A practical comparison between filtering algorithms for enhanced RFID localization in smart environments

Abstract

The rapid adoption of wireless technologies has increased the interest of many laboratories about the field of Wireless Sensor Network (WSN) or the Radio-Frequency Identification (RFID) technology which has emerged as a winning combination for the implementation of an advanced assistance system within smart environments. To fulfill the important mission of a technological assistance, an algorithm first had to identify the ongoing activities of its user by tracking everyday life objects in real time using, for example, passive RFID tags. To increase the quality of information extracted from the objects localization by properly using the Received Signal Strength Indicator (RSSI), this paper explores Kalman filter, particle filter and few others filtering algorithm that enhances the tracking performance. It also discusses three of the most interesting methods that can be applied for the localization of objects in smart environments without requiring the installation of references tags everywhere. Finally, to increase the value, we include experiments that were conducted within a real smart home infrastructure to review the positive and negative elements of each method.