Smart Health with Smart Meters

Written by Qi Hong Lai

According to Navigant Research reported in 2018, China continued to lead the global smart meter market with 496 million meters installed [1]. There were high-volume deployments across Japan and South Korea. The emergence of large meter tenders in India also helps to drive volumes. In Eastern Europe, Latin America, the Middle East & Africa, different small and mid-scale advanced metering infrastructure (AMI) deployments continue to propagate. To fully utilize resources, smart meter data could be considered as a means to promote smart health development. In this article, a short overview will be given on some of the opportunities and challenges that will be faced.


Smart meters give off radiofrequency (RF) non-ionizing radiation which, in general, has enough energy to move around atoms in a molecule or cause them to vibrate, but will not cause direct damage to DNA [2]. However, as RF radiation is a possible carcinogen, there is a possibility that smart meters could increase cancer risk. The World Health Organization has promised to conduct a formal assessment of the risks from RF exposure but from the author’s knowledge, this report was not yet available at the time of writing. In some places where smart meters are being installed, if there is a real concern, people have the choice to opt into or out of having them.

In the UK, Public Health England (PHE) has carried out an extensive program of research to assess exposure to smart meters, as the technology is rolled out in Great Britain. The results confirm PHE’s existing advice that exposure to radio waves from smart meters is well below the guidelines set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The results were published in Bioelectromagnetics [3].

The study also concluded that exposure to the radio waves produced by smart meters is likely to be much lower than those from other everyday devices, such as mobile phones. For a quantitative comparison, the readers could refer to Reference [4]. PHE considers exposure to radio waves to not provide a basis to decline to have a smart meter. The evidence to date suggests exposure to the radio waves produced by smart meters do not pose a health risk. However, PHE is committed to keeping the scientific evidence under close review and to publishing further reviews and updating statements as of and when necessary. The number of people who are living alone with self-limited conditions, such as Alzheimer's, Parkinson's disease and depression, is increasing. But no technology exists to allow automated monitoring of such individuals. Also, the number of people living alone has doubled over the last three decades, amounting to one in three people in the UK and US [5].

Existing monitoring services such as motion sensors, cameras, fall detectors and communication hubs, and wearable body networks are intrusive, expensive and are met with patient resistance. A smart meter records consumer data at regular intervals, which can be used to identify and detect sudden abnormal changes in behaviour based on the analysis of regular activities a consumer would undertake during 24 hours. The challenge, however, is to develop a system that can distinguish reliably between subtle changes in energy usage. Analysis of energy usage with data classification techniques can identify any anomalies in energy consumption. Reference [6] reported research using existing smart meter infrastructure technologies to study the possibility to have a large impact with significant benefits for society and academia based on data analysis of smart meter electricity readings to support social care that meets a person's individual needs, maximises independence and promotes a sense of security for those living alone; provides peace of mind and remote patient care.

A report from 2020 commissioned by Smart Energy GB, highlighted the ways energy usage data collected by smart meters could help with caring for vulnerable and elderly people and make it easier for them to live in their own homes for longer by remotely monitoring vulnerable members of society to improve social services [7, 8].

With the agreement of the householder, data from smart meters could be used as a non-intrusive way to help keep people who have a long-term condition or are vulnerable in other ways, in their own home for longer. Irregularities in patterns of energy use behaviour could alert relatives or healthcare workers that the individual may need additional support. For example, if there were no signs of electrical usage or heating in the house of an elderly person, a text alert could be sent to a carer or trusted relative for action.

Also, around one in seven UK householders are living in fuel poverty, which is defined as being unable to afford to heat their homes to the temperature needed to keep warm and healthy. Living in cold conditions can increase many common physical and mental health problems. With smart meter energy usage data and weather data, it could be possible to remotely detect these unhealthy living conditions to prevent related health problems. Smart meter data could provide valuable insight into people’s health and potentially be a large-scale form of telehealth to support people with long-term conditions such as reducing hospital stays and allowing early discharge; reducing their dependency on primary health and services from family doctors. It can also improve access to care for people with mobility issues or people who are unable to get time off work.

As the UK’s target is to have 85% of consumers equipped with a smart meter by the end of 2024 if it is used to develop health and social care monitoring technology, this could soon become a practical and popular telehealthcare solution. No other telecare technology will have such high adaptability to maximize competitiveness and quality. The report on the smart future of healthcare also explores barriers to scaling up the use of smart meters in health and care monitoring systems [9].

Smart meter data can be used to check the health status, health changes and general wellbeing of a house occupant. The approach typically involves a remote non-intrusive load monitoring of household electricity consumption, through which the use of various appliances, such as a toaster, microwave, electric oven, kettle and washing machine can be determined. Machine learning techniques such as neural networks could be used to build a map of routine behaviours and activities over time, thereafter enabling the detection of abnormal behaviour or unexpected performance. For instance, a person’s deviation from normal routine may include the use of a kettle or other appliances during the night, possibly indicating sleep disturbances related to neurological deterioration, pain or mental health issues.

The increase in energy consumption during late evenings could suggest agitation and confusion, a symptom of dementia. Repeatedly forgetting to turn off the cooker may indicate memory problems associated with mild cognitive impairment. Health deterioration is quickly recognised through the deviation from typical energy use patterns and rapid response can be initiated as needed. Smart meter data could be used for planning social capital, improving social services and allocating healthcare capacity. The energy data can be compared with weather data to detect cold homes and unhealthy situations. This helps governments provide citizens with grants for better health and living conditions.

Opportunities always come with challenges. Reference [9] identifies several barriers to adopting smart meter data at a large-scale level. There is the unavailability of funding and a lack of collaboration between computer science, governments, engineering, energy and healthcare, therefore studies remain only theoretical, with little evidence of real-world validity and demonstration projects. There are also technological and connectivity limitations. The penetration of smart meters remains slow in the majority of countries. For example, in the UK, despite rapid deployment, smart meters remain the lesser-used metering technology by households due to connectivity issues. Other communication challenges include the installation of cellular and Wi-Fi connectivity, especially in rural areas where these types of networks are either intermittent or non-existent but essential for smart meter services.

In balance, it is believed that opportunities are more than challenges, and the use of smart meters in telecare should become a reality. Country-specific regulatory bodies must ensure robust data security, privacy and put in place consent regulations around the sharing of energy data with third parties delivering care services and data analytics. More public-funded research should investigate how smart meter data may together provide deeper insights into the activities of daily living and health risks associated with citizens. For example, the UK National Health Service (NHS) has conducted trials in the use of smart meter data for mental health patients [10]. It is expected that this work will directly impact local NHS trusts, housing associations, councils, local authorities and policymakers. More financial support is needed to carry out wider clinical trials to formulate policies and business models.

 

Conclusions

Since the adoption of smart meters have increased rapidly and the number of people in need of care is also increasing, investing in smart meter trials in this field would help us not only improve social services but also better allocate capital. The important topic of integrating healthcare applications into smart meters has been discussed in the context of smart cities. In particular, a brief but concise comparison between implementation options used in various countries for smart city deployment in the smart health domain has been given. From this short overview, it can be concluded that smart meter infrastructure can likely provide a sustainable, manageable, accurate, reliable and technical solution to smart health development.

 

 

 

References

  1. China leads global smart meter deployments at end-Q1, study finds, July 2018 https://enterpriseiotinsights.com/20180710/internet-of-things/china-leads-globl-smart-meter-deployments-end-q1-study-finds-tag23 (Accessed on 21 June 2019)
  2. Can smart meters cause cancer? American Cancer Society. https://www.cancer.org/cancer/cancer-causes/radiation-exposure/smart-meters.html (Accessed on 13 December 2020)
  3. Smart meters: radio waves and health, 23 April 2020 https://www.gov.uk/government/publications/smart-meters-radio-waves-and-health/smart-meters-radio-waves-and-health (Accessed on 3 August 2020)
  4. B. Fong, A.C.M. Fong and C.K. Li, Telemedicine Technologies: Information Technologies for Medicine and Digital Health, 2nd Edition, John Wiley & Sons, UK, 2020.
  5. Carl Chalmers, William Hurst, Michael Mackay, and Paul Fergus, “Smart Health Monitoring Using the Advance Metering Infrastructure,” 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 26-28 Oct. 2015.
  6. Data Analytics for Health-Care Profiling using Smart Meters, EPSRC Reference: EP/R020922/1  https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/R020922/1 (Accessed on 21 October 2020)
  7. How smart meters could transform health and social care. https://www.smartenergygb.org/smart-meter-benefits/benefits-for-you/how-smart-meters-could-transform-health-and-social-care  (Accessed on 5 December 2021)
  8. Nicholas Nhede, Using smart meters in health and care monitoring systems, 2 March 2021 https://www.smart-energy.com/magazine-article/using-smart-meters-in-health-and-care-monitoring-systems/ (Accessed on 22 April 2021)
  9. Jon Paxman, Matt James, Enrico Costanza and Julia Manning, Examining possibilities for smart meter data in health and care support https://2020health.org/publication/smart-future-of-healthcare/  (Accessed on 5 December 2021)
  10. https://www.sms-plc.com/insights/blogs-news/nhs-looks-to-smart-meters-for-help-with-dementia-and-mental-health-patients/  (Accessed on 21 December 2021)

 

 

This article was edited by Aris Gkoulalas-Divanis

To view all articles in this issue, please go to December 2021 eNewsletter. For a downloadable copy, please visit the IEEE Smart Cities Resource Center.

Qi Hong LAI photo
Qi Hong Lai gained her Bachelor of Science in Biomedical Science with First Class Honours from King’s College London, UK in 2019. At present, she is working towards her Doctor of Philosophy in Molecular Cell Biology in Health and Disease at the Sir William Dunn School of Pathology, University of Oxford, UK. Her current research interests are in transcription, bioinformatics, biotechnology and smart health. She is an IEEE Student Member with Engineering in Medicine and Biology Society, Technology and Engineering Management Society, and Systems, Man, and Cybernetics Society.