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This volume contains the Work-in-Progress papers presented at IPIN 2019, the Tenth International Conference on Indoor Positioning and Indoor Navigation (http://ipin2019.isti.cnr.it/posters) held in Pisa, Italy, on September 30th-October 3rd, 2019.

No standard methods for evaluating indoor localization systems are generally accepted and used by researchers and industry. The lack of common test beds is a problem when evaluating the relative performance of different systems. As a step towards tackling this problem, the EvAAL Indoor Localization competition was launched in 2011, followed by the ongoing series of IPIN competitions. The EvAAL evaluation framework defines tools and metrics usable for comparing both real-time systems and off-line methods based on recorded data. The EvAAL framework is discussed in its incarnation along the various editions of the EvAAL and IPIN competitions, together with a discussion on the performance and technologies used by the competing systems.

Ambient Assisted Living applications are deployed in smart environments that provide some basic services, a typical example being user localization. AAL applications generally have low accuracy requirements for indoor localization; this opens the opportunity for parasitizing the existing smart environment infrastructure without adding dedicated positioning sensors. In this scenario, one can exploit simple binary sensors that are usually present in the smart environment, such as light and appliance switches or intrusion detection sensors, to obtain a rough estimate of the position of the user. This application is device-free, meaning that the user is not required to carry any device in order to be localized. In this paper we present CEO, a software-only system which we evaluate along the technical guidelines of the EvAAL competition. While the localization performance of CEO is lower with respect to most EvAAL competitors of past editions, it has the benefit of being non-intrusive, easy to install and perfectly compatible with other software systems: these characteristics would made it a potentially significant EvAAL competitor. While developing CEO, we only exploited the definition of the EvAAL competition environment as it was presented to competitors. The only inputs to CEO are the context events generated during the competition, which in 2012 and 2013 were limited to pressing light switches and using a stationary bicycle. We compare the performance of CEO against the results of those editions of EvAAL and show how it can be used to easily improve the performance of any EvAAL competitor.

Indoor localization systems that involve Wireless Sensor Networks (WSNs) identify the target position by mea- suring the Received Signal Strength (RSS), the Time of Arrival (ToA), the Time Difference of Arrival (TDoA) or the Angle of Arrival (AoA). Of these, the most promising for low-cost applications are those based on RSS measures, which exploit approximate path loss models, or more reliably the relationship between the multi-path interference (shadowing) and the target position. These methods can work with WSNs based on Wi-Fi, Bluetooth and ZigBee wireless technologies. In this paper we concentrate on device-free RSS-based indoor localization methods. These methods, which have generated much research interest in the last few years, are now starting to hit the market. Specifically, the purpose of this paper is to assess the perfor- mance improvements of a Variance-based Radio Tomographic Imaging technique, when scanning various radio channels with respect to using only one, the latter being the "minimum introduced interference" option. In our setup, the data used for target localization are captured by wireless sensors deployed in the localization area, which are in line of sight among them. The localization error metrics include the mean square error and percentiles of the error distribution.

EvAAL (Evaluating AAL Systems Through Competitive Benchmarking) is an international competition aimed at the evaluation and assessment of Ambient Assisted Living systems components, services and platforms. In 2011 took place the first edition of EvAAL on the special theme of Indoor Localization and Tracking for AAL. This paper describes the technical aspects of the first edition of EvAAL and draws a roadmap for the future editions.

Evaluation of Ambient Assisted Living (AAL) systems is particularly challenging due to the complexity of such systems and to the variety of solutions adopted and services offered. This problem is related to the evaluation of pervasive and ubiquitous systems that has been the focus of many researchers in the recent years and that still awaits for solutions. On the other hand, analyzing and comparing AAL solutions is paramount for the assessment of the research results in this area. EvAAL (Evaluating AAL Systems Through Competitive Benchmarking) is a recently established international competition that aims to address this problem in order to let benchmarking and comparison methodologies of AAL systems emerge from experience. This work describes the first EvAAL competition which was devoted to localization and tracking; proposed evaluation criteria, benchmarks, and achieved results are reported.

Localization is an essential service in many context-aware applications and in ambient assisted living (AAL). A promising localization approach is based on Wireless Sensor Networks [1]. These solutions estimate the location of the mobile sensors (also called mobiles) with respect to a set of fixed sensors (or anchors) whose position is known. In this work, we consider a range-based localization [2], that exploits measurements of Received Signal Strength Indicator (RSSI). The use of the RSSI does not require any special hardware and it is available in most of the standard wireless devices, and it has received considerable interest in the recent literature [3].