KEYWORDS: Antennas, Multiplexers, Computer architecture, Multiplexing, Received signal strength, Control systems, Statistical analysis, Algorithm development, System identification, Electromagnetism
Radio frequency identification (RFID) systems based on passive tags are used successfully in a wide range of object
identification applications. However, the increasing needs to meet new demands on applications of localization and
tracking create a new field for evolution of the RFID technology. This paper presents the design, implementation, and
evaluation of a cost-effective localization system for in-building usage that is able to localize objects that carry passive
RFID tags. The RFID reading is performed by a single Reader and an array of directional antennas through multiplexing.
Evaluation and experimental results from three localization algorithms based on RSSI are presented.
Indoor localization is considered to be a key aspect of future context-aware, ubiquitous and pervasive systems, while
Wireless Sensor Networks (WSNs) are expected to constitute the critical infrastructure in order to sense and interact with
the environment surrounding them. In the context of developing ambient-assisted living and aftermath crisis mitigation
services, we are implementing WAX-ROOM, a WSN specially developed for indoor localization but at the same time
able to sense and interact with the environment. Currently, WAX-ROOM incorporates three different localization
techniques and an optimal fusion rule. The proposed WSN's architecture and advantages, as well as measurements
results regarding its performance in terms of localization accuracy are presented herein, demonstrating the eligibility of
the proposed platform for indoor localization.
A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on
ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a
market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf
system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield
highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance
characteristics is established. A low-complexity but accurate sensor fusion and localization technique is
then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered
most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is
subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed
fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most
flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and
availability.
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