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April 25, 2025 · Featured in Senior Times

The AI Revolution in Safe Independent Living, and an Honest Look at the Numbers

In April 2025, Senior Times profiled SmartGuardian's stick-figure AI. We have reproduced that feature in full below, then added the Irish context and the technical detail the original article did not have room for.

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Why we are republishing this

On 25 April 2025, Senior Times – one of Ireland's longest-running publications for older adults – ran a feature on the latest version of SmartGuardian, the in-home safety system from our sister company, Smart Space Technologies. You can read the original on the Senior Times website.

We are proud of the coverage, so we have reproduced the feature here in full and clearly attributed. A press feature is written to introduce a product, though, not to weigh up the evidence behind it. So below the article we have done something a little unusual for a company website: we have fact-checked the headline statistic against Irish data, explained how the technology genuinely works with reference to the published research, and set out plainly what the system can and cannot do. The marketing language in the feature (words like "unparalleled" and "complete anonymity") is the publisher's and the company's wording from 2025; treat it as quoted press copy. The context, citations and caveats underneath are ours.

The Senior Times feature (as published, 25 April 2025)

Reproduced with attribution. The section below is the feature as it appeared in Senior Times on 25 April 2025, headlined "Smart Space – Privacy Protected with Innovative Stick Model Technology." It is presented as a historical record of the press coverage. Quotations are attributed to Nigel Cobbe, Managing Director of Smart Space Technologies. For our own assessment of the claims, see the sections that follow.

Smart Space – Privacy Protected with Innovative Stick Model Technology

Smart Space Technologies, described in the feature as Ireland's leading specialist in advanced Artificial Intelligence (AI) for independent living, introduced the latest evolution of its SmartGuardian system. This version features an enhanced AI engine that uses a unique stick-figure representation for in-home monitoring, which the company said provides "unparalleled safe independence without compromising user privacy." This approach, coupled with the intuitive "Raise to Call" function, was presented as a new way for older adults to live securely and autonomously in their own homes across Ireland.

Recognising the challenge of falls affecting Ireland's senior population – the feature cited the widely-quoted figure of one in three individuals over 65 experiencing a fall each year – SmartGuardian's AI was described as using "discreet stick model technology" to offer a safety net while maintaining user anonymity.

At the core of the advancement is AI that transforms movement data into non-identifiable stick figures for continuous in-home monitoring. The company said this ensures a privacy-first design while the AI analyses movement and context. When a fall occurs, or when the user activates the "Raise to Call" function by raising an arm, the AI alerts designated family contacts. Each alert includes a stick-figure animation reconstructed from sensor data, never video and never a photograph, intended to give clear confirmation of an emergency without revealing personal details. Integrated two-way communication then allows families to offer immediate support. The "Raise to Call" function, powered by the AI's reading of gesture within the stick-model framework, lets users request help discreetly.

Nigel Cobbe, Managing Director of Smart Space Technologies, said: "The latest SmartGuardian version, with its advanced AI and stick model technology, delivers unparalleled safe independence by design. We've engineered a system that prioritises user privacy above all else, ensuring complete anonymity while providing families with reliable fall detection and an easy way for users to call for assistance. This is truly the next level of safe living at home in Ireland."

Beyond immediate assistance, the feature said SmartGuardian's AI learns daily routines within the stick-model framework to identify subtle anomalies that could indicate increased fall risk, offering a proactive layer of safety, all while maintaining "uncompromising privacy." Smart Space said it was committed to making the technology accessible to families throughout Ireland.

SmartGuardian's daily cost was given as €4 (plus a one-off installation charge), described as a small fraction of the €225 average daily cost of a care home in Ireland.

Nigel Cobbe added: "Our latest SmartGuardian underscores our commitment to providing unparalleled safe independence in Irish homes, underpinned by our innovative and privacy-centric stick model technology. It's a smarter, safer, and more affordable way to live at home for longer."

Key features of SmartGuardian, as listed in the feature: non-identifiable stick-figure monitoring; AI-powered visual emergency confirmation via a stick-figure animation reconstructed from sensor data rather than video; direct two-way communication; an effortless "Raise to Call" gesture function; AI fall detection; proactive anomaly detection that learns routines; discreet, non-wearable sensor technology; prompt family alerts; and a daily cost of €4 plus a one-off installation charge.

End of reproduced feature. The remainder of this page is SmartCare Living's own editorial context and was not part of the original publication.

Context & fact-check: where the falls figures come from

The short version. The "one in three over-65s fall each year" line in the feature is the international figure, most often attributed to the World Health Organization. It is a fair global headline, but it is not the Irish number. In Ireland, the best local evidence (TILDA) is more specific: roughly one in eight community-dwelling over-70s need medical attention for a fall each year. Both things can be true at once: many older people have a minor fall, while a smaller share have one serious enough to need a doctor or hospital.

Falls are the reason this technology exists, so the statistics matter and they deserve to be quoted accurately. Here is the fuller picture.

The global figure (WHO)

The World Health Organization describes falls as the second leading cause of unintentional injury death worldwide. It estimates that around 684,000 people die from falls each year globally, and that 37.3 million falls each year are severe enough to require medical attention (WHO, Falls fact sheet). The "roughly a third of community-dwelling adults over 65 fall at least once a year" framing used in the feature is the long-standing international estimate that appears across WHO and public-health literature. The figure climbs with age.

The Irish figure (TILDA)

For an Irish audience, The Irish Longitudinal Study on Ageing (TILDA) at Trinity College Dublin is the more relevant source. Its research on falls requiring medical attention found that approximately one in eight people aged 70 and over needed medical attention for a fall in the previous year – an estimated 62,000 older adults, with more than 32,000 presenting to emergency departments (TILDA, Wave 6; published in Age and Ageing). TILDA also notes that Ireland currently has no national falls-prevention strategy, despite strong international evidence that coordinated approaches reduce falls and fractures.

So when you read "one in three" in a headline, read it as: a fall of some kind is common in later life, and the more serious end of that range is what puts tens of thousands of Irish people in front of a doctor every year. That is the problem a fall-detection system is designed to shorten the response to, not prevent. For prevention itself, see our guide on how to prevent elderly falls at home.

Two different "falls" figures, and why both are right Sources: WHO Falls fact sheet (global); TILDA / Age and Ageing, Wave 6 (Ireland, over-70s needing medical attention). Bars show share of the relevant population per year.
Global versus Irish falls figures compared The international estimate is that roughly one in three community-dwelling adults over 65 fall at least once a year, about 33 percent. The Irish TILDA figure for over-70s who need medical attention for a fall is about one in eight, about 12 percent. The two figures measure different things: any fall versus a fall serious enough to need medical attention. Global, over-65 any fall in a year (WHO/intl.) ~1 in 3 (33%) Ireland, over-70 fall needing medical attention (TILDA) ~1 in 8 (12%) 0% ~33% (full bar width) Different denominators: "any fall" is much more common than "a fall needing medical care."

The takeaway: the global "one in three" and the Irish "one in eight" are not contradictory. One counts every fall; the other counts only falls serious enough to need medical attention. Either way, the risk is real and rises sharply with age, which is the case for having a reliable way to call for help.

The cost comparison

The feature contrasts SmartGuardian's daily cost with "the €225 average daily cost of a care home in Ireland." That care-home figure is broadly consistent with published data: the National Treatment Purchase Fund (NTPF), which agrees nursing-home prices under the Fair Deal scheme, underpins average private nursing-home costs of roughly €1,560–€1,575 per week, which works out at about €220–€225 per day. It is an average, so individual homes and regions vary considerably. The comparison is a useful illustration of scale, not a like-for-like swap: a nursing home provides 24-hour personal and nursing care, whereas an in-home safety system is one part of staying at home for longer. For how the home-care side adds up, see Fair Deal versus home care costs.

How the stick-figure (pose-estimation) technology actually works

The "stick figure" in the feature is not a marketing metaphor. It refers to a real and well-established field of computer vision called human pose estimation (also called skeleton-based or keypoint detection). It is worth understanding, because it is the part that makes the privacy claim plausible rather than just a slogan.

Step 1: detect keypoints, not faces

Pose-estimation algorithms locate a set of body "keypoints" – head, shoulders, elbows, hips, knees, ankles and so on – and join them into a skeleton, or "stick figure." This is a mature technique in articulated body pose estimation: the output is a small set of coordinates describing posture and movement, not a recognisable image of a person (see the overview of articulated body pose estimation).

Step 2: read movement over time

A fall is not a single frame; it is a pattern. By tracking how those keypoints move from moment to moment – a rapid downward change in the hips and shoulders, followed by stillness on the floor – the system can distinguish a fall from sitting down quickly or lying on a sofa. Researchers describe this as skeletal action recognition, and it is an active research area for elderly fall detection precisely because the skeleton discards appearance while keeping the movement information that matters.

Step 3: keep the data anonymised, ideally on-device

Because only the skeleton (not the camera image) needs to be analysed and shared, this class of system can be designed to be privacy-preserving. The research community has explicitly studied privacy-preserving pose estimation, including approaches that degrade or never capture the recognisable image while still extracting the pose (for example, work on learning privacy-preserving optics for human pose estimation, IEEE/CVF ICCV 2021). More broadly, the principle of visual privacy and the use of edge (on-device) computing – processing data on the local device rather than uploading raw footage to a server – are recognised ways to reduce privacy risk.

What this means in plain English. A well-designed pose-estimation system can confirm "a person has fallen in this room" and send a stick-figure animation that shows the posture, without ever transmitting a photograph or video of the person. That is a genuine, design-level privacy advantage over a camera that streams footage. It is a meaningful improvement, not an absolute guarantee. Any connected device handles some data, so privacy depends on how a specific product is built and configured. We therefore describe SmartGuardian as privacy-first by design rather than claiming "100% privacy." For our fuller treatment, see Privacy & Peace: AI Home Monitoring.

The other advantage is practical: because nothing is worn, the system keeps working in the bathroom, in bed, and on the days a pendant or watch is left on the bedside table. That is the core argument for ambient detection over wearables, which we cover in No Wearables? No Worries. The full overview of the category sits in our pillar guide, non-wearable fall detection.

Third-party validation

Press coverage is one signal among several. Here are the independent markers behind the SmartGuardian system, and what each one does and does not mean.

  • Three Ireland SME Grant (2025). Smart Space Technologies was named among the recipients of the 2025 Three Ireland Small Business / SME grant programme, which awards selected Irish SMEs a package of cash and Three connectivity and device support, delivered in partnership with Enterprise Nation. It is a recognition of the business, not a clinical endorsement of the product.
  • HSE Technology Partner. Smart Space works as a technology partner in the Irish health-and-care setting. This reflects a working relationship; it is not a statement that SmartGuardian is a regulated medical device (it is not, see below).
  • Senior Times feature (April 2025). The reproduced article above is genuine editorial coverage in an established Irish title for older adults.

We list these because they are verifiable. We have deliberately not repeated the marketing superlatives from the press feature ("leading", "unparalleled", "complete anonymity") as if they were our own measured claims; in our editorial voice they remain the company's 2025 wording.

What SmartGuardian is, and is not

It is It is not
An ambient, non-wearable fall-detection and help-calling system for the home A regulated medical device. SmartGuardian is a safety and monitoring system, not a clinical or diagnostic device
Privacy-first by design: it shares an anonymised stick-figure animation, not video or photographs A guarantee of "100% privacy." It is a connected system, so privacy depends on how it is built and run
A way to shorten the time before someone responds to a fall A way to prevent falls. Prevention needs environmental changes and clinical input
One affordable part of staying independent at home for longer A replacement for nursing or personal care where that level of support is genuinely needed

If that honest framing is what you were hoping to find, it is also how we will talk to you if you get in touch. We would rather tell you that simpler changes are enough than sell you a system you do not need.

Sources

  • Senior Times, "Smart Space – Privacy Protected with Innovative Stick Model Technology", 25 April 2025: seniortimes.ie
  • World Health Organization, Falls fact sheet (684,000 fatal falls/year; 37.3 million falls needing medical attention/year): who.int
  • The Irish Longitudinal Study on Ageing (TILDA), falls requiring medical attention among over-70s (~1 in 8; ~62,000 people; >32,000 ED presentations), Wave 6, published in Age and Ageing: tilda.tcd.ie
  • National Treatment Purchase Fund (NTPF), Fair Deal nursing-home pricing (basis for ~€225/day average): ntpf.ie
  • Three Ireland Small Business / SME Grant programme 2025 (recipient recognition): three.ie
  • Human pose estimation background: articulated body pose estimation; visual privacy. Privacy-preserving pose estimation: Hinojosa et al., "Learning Privacy-preserving Optics for Human Pose Estimation," IEEE/CVF ICCV 2021.

Editorial note: the boxed feature above is reproduced from Senior Times (25 April 2025) and reflects the company's wording at that time. The surrounding context, fact-check and technology explainer were added by SmartCare Living and last updated on 17 June 2026. SmartGuardian is a home safety and monitoring system, not a medical device.

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