Wireless sensor networks (WSN) are built of spatially distributed nodes which are connected to
one or more sensors. Each sensor node typically consists of several parts that are connected to an energy
source like a battery, which limits the power resources of a wireless sensor. The major energy demanding
parts in a sensor network node are the processor and the transmitter. Typically, those nodes that work continuously
consume huge amounts of power. This suggested reducing the quantity of the obtained data to reduce
the required power, of course without losing any important data. It means that the data should be sent
through sensors with minimal additional operations performed by the processor. This is called the Compressive
Sensing which is an innovative technique that fulfills the previously mentioned requirements. The aim of
this research is to evaluate the reliability of compressive sensing when applied on signals obtained in real life.
For this purpose; two types of signals are used with two different reconstruction algorithms. The obtained results
are discussed and some conclusion remarks are presented.