Towards Context-Aware Data Management for Ambient Intelligence

Abstract

Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service support, with an aim to make people's daily activities more convenient, thus improving the quality of human life. To make AmI real, effective data management support is indispensable. High-quality information must be available to any user, anytime, anywhere, and on any lightweight device. Beyond that, AmI also raises many new challenges related to context-awareness and natural user interaction, entailing us to rethink current database techniques. The aim of this paper is to address the impact of AmI, particularly its user-centric context-awareness requirement on data management strategies and solutions. We first provide a multidimensional view of database access context. Taking diverse contextual information into account, we then present five context-aware data management strategies, using the most fundamental database operation-context-aware query request as a case in point. We execute the proposed strategies via a two-layered infrastructure, consisting of public data manager (s) and a private data manager. Detailed steps of processing a context-aware query are also described in the paper.

Context-aware assessment in out-of-classroom activities by means of mobile technologies

“…The type of data to be collected will most likely fall into one of these categories (as proposed by Feng et al, 2004):…”

Models, AmI-Creator and A-Methodology for Ambient Intelligence Environments

“…They include such notions as Ubiquitous/Pervasive/Proactive/Ambient Computing, Calm Technology and Smart Environments [7]. The interpretations and visions refer to "multidisciplinary paradigm" [8] and "vision of future Information Society" [9].…”

Ao Dai: Agent Oriented Design for Ambient Intelligence

“…If many authors consider context as merely a set of sensed values [1,7], a particularly interesting approach to context-awareness is taken by Henricksen et al [8,9], that model context as associations between entities or between entities and attributes, where an entity can be a person, a place, a communication device, etc. These associations can be of different types: static -associations that remain fixed for the lifetime of the entity; dynamic and sensed -obtained from sensors, usually transformed afterwards, changing frequently and subject to sensing errors; dynamic and derived -information that is inferred, usually from sensed or static associations; dynamic and profiled -introduced explicitly by the user, leading to greater reliability, but also subject to staleness.…”