Smart Homes for Seniors: How the IoT Can Help Aging Parents Live at Home Longer
- by 7wData
According to Forbes, “It costs families more to care for a frail older adult than to raise a child for the first 17 years of her life.” And this is a growing concern. An AARP publication reported in late 2015 that the population of adults 85 and older in the U.S. will roughly triple between 2015 and 2060 – making it the fastest-growing age group over this time period.
So what happens when our senior loved ones still want to live independently at home, but we worry about them? What if we had a smart home system that could provide information on an aging loved one – and give some peace of mind?
When does Grandma get up in the morning and eat her meals? When does she leave and come back? Qorvo’s Senior Lifestyle System has been tested and used for the last 15 years in assisted living communities in Europe to help seniors live more independently. Within a few weeks, this system learns the routine day-to-day activities of the senior resident, provides intelligent status updates in a dashboard app, and sends alerts to designated caregivers if something unexpected happens.
Built around wireless sensor nodes located throughout the home, the system requires only five sensors, a gateway that supports ZigBee®, and links to the internet. Installed in less than an hour using simple QR codes, this inexpensive application doesn't require any programming, and caregivers or family members can manage it using a smartphone or tablet.
The five sensors (motion detection or open/close) are placed in predefined, carefully selected locations to make the system effective: the front door, bedroom, bathroom, refrigerator and living room. The sensors provide full-home coverage, even through concrete floors and walls, and are not susceptible to interference from other RF devices in the house.
The algorithm the system uses is self-learning. After a two-week “training period,” the system can generate alerts based on behavioral pattern recognition. It then continuously collects information via the sensors, “learns” the living patterns of the person in the house and will report on any irregular behavior.
An example: say Grandma gets up around 8:30 a.m.
[Social9_Share class=”s9-widget-wrapper”]
Upcoming Events
Evolving Your Data Architecture for Trustworthy Generative AI
18 April 2024
5 PM CET – 6 PM CET
Read MoreShift Difficult Problems Left with Graph Analysis on Streaming Data
29 April 2024
12 PM ET – 1 PM ET
Read More