Table 3 Sample data fusion use cases at different levels in healthcare

LDF

To detect sudden health deterioration and inform healthcare staff

To transfer biometric information about individual patients to higher data fusion levels, specifying the detected symptoms and the location (i.e. room and floor)

Detecting a monotonic increase of a single body health indicator (e.g. body temperature), where every next value is higher than the previous within a given time frame

Detecting a rapid simultaneous increase in multiple body health indicators (e.g. body temperature, blood pressure, heart rate) within a given time frame

Temporal semantics

Sequential operators to capture the chronological order of events

Iterative operators to compare current values with respect to the previous ones

Condition checking to map streaming sensor values to background knowledge on patients’ health records

MDF

To allocate more hospital staff on floors with increased demand

To detect a potential disease outbreak within the hospital

Detecting identical health deterioration symptoms coming from the same room/floor

Temporal spatial semantics

Condition checking to map streaming values with locations of rooms and floors

HDF

To navigate ambulances to less overloaded healthcare institutions

To detect a potential disease outbreak within a metropolitan area

Detecting identical health deterioration symptoms coming from hospitals located in the same area

Temporal spatial semantics

Condition checking to map hospitals and ambulances with their geographical locations