After comparing the ideas and returning to the evidence, I currently think the strongest probable direction is:
<aside> ✈️
A biosensing-informed contextual airport-support system for autistic adults travelling independently.
</aside>
The important change is the role of biosensing. I am not trying to find a signal that tells the system “this person is overloaded.” The evidence does not justify that.
Instead, I am exploring physiological information as a timing / awareness signal that may indicate it is useful to check in.
<aside> →
Biosensing + movement + airport context → cautious interpretation / uncertainty → transparent check-in → user choice → optional support
</aside>
The contextual layer could include information such as where the traveller is in the airport, journey stage, movement, crowding, queues, noise or environmental conditions, disruption or gate changes, time pressure and nearby support locations.
The prompt should make uncertainty visible rather than pretending the system knows what the traveller feels.
“A change was detected while this area became busier. Would support help?”
The traveller remains the final interpreter.
Contextual support
Sensory support
Optional regulation support
At every stage, the traveller should still be able to pause, dismiss, override or request support manually.
My sensing research is also becoming more specific. The current working shortlist is:
EDA + PPG / heart rate + accelerometry