A review of the potential of smart homes to support independent living

Between 2015 and 2050, the proportion of the world's population over 60 years of age is expected to nearly double, from 12% to 22%. Whilst hospitals offer care to people with health problems, support at home is generally limited to carers, a costly labour intensive method that impacts on the ability of many elderly patients to live independently. This pushes the demand for housing that caters for elderly people allowing them to remain in their homes but with some level of healthcare support. In the UK, the domestic sector currently accounts for around 30% of total energy consumption and contributes in the region of 27% of total carbon dioxide and greenhouse gas emissions. With an ageing population, offering healthy environments with a cushion against rising energy prices will be essential for people spending most of their time at home and often living on limited budgets. In this context, the drive to reduce energy consumption and associated greenhouse gas emissions from housing has acted as a catalyst in the increasing installation of meters and sensors for monitoring energy use and indoor environmental conditions in buildings. These monitoring technologies can track and record a range of parameters such as temperature, air quality, occupant behaviour etc. Many of these could be optimised to help create environments that assist people such as the elderly to live at home. This paper aims to review relevant studies and technologies in the areas of smart, energy-efficient and lifetime homes, identifying some of the health needs of elderly people who could live at home if provided with adequate support, the range and type of technologies that could be employed to this objective, and suitable metrics to be used to measure the effectiveness of these technologies. The paper concludes that there is a limited evidence base on the health effects of energy-efficient homes, highlighting the need for more research and post occupancy evaluation using indoor environmental quality monitoring technology and wearable devices to analyse not only the energy performance of ‘green’ housing but also the possible effects of indoor environmental conditions on the subjective and objective wellbeing of occupants

An Instrumented Apartment to Monitor Human Behavior: A Pilot Case Study in the NeuroTec Loft

For patients suffering from neurodegenerative disorders, the behavior and activities of daily living are an indicator of a change in health status, and home-monitoring over a prolonged period of time by unobtrusive sensors is a promising technology to foster independent living and maintain quality of life. The aim of this pilot case study was the development of a multi-sensor system in an apartment to unobtrusively monitor patients at home during the day and night. The developed system is based on unobtrusive sensors using basic technologies and gold-standard medical devices measuring physiological (e.g., mobile electrocardiogram), movement (e.g., motion tracking system), and environmental parameters (e.g., temperature). The system was evaluated during one session by a healthy 32-year-old male, and results showed that the sensor system measured accurately during the participant’s stay. Furthermore, the participant did not report any negative experiences. Overall, the multi-sensor system has great potential to bridge the gap between laboratories and older adults’ homes and thus for a deep and novel understanding of human behavioral and neurological disorders. Finally, this new understanding could be utilized to develop new algorithms and sensor systems to address problems and increase the quality of life of our aging society and patients with neurological disorders

NILM techniques for intelligent home energy management and ambient assisted living: a review

The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.Agência financiadora: Programa Operacional Portugal 2020 and Programa Operacional Regional do Algarve 01/SAICT/2018/39578 Fundação para a Ciência e Tecnologia through IDMEC, under LAETA: SFRH/BSAB/142998/2018 SFRH/BSAB/142997/2018 UID/EMS/50022/2019 Junta de Comunidades de Castilla-La-Mancha, Spain: SBPLY/17/180501/000392 Spanish Ministry of Economy, Industry and Competitiveness (SOC-PLC project): TEC2015-64835-C3-2-R MINECO/FEDERinfo:eu-repo/semantics/publishedVersio

Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home

This paper explores using RSS measurements on many links in a wireless network to estimate the breathing rate of a person, and the location where the breathing is occurring, in a home, while the person is sitting, laying down, standing, or sleeping. The main challenge in breathing rate estimation is that "motion interference", i.e., movements other than a person's breathing, generally cause larger changes in RSS than inhalation and exhalation. We develop a method to estimate breathing rate despite motion interference, and demonstrate its performance during multiple short (3-7 minute) tests and during a longer 66 minute test. Further, for the same experiments, we show the location of the breathing person can be estimated, to within about 2 m average error in a 56 square meter apartment. Being able to locate a breathing person who is not otherwise moving, without calibration, is important for applications in search and rescue, health care, and security