Although the Global Position System (GPS) can help to navigate around the world, it cannot provide useful information in an indoor environment. I developed an indoor localization system using wireless sensor networks (WSNs). This system has two goals: (1) to make a system that runs for long duration without changing or charging batteries, and (2) to obtain more accurate position estimates of the target nodes using received signal strength indicator (RSSI) values than other localization systems using different localization algorithms. I chose ANT radio due to its lower power consumption. I applied a fingerprinting-based algorithm and used the parameters of the closest point to the estimated target node to calculate the final position of a target node. A local weighted k-Nearest Neighbour algorithm was proposed to estimate the position of a mobile node. I compared my system to other indoor localization systems to assess its performance. / February 2016