Indoor navigation is a challenging task for visually impaired people. Although there are guidance systems available for such purposes, they have some drawbacks that hamper their direct application in real-life situations. These systems are either too complex, inaccurate, or require very special conditions (i.e., rare in everyday life) to operate. In this regard, Ultra-Wideband (UWB) technology has been shown to be effective for indoor positioning, providing a high level of accuracy and low installation complexity. This paper presents SUGAR, an indoor navigation system for visually impaired people which uses UWB for positioning, a spatial database of the environment for pathfinding through the application of the A* algorithm, and a guidance module. The interaction with the user takes place using acoustic signals and voice commands played through headphones. The suitability of the system for indoor navigation has been verified by means of a functional and usable prototype through a field test with a blind person. In addition, other tests have been conducted in order to show the accuracy of different relevant parts of the system.

This paper presents a novel advanced Bluetooth Low Energy (BLE) beacon, which is based on an array of frequency-steered leaky-wave antennas (LWAs), as a transmitter for a Direction-of-Departure (DoD) estimation system. The LWA array is completely passive, fabricated in a low-cost FR4 printed-circuit board and designed to multiplex to different angular directions in space each one of the three associated BLE advertising channels that are used for periodically transmitting the ID of the beacon. This way, the use of more expensive hardware associated to electronic phased-array steering / beam-switching is avoided. Four commercial BLE modules are connected to the four ports of the array, producing an advanced BLE beacon that synthesizes twelve directive beams (one per each port and advertising channel) distributed over a wide Field of View (FoV) of 120 degrees in the azimuthal plane. Then, any BLE enabled IoT device located within this FoV can scan the messages from the beacon and obtain the corresponding Received Signal Strength Indicator (RSSI) of these twelve beams to estimate the relative DoD by using amplitude-monopulse signal processing, thus dispensing from complex In-phase/Quadrature (IQ) data acquisition or high computational load. We propose an angular windowing technique to eliminate angular ambiguities and increase the angular resolution, reporting a root mean squared angular error of 3.7° in a wide FoV of 120°.

Simulations are currently an essential tool to develop and test wireless sensor networks (WSNs) protocols and to analyze future WSNs applications performance. Researchers often simulate their proposals rather than deploying high-cost test-beds or develop complex mathematical analysis. However, simulation results rely on physical layer assumptions, which are not usually accurate enough to capture the real behavior of a WSN. Such an issue can lead to mistaken or questionable results. Besides, most of the envisioned applications for WSNs consider the nodes to be at the ground level. However, there is a lack of radio propagation characterization and validation by measurements with nodes at ground level for actual sensor hardware. In this paper, we propose to use a low-computational cost, two slope, log-normal path-loss near ground outdoor channel model at 868 MHz in WSN simulations. The model is validated by extensive real hardware measurements obtained in different scenarios. In addition, accurate model parameters are provided. This model is compared with the well-known one slope path-loss model. We demonstrate that the two slope log-normal model provides more accurate WSN simulations at almost the same computational cost as the single slope one. It is also shown that the radio propagation characterization heavily depends on the adjusted model parameters for a target deployment scenario: The model parameters have a considerable impact on the average number of neighbors and on the network connectivity.