Towards Collaborative Sensing using Dynamic Intelligent Virtual Sensors
The recent advent of ‘Internet of Things’ technologies is set to bring about a plethora of heterogeneous data sources to our immediate environment. In this work, we put forward a novel concept of dynamic intelligent virtual sensors (DIVS) in order to support the creation of services designed to tackle complex problems based on reasoning about various types of data. While in most of works presented in the literature virtual sensors are concerned with homogeneous data and/or static aggregation of data sources, we define DIVS to integrate heterogeneous and distributed sensors in a dynamic manner. This paper illustrates how to design and build such systems based on a smart building case study. Moreover, we propose a versatile framework that supports collaboration between DIVS, via a semantics-empowered search heuristic, aimed towards improving their performance.
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- 1.U. Bellur and R. Kulkarni. Improved matchmaking algorithm for semantic web services based on bipartite graph matching. In Proceedings of the IEEE International Conference on Web Services (ICWS), pages 86–93, 2007.Google Scholar
- 2.F. Castanedo, J. Garcia, M.A. Patricio, and J.M. Molina. A multi-agent architecture to support active fusion in a visual sensor network. In Proceedings of the Second ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), pages 1–8, Sept 2008.Google Scholar
- 3.P. Corsini, P. Masci, and A. Vecchio. Configuration and tuning of sensor network applications through virtual sensors. In Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom), pages 315–320, 2006.Google Scholar
- 4.Daniel J. Dailey and Frederick W. Cathey. Deployment of a virtual sensor system, based on transit probes in an operational traffic management system. Technical report, Washington State Transportation Center, 2006.Google Scholar
- 5.Md. Motaharul Islam, Mohammad Mehedi Hassan, Ga-Won Lee, and Eui-Nam Huh. A survey on virtualization of wireless sensor networks. Sensors, 12(2):2175–2207, 2012.Google Scholar
- 6.Ilias Leontiadis, Christos Efstratiou, Cecilia Mascolo, and Jon Crowcroft. Senshare: Transforming sensor networks into multi-application sensing infrastructures. In Proceeding of the 9th European Conference on Wireless Sensor Networks (EWSN), pages 65–81. Springer Berlin Heidelberg, 2012.Google Scholar
- 7.Lichuan Liu, S. M. Kuo, and M. Zhou. Virtual sensing techniques and their applications. In Proceedings of the International Conference on Networking, Sensing and Control, (ICNSC), pages 31–36, 2009.Google Scholar
- 8.S. Madria, V. Kumar, and R. Dalvi. Sensor cloud: A cloud of virtual sensors. IEEE Software, 31(2):70–77, 2014.Google Scholar
- 9.Massimo Paolucci, Takahiro Kawamura, Terry R. Payne, and Katia Sycara. Semantic matching of web services capabilities. In Proceedings of the First International Semantic Web Conference (ISWC), pages 333–347. Springer Berlin Heidelberg, 2002.Google Scholar
- 10.Z. Yan, V. Subbaraju, D. Chakraborty, A. Misra, and K. Aberer. Energy-efficient continuous activity recognition on mobile phones: An activity-adaptive approach. In Proceedings of the 16th International Symposium on Wearable Computers (ISWC), pages 17–24, 2012.Google Scholar