Using AI & NILM technology to help older adults live longer in their own homes and bring higher efficiency to group caring

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Title
Using AI & NILM technology to help older adults live longer in their own homes and bring higher efficiency to group caring

CoPED ID
02724011-9cb7-417f-937c-0c8f516a0123

Status
Active

Funder

Value
£48,479

Start Date
Nov. 1, 2022

End Date
April 29, 2023

Description

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At Informetis Europe, our goal is to support the more vulnerable and ageing members of our society to enjoy the future more independently within the comfort of their own home. We believe that older adults should not only be able to live independently in an environment that is both safe and familiar to them for as long as they wish, but also that any preventative domiciliary care provided should be as non-intrusive as possible.


Our innovation is to offer a 24/7 assisted living solution called InfoCarePro. InfoCarePro is based on Non-Intrusive Load Monitoring (NILM) technology - a process that monitors voltage and current usage within a property and then deduces what appliances are being used using Artificial Intelligence (AI).


Although some product offerings already exist, InfoCarePro differs by putting emphasis on discrete monitoring as well as no interaction required from the user. Whilst the majority of the current solutions require some combination of cameras, motion sensors, smart plugs, and interactive alarms, we utilise a single sensor which is installed into the customer's fusebox. This sensor will be "invisible" to the resident, but will provide all the necessary data for our Artificial Intelligence (AI) algorithm to determine when deviations from the norm have occurred and when alerts need to be sent out to family members and healthcare professionals. There is no need for the individual being cared for to interact in any way with our sensor (eg. replacement of batteries or remembering to wear a pendant etc.)

Our comprehensive AI algorithms will then be able to highlight deviations in normal routine behaviour, allowing alerts to be sent to family members or health care workers indicating either the overuse or under use of appliances. This can identify deviations ranging from an oven or hob being left on longer than normal to a kettle not being used first thing in the morning. This type of daily routine analysis can then be used to analyse long-term deviations which could be indicative of potential serious health conditions. This would allow for preventative actions to be taken, thereby reducing the levels of reactive care required and in turn alleviating the volume of stress on our already overburdened NHS.

Marc Reynolds PM_PER

Subjects by relevance
  1. Older people
  2. Artificial intelligence
  3. Public health service
  4. Interaction

Extracted key phrases
  1. Use
  2. Comprehensive AI algorithm
  3. Old adult
  4. NILM technology
  5. Preventative domiciliary care
  6. Health care worker
  7. Long
  8. Intrusive load monitoring
  9. Artificial Intelligence
  10. Term deviation
  11. Normal routine behaviour
  12. Single sensor
  13. Family member
  14. Motion sensor
  15. Reactive care

Related Pages

UKRI project entry

UK Project Locations