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.

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Context Aware Computing for The Internet of Things: A Survey

Measuring Health: A Guide to Rating Scales and Questionnaires

Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behaviour accordingly. Especially in combination with mobile devices, these mechanisms are of high value and are used to increase usability tremendously. In this paper, we present common architecture principles of context-aware systems and derive a layered conceptual design framework to explain the different elements common to most context-aware architectures. Based on these design principles, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyse important aspects in context-aware computing on the basis of the presented systems.

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A survey on context-aware systems

Context-awareness is one of the drivers of the ubiquitous computing paradigm, whereas a well designed model is a key accessor to the context in any context-aware system This paper provides a survey of the the most relevant current approaches to modeling context for ubiquitous computing Numerous approaches are reviewed, classified relative to their core elements and evaluated with respect to their appropriateness for ubiquitous computing

A Context Modeling Survey

A survey of context modelling and reasoning techniques

Here we propose an OWL encoded context ontology (CONON) for modeling context in pervasive computing environments, and for supporting logic-based context reasoning. CONON provides an upper context ontology that captures general concepts about basic context, and also provides extensibility for adding domain-specific ontology in a hierarchical manner. Based on this context ontology, we have studied the use of logic reasoning to check the consistency of context information, and to reason over low-level, explicit context to derive high-level, implicit context. By giving a performance study for our prototype, we quantitatively evaluate the feasibility of logic based context reasoning for nontime-critical applications in pervasive computing environments, where we always have to deal carefully with the limitation of computational resources.

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Ontology based context modeling and reasoning using OWL

http://www-public.tem-tsp.eu/~zhang_da/pub/JNCA-gu-1.pdf

A service-oriented middleware for building context-aware services

Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware of and adapt to their changing contexts in highly dynamic environments. Today, building context-aware systems is a complex task due to lack of an appropriate infrastructure support in intelligent environments. A context-aware infrastructure requires an appropriate context model to represent, manipulate and access context information. In this paper, we propose a formal context model based on ontology using OWL to address issues including semantic context representation, context reasoning and knowledge sharing, context classification, context dependency and quality of context. The main benefit of this model is the ability to reason about various contexts. Based on our context model, we also present a Service-Oriented Context-Aware Middleware (SOCAM) architecture for building of context-aware services.

/pdf/an-ontology-based-context-model-in-intelligent-environments-4qe40w32ro.pdf

An Ontology-based Context Model in Intelligent Environments

Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware and adapt to highly dynamic environments. Today, building context-aware mobile services is a complex and time-consuming task. We present a service-oriented context-aware middleware (SOCAM) architecture for the building and rapid prototyping of context-aware mobile services. We propose an ontology-based approach to model various contexts. Our context model supports semantic representation, context reasoning and context knowledge sharing. We take a service-oriented approach to build our middleware which supports tasks including acquiring, discovering, interpreting, accessing various contexts and interoperability between different context-aware systems.

/pdf/a-middleware-for-building-context-aware-mobile-services-1vfa1wfba1.pdf

A middleware for building context-aware mobile services

Applications and services must adapt to changing contexts in dynamic environments. However, building context-aware applications is still complex and time-consuming due to inadequate infrastructure support. We propose a context-aware infrastructure for building and rapidly prototyping such applications in a smart-home environment. This OSGi-based infrastructure manages context-aware services reliably and securely and efficiently supports context acquisition, discovery, and reasoning. A formal, ontology-based context model enables semantic context representation, reasoning, and knowledge sharing. We propose an ontology-based context model that leverages Semantic Web technology and OWL (Web Ontology Language). OWL is an ontology markup language that enables context sharing and context reasoning. Based on our context model, we also propose a service-oriented context-aware middleware (SOCAM) architecture, including a set of independent services that perform context discovery, acquisition, and interpretation.

Hung Keng Pung

Papers

Ontology based context modeling and reasoning using OWL

A service-oriented middleware for building context-aware services

An Ontology-based Context Model in Intelligent Environments

A middleware for building context-aware mobile services

Toward an OSGi-based infrastructure for context-aware applications