04

Applied research & simulation

Some rules cannot be tested by deploying them and watching. Either the cost of being wrong is too high, or the situation is too rare to wait for, or the people involved cannot be experimented on.

The answer is to model the thing and run the rules against the model — and, before that, to read what has already been established rather than rediscovering it. This is the work behind the graduation project: about forty peer-reviewed sources resolved into a stated gap, a formal rulebook built from it, and a simulation whose entire purpose is to verify that rulebook before it reaches a real home.

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01

An ADL smart home for Alzheimer's safety and caregiver burden reduction

A research project in ambient assisted living (AAL), addressing safety and caregiver burden for people living with Alzheimer's at home. The central constraint came out of the literature rather than out of preference: visual surveillance is where acceptance collapses, and the highest-risk rooms are the ones a camera is least tolerable in. So the system senses ambient, non-visual signals only — no cameras, no always-listening microphones — and the engineering problem becomes inference under that constraint.

Activities of daily living (ADL) are read as evidence, never as proof. An opened medication box records an interaction, not a swallowed dose. A stove on is ordinary until the kitchen is empty. A finite-state rulebook resolves that evidence into an explainable care state. The simulation exists to verify the rulebook — the home is modelled in Unreal Engine so scenarios are injected and replayed identically, which is how care rules get tested before anyone's safety depends on them.

Unreal EngineAmbient sensingFinite-state modellingApplied research

The simulation is not the product. It is the instrument for testing whether the care rules hold.

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