The Semantic Web of Things (SWoT) is an emerging vision in Information and Communication Technology (ICT), joining together some of the most important paradigms of the decade: the Semantic Web and the Internet of Things.
The Semantic Web initiative [1] aims at allowing available information in the World Wide Web to be seamlessly shared, reused and combined by software agents. Each available resource in the semantic-enabled Web should be properly described in order to infer new information from the one stated in the semantically annotated resource descriptions.
The Internet of Things vision [2] promotes on a global scale the ubiquitous computing paradigm. In ubiquitous and pervasive contexts, intelligence is embedded into objects and physical locations by means of a large number of heterogeneous micro-devices, such as RFID tags or sensors, each conveying a small amount of information. Due to space, power and cost constraints, devices are usually endowed with very low storage, little or no processing capabilities and short-range, low-throughput wireless links allowing only a simple service/resource fruition.
Ideas and technologies borrowed from the Semantic Web vision may allow to overcome these limitations. In fact the SWoT vision enables knowledge-based systems that achieve high degrees of autonomic capability for information storage, management and discovery, also providing transparent access to information sources in a given area.
References:
- T. Berners-Lee, J. Hendler, O. Lassila, The semantic Web, Scientific American 284 (5) (2001) 28-37.
- ITU, Internet Reports 2005: The Internet of Things (November 2005).
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Due to architectural and performance reasons, it is currently unfeasible or impractical to use available Semantic Web reasoners in the Semantic Web of Things.
Therefore we are developing a prototypical mobile reasoner for the SWoT.
It supports standard Semantic Web technologies through the <OWL API and implements both standard reasoning tasks for knowledge base (KB)
management (subsumption, classification, satisfiability) and non-standard inference services for semantic-based matchmaking and
resource ranking (abduction and contraction).
Mini-ME is developed in Java, adopting Android as the current target computing platform, but running also on Java SE.
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iDriveSafe 1.0 is a mobile Apple iPhone application for semantic-enhanced real-time car diagnostics and driving assistance.
The system is able to identify specific high-level events and conditions, based on low-level data streams such as
vehicle health and safety equipments; environmental factors and driving style. Exploiting Semantic Web techniques and
technologies, events are semantically annotated w.r.t. an ontology modeling factors influencing driving safety.
Annotated descriptions undergo a semantic matchmaking process which is able to discover all possible risk factors.
The matchmaking outcome is used to suggest the driver actions and behaviors she can adopt in order to minimize risks.
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iDriveSafe 2.0 is an evolution of the first version that supports also the measurement of exhaust emissions,
fuel consumption and autonomy and engine load. The system is able to evaluate driving performance, environmental impact and risk level,
and to suggest users how to reduce or even eliminate danger by exploiting a semantic-based matchmaking. Improvements have been performed
in the design of the user interface that is now formed by a set of coloured icons. Each icon changes her colour depending on
the semantic matchmaking results and emits an acoustic signal to inform drivers.
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Home and Building Automation (HBA) is a growing research and industrial sector attracting efforts from several disciplines, coalescing into a research area known as Ambient Intelligence (AmI). The integration of knowledge representation languages and reasoning techniques (originally devised for the Semantic Web) into standard home automation protocols can allow to offer high-level services to users and to adapt the environment dynamically and automatically to varying conditions, overcoming limitations of current implementations based on preset conditions. Exploiting semantic-based matchmaking, the user profile can be compared with house configuration (which includes devices settings and appliances behavior), so identifying the home features best fitting user needs. Furthermore, household equipments are autonomously able to reach the status better satisfying users' activities or device requirements.
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We are currently developing a prototypical software tool for editing semantic-based annotations of OpenStreetMap points of interest (POIs), through a fully visual user interface based on simple drag-and-drop operations. We chose to extend the open source JOSM (Java OpenStreetMap editor) application.
Thanks to an easily understandable GUI, our tool can make any OpenStreetMap contributor capable of enriching maps along the Semantic Web / Linked Open Data vision. No specific knowledge of Semantic Web languages and underlying logic-based formalisms is required.
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Contacts
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