Intelligent processing of experimental data in ISES remote laboratory

Abstract

The paper deals with the design of the intelligent processing of experimental data measured in the remote laboratories, where the measurements are performed by connected clients via the finite-state machine residing at an advanced server. As physical hardware and software is used the Internet School Experimental System (ISES). This platform is intended for educational purposes at schools and universities to provide the suitable measuring environment for students using computers. It is especially suitable for distance students who cannot attend regular courses during their studies of physics, chemistry or electro-engineering. At present, the remote laboratory does not have any data processing technique. This results in excessive demands on storing capacity. The suggested solution solves this drawback by processing and archiving techniques to store measured data after their organizing in predetermined structures and concomitant data volume reduction. The paper is organized in the following manner. In the first section, Introduction, the ISES remote laboratory concept is introduced, following, State of the art, describing present stage of its ISES physical hardware development. The description of ISES physical software is concentrated at the Measureserver core unit realized as the finite-state machine. The next section deals with the design and implementation of the intelligent data processing component, which is focused on the extracting, filtering and archiving of measured data coming from the Measureserver unit communicating with a physical experiment. Finally, all the functional benefits are summarized for interested, who are involved in the remote experiments construction.