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An analysis of distance estimation to detect proximity in social interactions

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Abstract

In the area of human behaviour analysis, smartphones are opening new possibilities where a multitude of embedded sensors can be used to regularly monitor users’ daily activities and interactions in a non-obtrusive way. In this paper we focus on proximity detection, which refers to the ability of a system to recognize the co-location of two or more individuals and infer interpersonal distances. We present Comm2Sense, our mobile platform to detect proximity among users exploiting sensing capabilities available in modern smartphones, namely Wi-Fi hotspot and Wi-Fi receiver. The platform estimates the distance between subjects applying data mining techniques to the analysis of the Wi-Fi RSSI. We describe the design and implementation of the platform, together with the technical solutions implemented in each module. We demonstrate that the proposed platform is able to achieve a resolution of 0.5 m.

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Authors and Affiliations

  1. CREATE-NET, via alla Cascata 56/D, Povo, Trento, Italy

    Venet Osmani, Iacopo Carreras, Aleksandar Matic & Piret Saar

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  1. Venet Osmani
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  2. Iacopo Carreras
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  3. Aleksandar Matic
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  4. Piret Saar
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Correspondence to Venet Osmani.

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Osmani, V., Carreras, I., Matic, A. et al. An analysis of distance estimation to detect proximity in social interactions. J Ambient Intell Human Comput 5, 297–306 (2014). https://doi.org/10.1007/s12652-012-0171-6

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  • DOI: https://doi.org/10.1007/s12652-012-0171-6

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