Opportunistic pervasive computing: adaptive context recognition and interfaces

Riboni, Daniele
Primo
2019-01-01

Abstract

Pervasive computing is promising to radically change people’s life in several dimensions, including the way we work, travel, have leisure, and take care of ourselves. In order to realize the goal, pervasive technologies must be aware of people’s context and react accordingly by tailoring services and interfaces to the current situation. Unfortunately, today’s pervasive applications have a restricted scope: their visibility is limited to their specific application domain. Hence, they are very well suited to address their specific objective, but lack the overall landscape of the user’s context and goals. In this paper, we put forward the vision of opportunistic pervasive computing: pervasive technologies that can dynamically exploit the available data sources and heterogeneous reasoning services to opportunistically reconstruct the whole landscape of the users’ context and seamlessly adapt to their needs and expectations. We point out the research challenges involved in this vision, and we present a conceptual model and architecture to address these issues, that include solutions for interoperability, reasoning integration, and artificial intelligence tools. Moreover, we introduce technical solutions for opportunistic context data discovery, reasoning and integration, as well as a hybrid method for opportunistic context-aware adaptation. We have also developed a prototype implementation considering an adaptive healthcare application for self-administration of therapies, and a system for opportunistic recognition of different activities based on sensor data. Experimental results indicate the viability and effectiveness of our solution.
2019
Inglese
1
2
125
139
15
Esperti anonimi
scientifica
no
Riboni, Daniele
1.1 Articolo in rivista
info:eu-repo/semantics/article
1 Contributo su Rivista::1.1 Articolo in rivista
262
1
reserved
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