Tech Talks Daily
00:08:33 · Mike Link, Neil C. Hughes
[00:08:33] S1: It's not SIM related. It's Wi Fi based. We've thought about putting a a SIM card in the consumer version in the future. Yeah. We haven't even fully released the consumer version. We've sent it out probably to, like, 500 families to use, and, you know, that's how we've been, you know, building and and kinda modifying the the the model because we have it in tons of care homes. In The US, in in a bunch in The UK, some in Japan. So the the way that we have now started to modify that for in home is by having families use it in home. So, right, know, as of now, you can't even go, you know, buy the consumer version. It's only in community and residential settings. But... Yeah. Yeah. Yeah. The the SIM card is definitely the thing that we've looked at because in a lot of homes, especially in rural places in America or, you know, I would assume also in The UK Yeah. Wi Fi can be an issue and connectivity can be an issue. So... And even in some of the facilities, like, they don't want to have Wi Fi go down and then, you know, potentially miss something. But at the same rate, like, a lot of these facilities do have Wi Fi now, so it hasn't really been too much of an issue. [00:09:43] S0: So when you've put all these in, what changes when computer vision has to operate reliably across millions of live devices rather than just a controlled pilot? What have you seen? Has anything surprised you here?
00:09:43 · Neil C. Hughes, Mike Link
[00:09:43] S0: So when you've put all these in, what changes when computer vision has to operate reliably across millions of live devices rather than just a controlled pilot? What have you seen? Has anything surprised you here? [00:09:56] S1: Nothing really. I mean, if if you think about it, there's already millions of connected devices with Kami Home. We have more than a million paid users. There's probably three or 4,000,000 free subscribers to the KamiHome platform. So we already manage a huge amount of data. So it's basically the same thing with the other system, the KamiCare elder care in communities and facilities system. [00:10:24] S0: What kind of feedback have you had from some of those nursing homes or elderly homes? Have you had any feedback from around the world? I know you said The UK, Japan, US. How's that feedback?
00:10:34 · Mike Link
[00:10:34] S1: The feedback is always kind of the same. It's kind of shock and surprise because when we go to sell the solution to some of these communities and facilities, they're like, well, we don't really have an issue with falls. They just kind of happen. And, you know, how is detecting the event going to help us prevent? They kinda feel like it's reactive. Yeah. And I think the thing that's surprising to them is by seeing what happened in a reactive fashion, they're actually able to be proactive because most of the time, these people aren't hurting themselves. Like, ninety six percent of falls aren't resulting in some kind of hip fracture or injury or event that makes them need emergency services. So the majority of falls that are detected are people putting themselves on the ground because they don't have the strength or the confidence to walk and do the things they need to do. So what happens a lot of the time is either somebody puts themselves on the ground or they scoot off the bed onto the ground. And then what happens in a facility is if a staff member comes in... Imagine you have a memory care patient who's got dementia. Their memory care resident has dementia, and you find them on the ground. They're... They can't remember why they are on the ground. And then as somebody running the facility, you have to document this as a fall. But in fact, it wasn't a fall. And then when they can see the clip of the fall, they go, oh, they just scooted onto the floor. They actually wanted to put their shoes on, but they sat on the floor to put their shoes on because they didn't have the strength to stand up. And now they could send a nurse in there when they need to put their shoes on or when they need to dress or change or whatever the thing is. So it's these kind of, like, environmental changes maybe in, like, the room layout or activity changes in their routine where maybe a staff member can help them is where the the realizations happen. And then the other thing is you could start to see as somebody's declining because they'll start to go to the ground. Right? It's not necessarily a fall, but it's detecting the person on the ground, which allows you to see the meaningful change and then, you know, make a change in the way that you care for them.
00:12:33 · Neil C. Hughes, Mike Link, S2
[00:12:33] S0: And I'm curious. How do you reduce false alarms while still detecting the accidents that require a a rapid human response? Tell me a bit more about that, and and I would imagine that's somewhat of a challenge or can be. [00:12:46] S1: It definitely was. I think for the first handful of years, we had a lot of false events because the model was being trained. But, you know, if you imagine, you know, tens of thousands of falls, it's probably, you know, maybe 2023, maybe 2024, when we were able to actually hit this accuracy number because we had enough falls that the data was being trained on. [00:13:13] S2: Do you need AI agents that you can trust? Well, with an AI data layer providing real time connection within your data platforms, you can trust your agents to provide accurate solutions. So scale your business by trusting your agentic AI accurately getting the work done for you. Trust its capabilities with Denodo. And you can do that by simply visiting denodo.com to learn more. [00:13:37] S0: And how do you think the the tech should differ between living independently at home and a a resident in a managed care setting? I know you've only got the one at the moment, but you're obviously looking at both. Is there a big difference there?
00:13:53 · Mike Link
[00:13:53] S1: There is kind of a big difference. I think some of the challenges are a little bit different. If you think about in a facility, it's very controlled versus in home, you have a lot of different objects, people, lighting. So in a way, the community is kind of like a test facility. You know, the lighting is typically the same. All the rooms are the same. Typically, it's a one bedroom or a studio. Whereas a home, maybe you have four bedrooms. Maybe you have, you know, dim lighting, or maybe you have really bright lighting, or maybe you have a dog running around. And these are all things that the model has to differentiate. So I think that's the next kind of challenge is how do you make fall detection in home just as accurate. The other thing is the visual sensor isn't able to see everything always in the way that you set up in the home. And sometimes you need, like, five or six devices. So the thing we've been looking at is, like, what kind of ancillary device will we be able to connect with the visual sensor that we can... Oh, like, say, okay. The visual sensor can't see behind the couch over here, but there's Wi Fi radar mapping technology where we can see if a body is somewhere in the room. So maybe when the camera or the visual sensor or, you know, something else wouldn't be able to see in one area, maybe we could use a different type of technology to detect the other area. So, yeah, we've been looking at a handful of things like radar. We've looked at potentially using, like, robot vacuums or, like, mini drones in the home as well as wearable devices. We looked at a ring in 2025 to potentially see if we could detect when somebody's heart rate, like, dropped significantly in in home because maybe this would be indicative of all. But there's a bunch of other devices that we've looked at to try to cover spots that we might miss in a home that we could easily get in the care setting with with one type of technology.
00:15:59 · Neil C. Hughes
[00:15:59] S0: And if we do have anybody listening in... Maybe they're a care provider or work in the industry for, and they're looking for the ROI on this. What is the the business case for a care provider, and and what results show the tech and any technology is improving outcomes rather than just adding another dashboard that they need to monitor?