99,473 research outputs found
Challenges in Annotation of useR Data for UbiquitOUs Systems: Results from the 1st ARDUOUS Workshop
Labelling user data is a central part of the design and evaluation of
pervasive systems that aim to support the user through situation-aware
reasoning. It is essential both in designing and training the system to
recognise and reason about the situation, either through the definition of a
suitable situation model in knowledge-driven applications, or through the
preparation of training data for learning tasks in data-driven models. Hence,
the quality of annotations can have a significant impact on the performance of
the derived systems. Labelling is also vital for validating and quantifying the
performance of applications. In particular, comparative evaluations require the
production of benchmark datasets based on high-quality and consistent
annotations. With pervasive systems relying increasingly on large datasets for
designing and testing models of users' activities, the process of data
labelling is becoming a major concern for the community. In this work we
present a qualitative and quantitative analysis of the challenges associated
with annotation of user data and possible strategies towards addressing these
challenges. The analysis was based on the data gathered during the 1st
International Workshop on Annotation of useR Data for UbiquitOUs Systems
(ARDUOUS) and consisted of brainstorming as well as annotation and
questionnaire data gathered during the talks, poster session, live annotation
session, and discussion session
The Mundane Computer: Non-Technical Design Challenges Facing Ubiquitous Computing and Ambient Intelligence
Interdisciplinary collaboration, to include those who are not natural scientists, engineers and computer scientists, is inherent in the idea of ubiquitous computing, as formulated by Mark Weiser in the late 1980s and early 1990s. However, ubiquitous computing has remained largely a computer science and engineering concept, and its non-technical side remains relatively underdeveloped.
The aim of the article is, first, to clarify the kind of interdisciplinary collaboration envisaged by Weiser. Second, the difficulties of understanding the everyday and weaving ubiquitous technologies into the fabric of everyday life until they are indistinguishable from it, as conceived by Weiser, are explored. The contributions of Anne Galloway, Paul Dourish and Philip Agre to creating an understanding of everyday life relevant to the development of ubiquitous computing are discussed, focusing on the notions of performative practice, embodied interaction and contextualisation. Third, it is argued that with the shift to the notion of ambient intelligence, the larger scale socio-economic and socio-political dimensions of context become more explicit, in contrast to the focus on the smaller scale anthropological study of social (mainly workplace) practices inherent in the concept of ubiquitous computing. This can be seen in the adoption of the concept of ambient intelligence within the European Union and in the focus on rebalancing (personal) privacy protection and (state) security in the wake of 11 September 2001. Fourth, the importance of adopting a futures-oriented approach to discussing the issues arising from the notions of ubiquitous computing and ambient intelligence is stressed, while the difficulty of trying to achieve societal foresight is acknowledged
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
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