By Amr Mohamed, Paulo Novais, António Pereira, Gabriel Villarrubia González, Antonio Fernández-Caballero
This quantity includes the complaints of the 6th overseas Symposium on Ambient Intelligence (ISAmI 2015), held in Salamanca, Spain on June 3th-5th on the college of Salamanca. After a cautious assessment, 27 papers from 10 various nations have been chosen to be offered in ISAmI 2015 on the convention and released within the proceedings.
ISAmI has been operating each year and aiming to compile researchers from a variety of disciplines that represent the medical box of Ambient Intelligence to provide and speak about the most recent effects, new principles, tasks and classes discovered, particularly by way of software program and purposes and goals to compile researchers from numerous disciplines which are attracted to all facets of this area.
Ambient Intelligence is a contemporary paradigm rising from man made Intelligence, the place pcs are used as proactive instruments supporting individuals with their daily actions, making everyone’s existence more well-off. one other major situation of AmI originates from the human laptop interplay area and specializes in delivering how you can have interaction with structures in a extra ordinary manner by way of skill consumer pleasant interfaces. This box is evolving quick as could be witnessed by means of the rising common language and gesture dependent kinds of interaction.
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Additional info for Ambient Intelligence - Software and Applications: 6th International Symposium on Ambient Intelligence (ISAmI 2015)
C. Wu, Y. Liu, Queuing network modeling of driver workload and performance. IEEE Trans. Intell. Transp. Syst. ) 3. M. Itoh, E. Kawakita, K. Oguri, Real-time estimation of driver’s mental workload using physiological indexes, in Proceedings of ITS World Congress (2010) pp. 1–11 4. Teh, S. Jamson, O. Carsten, How does a lane change performed by a neighboring vehicle affect driver workload? in Proceedings of ITS World Congress (2012), pp. 1–8 5. S. Sega, H. Iwasaki, Veriﬁcation of driving workload using vehicle signal data for distractionminimized systems on ITS, in Proceedings of ITS World Congress (2011), pp 1–12 6.
G. source and quality-of-context - QoC metrics) and context integrity, uniqueness or value constraints. 8 and ts=2015-06-03 12:00:00 are ContextAnnotations characterizing the accuracy and timestamp of the location statement. The context model is leveraged at runtime by the CONSERT Engine, which handles context updates, higher-level inference, constraint and consistency checking, as well as asynchronous query answering. The engine inference mechanism performs semantic event processing, employing a rule-based derivation approach using SPARQL CONSTRUCT queries coupled with ontology reasoning.
The tests were performed in Madrid between the months of November 2014 to January 2015. The selected routes (A and B) has both parts of urban road and a highway. All tests were made under similar conditions (time, trafﬁc, and weather). 0 HDI. Drivers were divided into two groups: X and Y. Each group completed a different route (A, B). The experiment consisted of two phases. In the ﬁrst phase, drivers completed the route 4 times without the use of shared database. At this stage the aim was only to discover areas where stress and fuel consumption is high.