The emergence of more powerful computers, near-ubiquitous mobile broadband and cloud computing has created exponential change across every industry and society. Increasingly, we are seeing the convergence of physical and cyber systems, what society has termed the Fourth Industrial Revolution, Industry 4.0 and the Internet of Things (IoT). The IoT, combined with advancements in machine learning and artificial intelligence will fundamentally change society in the next five years with the commercialisation of autonomous vehicles, sensor-based health monitoring and ‘smart-homes’.

The aged care services industry is neither exempt nor oblivious to this change. In February 2014, The Aged Care Industry Information Technology Council and Accenture jointly released a vision for information technology across aged care services. This vision identified five ‘ICT Pillars’ that will enable the industry to build capacity, and adjust to ‘the new environment’. In 2016, Flinders University was commissioned to build on this vision, and outline an IT Roadmap that would support the execution of the Aged Care Sector Roadmap. This work is currently underway, with extensive consultation occurring at the Information in Aged Care Conference in November 2016.

In this article, I outline how advancements in the IoT and artificial intelligence have the potential to support carers of older Australians, as well as the long-term sustainability of informal care. This was the topic of a recent presentation at the Melbourne Accelerator Program’s Social Impact Showcase, where Umps Health was were awarded the Gourlay-Trinity Impact Prize for ‘demonstrating exceptional knowledge in a social issue’.


To demonstrate the capability of IoT and artificial intelligence, it is helpful to think of the workflow of a carer in the following stages:

  1. Gathering data:In order to provide care, a carer must first obtain data about the wellbeing of an individual. This could be through phone calls or a visit to the person. Other examples are the Red Cross TeleCross service, which call more than 9000 Australians every day or the button people press once a day when they use a personal alarm service.
  2. Analysing and interpreting the data: This data must then be analysed in the context of past behaviour and health history. Does a missed phone call indicate someone has fallen in their home, or are they out for a coffee with friends? If a person says they are OK, are they actually OK or are they simply trying not to worry people? We might not think about this explicitly, but we are subconsciously making an assessment when there is an abnormality in the data.
  3. Determining a recommended course of action: If a carer interprets the data as unusual, they will evaluate options and decide on a course of action. This may be to make a visit to their relative, schedule an appointment with a doctor or to call emergency services.
  4. Implementing the course of action: After a carer has determined the appropriate course of action, the ‘caring’ begins. This is the intrinsically human component of caring, and could be as simple as physical or emotional comfort, or driving someone to the doctor. In the event they need to consult a third party, the entire workflow will commence once again.


It is estimated that the average household in Australia has more than 11 connected devices, and this is projected to grow to more than 29 devices before the end of the decade. Some examples of connected devices include refrigerators, TVs, cameras, lighting, fitness trackers and bathroom scales.

The proliferation of these ‘IoT enabled devices’ has generated huge amounts of data, which service providers can leverage to develop innovative consumer services. For example, knowing that an individual has used their kettle in the morning is evidence they have got out of bed, while understanding how someone uses their microwave provides powerful insights into their eating habits. In this way, the IoT has enriched our ability to collect data. 


Artificial intelligence is a domain in computer science that seeks to simulate human intelligence. A key principle of intelligence is the ability to learn, and while we haven’t yet created the sorts of artificial intelligence popularised in fiction (like Rosie from the Jetsons), you may be surprised at the amount of artificial intelligence you already interact with everyday. Netflix uses advanced algorithms to assess your interest in different movies and make tailored predictions on content you will enjoy. Pandora uses artificial intelligence to analyse complex characteristics in music and build custom playlists for us, and Siri is constantly learning how to more effectively respond to human language questions.

Even those 11 devices currently in Australian homes could generate hundreds of data points per day, making it extremely difficult for human intelligence (carers or aged care service providers) to generate insights. This is in contrast to artificial intelligence, which can analyse small abnormalities in the context of past behaviour of the individual, while crosschecking against anonymised data from hundreds of thousands of other people.

Imagine your father boils water at 2:43AM and again at 3:17AM. This is not entirely unusual for your dad, who often has a cup of tea after working late on his computer. However, a machine learning program assesses this in conjunction with the large number of lights that have been left on in the house, the fact that the computer hasn’t been used all evening and knowledge that your dad made toast half an hour earlier. Further analysis against population data suggests that this combination of anomalies could be associated with a loss of sense of time, an early symptom of dementia. It isn’t difficult to imagine a future where a program would then review your calendar against available appointments with your father’s GP, and make a tentative booking on your behalf.


As the capabilities of artificial intelligence grow, there is a social imperative to the adoption of artificial intelligence-based services. Firstly, artificial intelligence can help older people to age in place, making greater sense of large amounts of data to predict and potentially prevent an incident like a fall. Secondly, it can provide peace of mind to the 2.8 million Australians providing unpaid care each year, allowing them to participate in paid employment and reducing the physical and emotional stress associated with being an informal caregiver.


I am a believer in the power of artificial intelligence and the IoT because I use it to provide better care to my family. After designing a solution like the above for my grandpa, I founded Umps Health. Umps Health uses uses connected devices to collect data about how people interact with their appliances, like their kettle, TV and microwave. Our machine-learning platform generates tailored insights based on past patterns of behaviour, and raises an alert to carers when behaviour is out of the norm. With this technology, we can better inform carers when an incident (like a fall) may have occurred, or when someone’s behaviour demonstrates they are at heightened risk of an incident.

By reducing the time and effort required to collect data, interpret data and determine a recommended course of action, we hope to improve the lives of both those receiving care and those delivering it.

About the Author
Adam Jahnke is the founder and CEO of Umps Health, a company that uses machine learning to enable better living outcomes for older people. He has previously worked on smart city and smart home projects throughout Australia and South-East Asia. Adam is also studying a Master of Public Health at the University of Melbourne, with a research focus on international and intergenerational response to challenges associated with ageing.

For more information, contact Adam at

The post How will artificial intelligence support care in the home? appeared first on Umps Health.