ETH - Indoor Positioning & Indoor Navigation


13:15 - 13:45	Andreas Löffler (presenting author), Simon Heisler: Simple Navigation with RFID-enabled cell phones This paper presents a navigation application based on RFID-capable (i.e. NFC-based) cell phones. The cell phone is used to read-out, at various locations fixed, HF-RFID tags, to receive, first, the position of the RFID tag, and second, the map environment surrounding the RFID tag. Therefore, the distributed RFID tags contain their fix positions and an extract of the basic map, which shows the tags nearby environment. This combination of RFID tags and cell phone generates a particular navigation application improving the performance of an indoor navigation system. By using a cell phone the user is provided with a graphical user interface leading the user transponder-by-transponder to its final destination. The advantages of the system include a non a priori knowledge and a small positioning error due to the limited range of the NFC technology.

13:45 - 14:15	Ming Zhu (presenting author), Kefei Zhang, William Cartwright: An Investigation of 3D GIS-Aided RFID Indoor Positioning Algorithms The probabilistic location fingerprinting algorithm is investigated for its potential people mobility tracking applications indoor using Radio Frequency IDentification (RFID). The environmental impacts on the radio frequency (RF) signal propagation in the training phase and the positioning errors due to the received signal strength (RSS) variations are two key limiting factors for precise indoor positioning. A 3D Geographical Information System (GIS) ray tracing algorithm for location fingerprinting training phase and probabilistic maps for personal positioning phase are developed and evaluated. Results suggest that the new algorithms developed can reduce the workloads and increase the positioning accuracy by utilising the spatial information provided by a 3D GIS.

14:15 - 14:45	Fernando Seco (presenting author), Christian Plagemann, Antonio R. Jiménez, Wolfram Burgard: Improving RFID-Based Indoor Positioning Accuracy Using Gaussian Processes The signal strength (RSSI) of radio-frequency signals emitted from beacons, such as RFID tags, placed at known locations in an environment, can be used to build local positioning systems (LPS) for persons or mobile objects. In indoor environments, multipath propagation of the RF signals, as well as the presence of obstacles and people, lead to complex RSSI distributions which are inaccurately modelled by simple parametric models. In this work, we present a Bayesian method for an indoor RFID location and guidance system which uses an observation model based in Gaussian processes (GPs) to represent the environment-specific RSSI distributions for the individual beacons. The experimental results obtained in an indoor environment demonstrate the effectiveness of this approach.

14:45 - 15:15	Alejandro Ramirez (presenting author, at Siemens), Christian Schwingenschlögl: Experiences with Time-of-Flight Positioning There is an increasing availability of active RFID systems with its long communication range. While short-range RFID technologies allowed a relatively precise localization as the range was only a few centimetres, this is no longer possible with long-range systems. In this work we present our experiences with our own round trip time-of-flight measurement method. The proposed method is hardware agnostic and only requires an existing communication protocol that generates an immediate answer to a message, such protocols are very common. We implemented said method on an active RFID hardware platform with available crystal oscillators of 8MHz/16MHz. We chose a very challenging environment were all walls, doors and ceilings are metallic. Our measurements show an average accuracy of 2.801 meters with non line-of-sight (NLOS). The resilience of the method was also tested by opening and closing the doors between the RFID readers and the tags, showing a precision of 1.101meters.

15:15 - 15:30	Maximina Paralta (at Intelligent Sensing Anywhere), Pedro Mestre (at University of Trás-os-Montes and Alto Douro), Rafael Caldeirinha, Jorge Rodrigues and Carlos Serôdio (presenting author, at University of UTAD, Villa Real): TraceMe - A Tool for Safety and Security in Clinical Governance using RFID and Integration of Location Services in a Hospital Environment TraceMe is an indoor location and tracking solution for people and asses, being a valuable tool that can be used in clinical governance to map, monitor and measure the status and location of high-value assets. It also provides critical data needed to improve workflows and processes associated with these assets. Besides its use as a simple location-based system it can also be used in access control applications for restricted areas, triggering alarms whenever anomalous situations occur, e.g. when a specific equipment is taken outside its area, or when a tag is violated. It is now being installed and tested in a hospital in Portugal, where it is being integrated with other systems such as BabyMatchTM and AIDA (Agency for Integration, Archive and Diffusion of Medical Information). For hospital administrators, TraceMe rapid-impact implementation and fully managed service model not only supports healthcare business processes, but also reduces costs and increases revenue.

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