Real-time Health Dashboard with Wearable Sensors

The challenge
Care teams must watch more patients with fewer staff. Occasional manual checks miss early warning signs and unnoticed falls, and home care often has unreliable internet.

What we built
We built a real-time health dashboard on our own wearable sensors. Body-worn sensors stream movement and temperature to a phone or gateway, where AI detects falls and classifies walking, resting, and sleeping.

Clinicians see each patient’s state, trends, and alerts in one view. Processing runs at the edge, so monitoring keeps working offline in home care or rural areas and syncs when the connection returns.

Business value

  • Falls and unusual inactivity detected immediately
  • Fewer one-to-one observation hours
  • Safer care at home and in rehabilitation
  • Works with or without connectivity

Where else it applies
The same approach transfers to elderly care, rehabilitation clinics, workplace safety, and sports medicine. It belongs to our Real-Time Intelligence work: data analysed as it happens, with alerts when something needs attention, instead of reports that arrive too late.

Task

Monitor patients continuously with wearable sensors, even offline.

  • Strategy

    Edge-first architecture with AI fall and activity detection and clinician dashboards.

  • Design

    Wearable sensor app, on-device AI, flexible sync to the backend, and a web dashboard with patient and ward views.

  • Client

    Hospital in Croatia (EU)

  • Tags

    ai, data lake, Health, iot, real-time processing

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