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T26 Multisensor Data Fusion in Wireless Sensor and Actuator Networks - Withdrawn

Length: 3 hours

Intended Audience: People who can benefit from this tutorial are e.g. researchers, system designers and developers from industry and academia working in the following areas: Information fusion in general, Wireless sensor networks, Internet of Things and decision support tools.

Description: This tutorial focuses on presenting Multisensor Data Fusion Techniques for Wireless Sensor and Actuator networks. Advances in microelectromechanical systems technologies and wireless communications have enabled the construction of devices, called sensors, endowed with processing and communication capabilities, used to monitor physical quantities in an environment. Due to their small size and low production cost, tens, hundreds or thousands of such sensor nodes, powered by batteries, can be connected together to create a Wireless Sensor Network (WSN). Recent years have witnessed the emergence of the Shared/ Virtual Sensor and Actuator Networks, which instead of assuming an application-specific design, allow the sensing and communication infrastructure to be shared among multiple applications. With an increasing number of sharing applications, a growing amount of sensor-generated data will be produced, from which useful information can be extracted. However, wireless sensors and actuators commonly rely on batteries as their energy sources, whose replacement is undesirable or unfeasible. Therefore, in order to reduce the amount of data to be transmitted in the wireless channel, thus saving energy, Multisensor Data Fusion Methods (MDF) can be employed. During this tutorial, we will implement data fusion techniques on sensors using a web ide platform called COMFIT ( COMFIT is a webIDE for wireless sensor network developed by the presenter’s group. The participants will have access to the presentation material and source code produced.

Prerequisites: General familiarity with probabilistic concepts such as random variables, probability distributions, density functions, conditional probabilities, and expectations.

Presenter: Claudio Miceli de Farias

Claudio Miceli de Farias received a M.Sc. degree on Computer Science in 2010 and his doctorate degree in 2014 from the Federal University of Rio de Janeiro, Brazil. He is nowadays professor at the Tercio Pacitti Institute for Applications and Computational Research. He coordinates undergrad activities in this institute. He is also reviewer of several Journals such as computer networks, IEEE sensors and computer communications. He is the author of COMFIT – a webide for wireless sensor networks (formerly known as web2compile) His research interests include nanonets, wireless sensor networks, network security, Information Fusion, Bayesian Networks and Game Theory.

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