In recent years, the use of wireless sensor networks has increased. This is due in part to the increasing miniaturization, decreasing costs and the identification of real-world scenarios where sensors can be deployed. Device-free Passive Localisation (DfPL) is the identification of a person without the need for any physical devices i.e. tags or sensors. A DfPL system uses the Received Signal Strength Indicator (RSSI) for monitoring and tracking changes in a Wireless Network infrastructure. The changes in the signal along with prior fingerprinting of a physical location allow identification of a person's location. The human body contains more than 70% water and it is known that resonance frequency of water is 2.4 GHz. Thus the human body reacts as an absorber attenuating the wireless signal. Many of the proposed RSSI-based technologies use the fingerprinting method for estimating the location of the tracked person. Fingerprinting in location estimation systems refers to a method that compares the fingerprint of some characteristic of a signal that is location dependent. This research is focused on implementing DfPL using a Wireless Sensor Network (WSN) to locate the presence of an individual within indoor locations. The main reason for deploying Wireless Sensor Network DfP Localisation is due in part to the benefits of deploying when a wireless network infrastructure is not available. Thus, a novel system that can identify multi-occupants in an environment using patterns of motion from those monitored areas has been deployed. A Pattern Recognition Neural etwork was used to identify two people in the environment. No other work based on the Device-free Passive Localisation (DfPL) technique has focused on multi-occupancy. DfPL is a new approach for detecting a person's presence and estimating the actual position of that person. Various functions such as: tracking, identification, multi-person and automatic construction of a passive radio map could be implemented for DfPL systems. This project is focused on addressing the possibility of deploying a multi-person localisation system based on Wireless Sensor Network DfPL. RSSI-based localisation techniques became more attractive because of their simplicity and robustness in environments affected by multipath compared to the techniques based on metrics like time or angle. The simplicity is achieved due to RSSI-based localisation systems not requiring additional hardware. Further, the RSSI values can be obtained by using functions that are already provided. How- ever, RSSI-based techniques are significantly affected by the variance of the wireless signal.