-Intrusive Appliance Load Monitoring (NIALM) techniques, leading to significant privacy concerns. Meanwhile, some Japanese power companies have successfully employed low-resolution data to monitor lifestyle patterns discreetly. Scope and Methodology: This study develops a lifestyle monitoring system for older adults using low-resolution smart meter data, mapping electricity consumption to appliance usage. The power consumption data are collected at 15-min intervals, and the background power threshold distinguishes between the active and inactive periods (0/1). The system quantifies activity through an active score and assesses daily routines by comparing these scores against the long-term norms. Key Outcomes/Contributions: The findings reveal that low-resolution data can effectively monitor lifestyle patterns without compromising privacy. The active scores and regularity assessments calculated using correlation coefficients offer a comprehensive view of residents’ daily activities and any deviations from the established patterns. This study contributes to the literature by validating the efficacy of low-resolution data in lifestyle monitoring systems and underscores the potential of smart meters in enhancing elderly people’s care.

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Section: Discussionmentioning

confidence: 99%

A Lifestyle Monitoring System for Older Adults Living Independently Using Low-Resolution Smart Meter Data

Mathunjwa,

Chen,

Tsai

et al. 2024

Sensors

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“…It is foreseen that by investigating advanced machine learning and load disaggregation techniques of this highly accurate sensing network, detailed habits of an individual's interactions with electrical devices can be assessed; smart meter electricity readings can be used to support social care that meets a person's individual needs, maximises independence and promotes a sense of security for those living alone [28,29].…”

Section: Case Studymentioning

confidence: 99%

“…Reference [28] reported that the measured energy dataset is taken from 12 households and collected by the smart meter with an interval of an hour for one month. The dataset is grouped according to the feature pattern.…”

Section: Case Studymentioning

confidence: 99%

Healthcare With Wireless Communication and Smart Meters

Lai

2023

IEEE Consumer Electron. Mag.

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Smart health is an essential domain within smart cities. Internet-assisted communication with medical practitioners is now widely used. This is important for elderly or disabled patients, who may not be able to travel but have inexpensive and simple internet access they can take advantage of with video-call consultations. However, smart health based on the Internet of Things (IoT) and smart meters is not without its challenges. This paper reviews the benefits and challenges of innovations in healthcare, with emphasis on IoT and smart meters. A top-level smart health with smart meter system design flowchart is given, and the component and module diagram is proposed.

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“…This work is an extension of our previous paper [1], and this article is organized into several sections for a clear and organized presentation of information. The second section, labeled as 2, will delve into a discussion of related work, providing context for the research presented in the paper.…”

Section: Introductionmentioning

confidence: 99%

Integrating Smart Meter Load Profiling for Enhanced Data Insights and Patient Care

Kelati,

Plosila,

Tenhunen

2024

Biomedical Engineering

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The utilization of smart meter data has opened new frontiers in the healthcare sector by enabling the detection of health status and daily life activities. A new methodology has been proposed to differentiate between normal and abnormal energy consumption, which can be leveraged to determine the health status of consumers by analyzing load profiling. By visualizing human activities based on electricity usage, there is a growing interest in using smart meter data for detecting health status and Activities of Daily Living (ADLs). The chapter discussed, this innovative approach utilizes the K-Means algorithm to classify the data and identify patterns in the energy usage of individuals. By analyzing this data, potential health issues can be indicated, thereby assisting the healthcare sector in addressing the needs of the elderly population more effectively. This technology has the potential to revolutionize healthcare by providing a non-invasive and cost-effective way to monitor the health of individuals and enable early intervention in case of any health issues.

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Smart Meter Load Profiling for e-Health Monitoring System

Cited by 7 publications

References 10 publications

A Lifestyle Monitoring System for Older Adults Living Independently Using Low-Resolution Smart Meter Data

A Lifestyle Monitoring System for Older Adults Living Independently Using Low-Resolution Smart Meter Data

Healthcare With Wireless Communication and Smart Meters

Integrating Smart Meter Load Profiling for Enhanced Data Insights and Patient Care

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