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Journal Articles Journal of Data Intelligence Year : 2021

An Approach to Develop Mobile Proxemic Applications


Traditional Human-Computer Interaction (HCI) is being overpowered by the widespread diffusion of smart and mobile devices. Currently, smart environments involve daily day activities covered by a huge variety of applications, which demand new HCI approaches. In this context, proxemic interaction, derived from the proxemic theory, becomes an influential approach to implement new kind of Mobile Human-Computer Interaction (MobileHCI) in smart environments. It is based on five proxemic dimensions: Distance, Identity, Location, Movement, and Orientation (DILMO). However, there is a lack of general and flexible tools and utilities focused on supporting the development of mobile proxemic applications. To respond to this need, we have previously proposed a framework for the design and implementation of proxemic applications for smart environments, whose devices interactions are defined in terms of DILMO dimensions. In this work, we extend this framework by integrating a Domain Specif Language (DSL) to support the designing phase. The framework also provides an API, that allows developers to simplify the process of proxemic information sensing (i.e., detection of DILMO dimensions) with mobile phones and wearable sensors. We perform an exhaustive revision of relevant and recent studies and describe in detail all components of our framework.


Other [cs.OH]
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Dates and versions

hal-03346783 , version 1 (16-09-2021)



Paulo Perez, Philippe Roose, Yudith Cardinale, Mark Dalmau, Dominique Masson, et al.. An Approach to Develop Mobile Proxemic Applications. Journal of Data Intelligence, 2021, 2 (2), pp.166-169. ⟨10.26421/JDI2.2-4⟩. ⟨hal-03346783⟩


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