Abstract

Multi-sensor array usually referred to as sensor/data fusion is one of absorbing topic in Artificial Intelligence studies. The advantages of multiple-sensor data fusion approaches in terms of cost, accuracy and reliability will be explained in this talk. Generally, “Data Fusion” deals with the synergistic combination of data provided by various knowledge sources such as sensors or information extractor, in order to provide a better understanding of a given scene or environment. The use of sensor/data fusion concept has advantages such as “Redundancy”, “Complementary”, “Timeliness” and “Less Costly Information”. Fusion characterization addressing the application domain, fusion objective, fusion process input-output (I/O) characteristics and sensor suite configuration will be shown. In this seminar the different models and levels of Data Fusion will be presented. Finally, some typical examples on applications of sensor/data

Biography

Behzad Moshiri received his B.Sc. degree in mechanical engineering from Iran University of Science and Technology (IUST) in 1984 and M.Sc. and Ph.D. degrees in control systems engineering from the University of Manchester, Institute of Science and Technology (UMIST), U.K. in 1987 and 1991 respectively. He joined the school of electrical and computer engineering, university of Tehran in 1992 where he is currently professor of control systems engineering. He has been senior member of IEEE since 2006. He is the author/co-author of more than 350 articles including 100+ journal papers and 20+ book chapters. He has been as adjunct professor of department of ECE, University of Waterloo and York University, Canada since 2004 and 2018 respectively. His fields of research include advanced industrial/process control design, advanced instrumentation system design, broad spread of applications of sensor/data fusion as well as information fusion concepts in mechatronics, robotics, process control, information technology, bioinformatics and intelligent transportation systems (ITS).