Out-of-the-Lab Pervasive Computing

Authors: Alt, F., Kostakos, V., Oliver, N.

External link: https://ieeexplore.ieee.org/abstract/document/9734290
Publication: IEEE Pervasive Computing Journal , 21(1) p. 7-8, 2022
PDF: Click here for the PDF paper

The radical societal changes we are witnessing as a result of COVID-19 are giving rise to not only new challenges but also new opportunities for pervasive computing and its researchers. As social distancing measures are making it harder to conduct lab-based user studies and in-person observations, researchers are now faced with the challenge of designing and conducting studies remotely. Many examples of out-of-the-lab research exist from the time before COVID-19, in particular, leveraging pervasive technologies, such as mobile phones and smartphones, public displays, smart watches, smart glasses, and VR glasses, to just name a few examples.

Yet, the past two years witnessed pervasive computing technology having become an enabler for such remote research also in other areas: an ever-increasing number of disciplines and application domains now embrace these opportunities of pervasive computing, including but not limited to education, health, housing, transportation, work, and entertainment.

Early community efforts to deal with research challenges imposed by COVID-19 included running online talk shows and courses at conferences as well as sharing best practices and approaches. Since then, the community has seen many research examples, where concepts for novel approaches to out-of-the lab research were created, implemented, tested, and applied. The aim of this special issue is to surface such novel approaches to and examples of out-of-the-lab pervasive computing. The accepted articles address a variety of topics, ranging from adapting multidevice deployments during a pandemic, tackling challenges that emerge when doing out-of-the-lab research (such as data labeling), collecting reliable human behavioral and emotional data, achieving zero-touch pervasive computing, relying on crowd sensing for living lab experimentation, or leveraging ubiquitous technology to support research with chronic disease patients.

Partially funded by the Generalitat Valenciana Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital and the European Union European Regional Development Fund