Abstract: In the last years sensor networks have proved their huge viability in the real world, even if their resources in terms of energy, memory, computational power and bandwidth are strictly limited. One of the important problems related to the usage of wireless sensor networks in harsh environments is the identification of the states of the physical variables in the field based on the measurements provided by the sensors. The sensor networks allow the usage of the multivariable estimation techniques in distributed systems. The paper presents a short survey of some identification techniques and some characteristics of the sensor networks. Some examples of applications of modeling of distributed systems in sensor networks and identification based on multivariable identification with auto-regression and neural networks are presented.

Brief Biography of the Speaker:
Constantin Volosencu graduated in 1981 “Traian Vuia” Polytechnic Institute of Timisoara, as an engineer in automatics and computers. He is doctor in control systems from 2000, and Professor since February 25, 2008. He has interests in linear control systems, fuzzy control, neural networks, control of electrical drives, modeling, identification and simulation and sensor networks. He is the author of 9 books, over 80 papers published in journals and conference proceedings, manager of over 30 research projects. Constantin Volosencu worked for 9 years in the mechanical industry, were he developed control equipments for a large scale of machineries, which are the objects of 27 patents.