Presentation - Supporting Situation-awareness in Smart Spaces

Computer Science and Information Systems, 2016

A smart home provides automated services based on the context of the home environment and user activity. Context acquiring, processing, reasoning, and disseminating to the services are complex tasks for a context-aware system. An appropriate middleware architecture could handle such complexity. In this paper, we proposed a middleware architecture for a context-aware system in smart home environment. Here, the context is modeled based on ontology using Web Ontology Language (OWL). In addition, a profile applied improved rule-based reasoning algorithm is integrated into this middleware to infer high-level contexts from available low-level contexts. Experimental result shows that the middleware provides more accurate and faster reasoning outcome compare with the traditional rule-based reasoning method. Moreover, context-aware service is also selected using the rule-based algorithm, where the service can be extended easily by adding new service rules in the service rule base.

2005

Context-aware computing is about gathering user information and their environment such as user location and preferences, service status, and nearby devices. Such context information is used to adjust enviroment settings to suit user needs and preferences. As environments can change rapidly, applications must be aware of it and adapt their behaviour in real time. We describe an application that introduces intelligent agents in smart homes to provide location-aware services and interfaces. This application must keep an eye on some context information to carry out user preferences. Our approach is based on a contextual ontology that is a key component to enable context sharing and representation.

Ubiquitous Computing is moving the interaction away from the human-computer paradigm and towards the creation of smart environments that users and things, from the IoT perspective, interact with. User modeling and adaptation is consistently present having the human user as a constant but pervasive interaction introduces the need for context incorporation towards context-aware smart environments. The current article discusses both aspects of the user modeling and adaptation as well as context awareness and incorporation into the smart home domain. Users are modeled as fuzzy personas and these models are semantically related. Context information is collected via sensors and corresponds to various aspects of the pervasive interaction such as temperature and humidity, but also smart city sensors and services. This context information enhances the smart home environment via the incorporation of user defined home rules. Semantic Web technologies support the knowledge representation of this ecosystem while the overall architecture has been experimentally verified using input from the SmartSantander smart city and applying it to the SandS smart home within FIRE and FIWARE frameworks.

International Journal of Smart Home, 2017

To realize smart home services, several context-aware applications should be deployed which adapt their behavior depend on context information of home occupants. For context-aware service, context providing, processing, reasoning, delivery and designing context-aware applications are complex tasks. Although every application uses its registered contexts to provide services but some of the contexts are common for different services. So, it is wise to compute contexts at once and distribute to each application cooperatively rather than compute the same context for different application separately. Here the context reusable mechanism can significantly reduce the context computing cost. For this purpose, middleware-based implementation is a good alternative. Middleware uses raw data through sensors then generates context using these data, and finally conveys context to applications. In this paper, we present a context-aware middleware which provides above tasks and supports context sharing in cooperative manner. Context reasoning is an important task in context-aware systems. A formal context model based on ontology can play a vital role in facilitating reasoning by formally representing domain knowledge. We model domain context using ontology and adopt FOL which helps the context reasoning.

Smart Spaces and Next …, 2011

This paper presents an approach for developing contextaware intelligent applications for Smart Space-based infrastructure. The goal is to model and process context information using our development tool and Nokia's Smart-M3 architecture. We propose an adaptable and scalable context ontology, an ambient computing framework based on Smart Spaces and a rule based reasoning to infer high level context. Our approach deals with key issues in context aware ubiquitous computing such as adaptive and proactive changes in the environment, incorporation of novel sources of context information and automatic code generation from the context ontology to provide seamless interoperability.

2006 International Conference on Hybrid Information Technology, 2006

Smart Home environments aim to integrate physical devices, human beings and computing entities in homes and buildings. They have to support characteristics coming from mobile computing, ubiquitous computing and sensor networking in order to provide intelligent, context-aware and pro-active applications. In this vision, "context" plays a central role; but, the raw context data, obtained by various data sources, are represented in heterogeneous formats and thus it's not possible to understand their meanings without a prior knowledge of the particular context information model. Therefore, data sources are not able to produce high-level context information, but provide only raw information. Such low-level information should be combined in order to generate higher-level context information. In this paper we propose a Semantic Context Service, that exploits Semantic Web technologies to support Smart Offices. In particular, this service relies on ontologies and rules to classify several typologies of entities, which can be involved in smart homes and offices, and to infer higher-level context information from low-level information coming from positioning systems and sensors in the physical environments.

2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems, 2012

Nowadays, activity recognition has been proposed in several researches. It is attractive to improve the ability of the activity recognition system because existing research on activity recognition systems still have an error in an ambiguous cases. In this paper, we introduce the novel technique to improve the activity recognition system in smart home domain. We propose the three contributions in this research. Firstly, we design the context-aware infrastructure ontology for modelling the user's context in the smart home. The innovative data, human posture, is added into the user's context for reducing the ambiguous cases. Secondly, we propose the concepts to distinguish the activities by object-based and location-based concepts. We also present the description logic (DL) rules for making the human activity decision based on our proposed concepts. Lastly, We conduct the Ontology Based Activity Recognition (OBAR) system for two purposes: to recognize the human activity, and to search the semantic information in the system, called semantic ontology search (SOS) system. The results show the system can recognize the human activity correctly and also reduce the ambiguous case.

2010

Any of our living environments can form a smart space that provides services and applications for the users according to their situations, the computing and communication facilities of the environment and the surroundings of the user. The ability to take into account the context of the user, and the digital and physical environment makes a space smart. This paper introduces a set of new capabilities that are required for achieving context-awareness in smart spaces. First, sensor data from the environment is acquired and aggregated. Second, the context data is interpreted and represented and possibly enhanced with external information. Thereafter, context reasoning is possible. Finally, situation based context reasoning is made by application agents that exploit domain ontologies for tuning context information to the situation in hand. The use of the introduced context-awareness concept is exemplified by an emergency scenario of a smart city.

The current paper provides an overview on how user modeling, context awareness and content adaptation in Smart Home environments may be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriate feedback provided by the user. The authors will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally, the authors will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

Proceedings of 2012 4th IADIS International Conference on e-Health

Smart homes are expected to provide better services to inhabitants, supporting independence especially to elderly people in living their lives. Home automation system plays an important role in supporting the well-being of inhabitants, reducing necessary human interventions in achieving different tasks. Sensors, actuators, and various devices are required to be installed in smart homes to provision context-aware services. This paper presents a home integration platform architecture based on Service-Oriented Architecture paradigm that can be used to integrate the functionalities of different devices. A proposed ontology to enhance the automated reasoning process is also presented, and several example scenarios related to safety and security at home utilising the Semantic Web Rule Language rules are described as well.