  An increasing amount of civil engineering applications are utilising data
acquired from infrastructure instrumented with sensing devices. This data has
an important role in monitoring the response of these structures to excitation,
and evaluating structural health. In this paper we seek to monitor
pedestrian-events (such as a person walking) on a footbridge using strain and
acceleration data. The rate of this data acquisition and the number of sensing
devices make the storage and analysis of this data a computational challenge.
We introduce a streaming method to compress the sensor data, whilst preserving
key patterns and features (unique to different sensor types) corresponding to
pedestrian-events. Numerical demonstrations of the methodology on data obtained
from strain sensors and accelerometers on the pedestrian footbridge are
provided to show the trade-off between compression and accuracy during and
in-between periods of pedestrian-events.
