Journal Articles

Wireless Sensor Networks are popular solutions for various applications in order to reduce the efforts required by traditional cable-based systems. If the system in question is used to monitor and control physical processes, robust and reliable communication services have to be provided by the network. This is especially true for industrial or vehicular applications where the nodes are deployed in environments facing harsh propagation conditions. Usually, the effect of this on the system performance is studied on isolated layers of the OSI-reference model only. Therefore, we present results from a measurement campaign of vehicular environments that try to estimate the achievable robustness with respect to multiple OSI layers. Our results show that even if the link is rather poor, protocols on the upper layers are able to compensate this at the cost of additional delay.

This paper presents a scanning method for indoor mobile robot localization using the received signal strength indicator (RSSI) approach. The method eliminates the main drawback of the conventional fingerprint, whose database construction is time-consuming and which needs to be rebuilt every time a change in indoor environment occurs. It directly compares the column vectors of a kernel matrix and signal strength vector using the Euclidean distance as a metric. The highest resolution available in localization using a fingerprint is restricted by a resolution of a set of measurements performed prior to localization. In contrast, resolution using the scanning method can be easily changed using a denser grid of potential sources. Although slightly slower than the trilateration method, the scanning method outperforms it in terms of accuracy, and yields a reconstruction error of only 0. 08 m averaged over 1600 considered source points in a room with dimensions 9.7 m × 4.7 m × 3 m. Its localization time of 0. 39 s makes this method suitable for real-time localization and tracking.