In this paper we will address those related to the publication of user-generated observations.Figure 1.In-vehicle HMI system for connected cars.In this work we will also rely on the design principles proposed by the W3C’s Multimodal Architecture and Interfaces (MMI) [15]. Following these principles we will discuss the design of in-vehicle context-aware multimodal HMI systems capable of collecting selleck inhibitor driver’s information reporting observations on different road, traffic or environmental situations, and generate semantic representations of them.The rest of the paper is organized as follows: Section 2 presents related research. Section 3 describes the design of in-vehicle HMI systems to collect driver-generated observations following the principles of the W3C’s MMI architecture instantiated on an OSGi framework.
The semantic annotation of driver-generated observations and their publication in the Semantic Sensor Web are discussed in Section 4. Section 5 presents our experimental set-up, implemented on an on-board unit of a connected car. Performance analyses and a concept validation study are described in Section 6. Finally, conclusions and future work are discussed in Section 7.2.?Related WorkIn-vehicle context-aware HMI systems and the more recent conceptions of user-generated sensors or the Human Sensor Web [13,16] are two research areas closely related to the work in this paper. Recent research on context-aware HMI systems in general, and in-vehicle interactive systems in particular, has sought to ensure that they are able function in highly heterogeneous environments, adapting to all kinds of situations and contexts, always giving correct and safe feedback to their users ([17�C19]).
Information services embedded in HMI systems have to manage a common representation of the user (identifying his mood state, needs and preferences) and the contextual situation coming from a variety of heterogeneous sources. In order to integrate this data in a homogeneous manner, some approaches, such as the one presented in [20], have already made use of Semantic Web technologies to define a model of contextual information composed of several independent ontologies, mainly to represent users, devices, environment and services.In HMI vehicle scenarios, integrating both multimodal interaction and context for in-vehicle applications has also been addressed, and a common approach [19] is to consider three independent domains: driver, vehicle Entinostat and environment. However, most of the research selleck products in conte
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