{"id":36290,"date":"2026-05-20T10:55:34","date_gmt":"2026-05-20T08:55:34","guid":{"rendered":"https:\/\/keplervision.eu\/91-dutch-care-locations-solve-care-staff-shortages-with-ai-copy\/"},"modified":"2026-05-20T11:16:56","modified_gmt":"2026-05-20T09:16:56","slug":"keplers-automated-human-activity-recognition-in-care-homes","status":"publish","type":"post","link":"https:\/\/keplervision.eu\/en\/keplers-automated-human-activity-recognition-in-care-homes\/","title":{"rendered":"Kepler\u2019s Automated Human Activity Recognition in Care Homes"},"content":{"rendered":"

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Kepler\u2019s Automated Human Activity Recognition in Care Homes: Past, Present, and Future<\/h1>\n

Our company, Kepler Vision Technologies, has now been in business for 9 years. Our software is used at more than a hundred care locations. We have zero churn, meaning that expiring software agreements get extended for three to five years. This means that if you buy our software, you will have a long-term relationship with us. Therefore, if you are considering engaging with us, I believe you\u2019d be interested first in learning more about Kepler\u2019s past, present, and future. That is what this article is about.<\/p>\n

Kepler Vision\u2019s Background<\/h3>\n

About fifteen years ago, two Dutch AI professors and I had spun off a computer vision company from the University of Amsterdam. A few years later, the company was acquired by San Diego-based multinational Qualcomm [1]. Our intellectual property adviser at the time had successfully licensed his peer-to-peer patent portfolio to Apple, Microsoft, and Spotify [2]. All of us, the professors, the IP advisor, the University, and I, then pooled together some of the proceeds and started a new University spinoff company, Kepler Vision Technologies.<\/p>\n

Our plan was to bring a new emerging field of AI, called human activity recognition, to the market. <\/strong>Our plan was also not to waste our careers on, for instance, keeping someone on a phone app to increase the chances of clicking on an advertisement. Instead, we wanted to have a meaningful impact in the years to come.<\/p>\n

Demographics are good predictors of what will happen decades from now. Demographic projections indicate that populations in Europe, China, and Japan will age. This means that the demand for care increases. At the same time, the availability of caregivers decreases. For the Netherlands, where I am from, the number of long-term care workers per 100 people aged 65+ fell by more than 20% in the last ten years [3]. This shortage will increase rapidly in the years to come. Furthermore, a third of the elderly fall every year [4], making falls the second leading unintentional injury death after road traffic injuries [5].<\/p>\n

Our dream, therefore, was to build a calm, intelligent layer of awareness of human activities that could protect elderly, vulnerable people. <\/strong>The layer should help understaffed care teams respond earlier when needed, thereby giving caregivers more peace of mind. The intelligent layer would depend critically on the latest computer vision research, which is the specialty of my fellow founders and me.<\/p>\n

The Challenge of Starting a Company Serving Care Homes<\/h3>\n

The main uncertainty at the time was whether care homes would accept cameras as sensors in residents’ rooms. <\/strong>There were indicators to suggest that this may be the case. Cameras that look like smoke detectors were being sold to Dutch long-term care facilities. Using geofencing, an area in front of the door or the bed could be manually outlined. If many pixels in these areas changed intensity, an alarm would be triggered.<\/p>\n

My main concern with this rudimentary \u201csmart\u201d sensor, when we started Kepler, was that a geofencing-based motion detector was outdated technologyat the first location with 20 beds, but only if the system integrator has capacity; otherwise, the rollout needs to be delayed by 1 or 2process everything. <\/strong>It would lead to unnecessary false alarms, for instance, when a pillow falls from the bed or a foot sticks out. In addition, the solution was unreliable. If the cleaners in a care facility accidentally move the bed, the move invalidates the geofenced area, resulting in missed fall detections. Modern AI solves all these problems, and this insight led to our first product, which we called the Kepler Night Nurse.<\/p>\n

In the early years, selling our solution to care homes proved to be difficult, though. Carehomes are not military organizations, where decisions are taken at the top and executed at the lower levels.<\/strong> In care homes, the number of decision-makers and decision-influencers is endless: family representatives, caregivers, IT managers, board members, the innovation manager, the operations manager, and the Chief Financial Officer all need to be involved.<\/p>\n

Furthermore, such a decision process takes time.<\/strong> My experience of how the introduction of new technology in care homes works:<\/p>\n