AI has reached the hospital – but not its building

Where the gap lies

There are understandable reasons why AI is still little used in the operation of hospitals and care homes:

• Separate data: Building management, meters, maintenance and individual sensors deliver data in different systems and formats. A shared picture rarely emerges.
• Rules for whole areas: Plant runs on set points and schedules for zones or wards – not on what is happening in a single room.
• Small teams, much technology: Building services and facility management look after many systems at once. Little time is left for analysing data.
• Three goals, three responsibilities: Room quality, energy and operations are often owned by different people and rarely looked at together.

How Fact & Feeling uses AI

Our approach follows five steps – from a single reading to action in the room:

• 1. Bring building data together: We connect existing data from building management (BMS), meters, existing sensors and exports – in any format. Where measuring points are missing, plug-and-play sensors are added, without building work.
• 2. Room context from floor plans: Floor plans and use give every room its context: size, position, orientation and whether it is a patient room, a waiting area or a day room.
• 3. Analysis per room: The AI is trained individually for each building. It analyses every variable on its own, room by room and hour by hour, and places it where research describes links between indoor climate and wellbeing.
• 4. Act: The result is recommendations to the right people – usually building services and facility management – or, where the plant is connected and the facility wants it, automatic control within fixed limits.
• 5. Learn: Every response is measured and fed back into training. Over time the models become more accurate for each building.

Health, energy and operations together

Anyone who wants to cut energy costs in a hospital cannot simply ventilate or heat less. Anyone who wants to improve indoor air quality cannot lose sight of energy use. And every change has to fit everyday operation.

That is why the AI looks for the optimum between the three goals in every room – in a fixed order: conditions for the people in the room come first. Savings never come at their expense and never at the expense of hygiene. Hygiene-critical rooms such as operating theatres or intensive care stay outside any automatic control.

What it takes to start

No new building technology and no large IT project. The way in is an audit in selected areas: we analyse the existing building data, link it with the floor plans and show, room by room, where room quality, energy and operations stand. The measurement phase can then become ongoing monitoring of the hospital or care home.

What the AI does not do

To avoid false expectations:

• No medicine: Fact & Feeling is not a medical device, makes no diagnoses and does not monitor patients.
• Not an alarm or safety system: The facility’s fire alarms, heat protection and medicine storage stay as they are.
• No personal data: Our room sensors measure the environment, not people. We process no personal data and no patient data.
• No decision without people: Building services, hygiene and nursing decide. The AI gives them a better basis.