One of the greatest challenge of research on smart homes is to be able to recognize the ongoing Activity of Daily Living (ADL) in real-time and make prediction on the future action of the resident. To accomplish this task, it is important to have accurate information. In this paper, we present a novel passive RFID Indoor Tracking System (ITS). The goal of this ITS was to create a simple solution from data mining that could be easily deployed in any smart environment without requiring specialized human expertise on RFID. The tracking average 80% of accuracy and show promising results for large scale deployment.