By Emile Aarts, Boris de Ruyter, Panos Markopoulos, Evert van Loenen, Reiner Wichert, Ben Schouten, Jacques Terken, Rob Van Kranenburg, Elke Den Ouden, Gregory O'Hare
This booklet constitutes the refereed court cases of the fifth overseas Joint convention of Ambient Intelligence, AmI 2014, held in Eindhoven, The Netherlands, in November 2014. The 21 revised complete papers awarded including five brief papers and four workshop papers have been conscientiously reviewed and chosen from fifty nine submissions. The papers are geared up alongside a suite of thematic tracks: ambient assisted residing; web of items; ambient play and studying; clever structures and towns; clever riding; information technology; clever healthcare and therapeutic environments; ambient persuasion; and new and rising themes.
Read Online or Download Ambient Intelligence: European Conference, AmI 2014, Eindhoven, The Netherlands, November 11-13, 2014. Revised Selected Papers PDF
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Additional info for Ambient Intelligence: European Conference, AmI 2014, Eindhoven, The Netherlands, November 11-13, 2014. Revised Selected Papers
F (e) = P ( ≤ e) (2) Figure 5 shows the CDFs of the localization error using the EvAAL 2013 localization systems, with and without the proposed SALT overlay. Figure 5a shows the localization performance of the ﬁrst place ranking of the competition, the REALTrack system, with and without the SALT overlay. 5m of error without the SALT overlay. The same trend can be seen for the other ﬁve competitors (subﬁgures from 5b to 5f). However, for two of the competitor, LOCOSmotion (Figure 5b) and AmbiTrack (Figure 5c), the increase in performance is not as evident as in other competitors.
16] Stopczynski et al.  Data sources Type Wi-Fi user-centric Wi-Fi, accelerometers,pressure sensors Wi-Fi Accelerometer,Wi-Fi Bluetooth,call logs,cell towers,application usage,phone status call logs, cell towers,Bluetooth Bluetooth,Wi-Fi Bluetooth, Wi-Fi social inference social inference Bluetooth social inference Digg,Twitter Simulated Wi-Fi Bluetooth diﬀerent datasets Bluetooth,location,voice calls,text messages Questionnaires,Facebook,Phone sensors user-centric multi-user multi-user social inference social inference social social social social inference inference inference inference social inference social inferecne Detecting Walking in Synchrony Through Smartphone Accelerometer 3 37 Methodology In this section we describe the details of the data collection process, pre-processing steps and ﬁnally the accelerometer and Wi-Fi data analysis.
The paper is organized as follows: Section 2 surveys related work into indoor localization area, Section 3 depicts the details of our solution, Section 4 provides both the description of the living lab hosting the EvAAL’13 competition, the binary sensor network on which leverages SALT, and the localization systems presented at EvAAL’13 that will be used to evaluate the proposed technique. Section 5 shows the performance of the proposed approach, while concluding remarks are presented in Section 6.