2006 - Algorithm for Noise-Data Reduction for Long-Term EMF Monitoring Systems
H. Haider, A. Nöhrer, G. Neubauer
4th International Workshop on Biological Effects of Electromagnetic Fields, Kreta, Greek, 16.-20. October 2006, NCSR "Demokritos"
In addition to present popular ‘in situ’ EMF-measurements performed at critical locations like schools, hospitals or in front of base stations for one-time, long-term evaluations of RF-fields become more and more essential. This is especially because of the continuously increasing number of new applied technologies and even more emitting base stations. To perform such long-term investigation, fully automatic, stand alone EMF-monitoring stations are suited very well. Typically, several of such stations are connected to one environmental network, fully remote controlled by one server. To yield maximum of information, each station is continuously in operation, performing frequency selective measurements and generating an enormous amount of measurement data. The data communication often represents the bottleneck of such systems and therefore the reduction of these data becomes very essential. By implementing an intelligent algorithm for data reduction directly on the measurement station this problem could be reduced. Therefore we will provide in this paper a methodology suited for a considerable reduction of noise points without loosing any relevant signal information. The specific nature of this algorithm and his efficiency in data reduction will be discussed and explained, including how it works and what parameters are needed. The results which can be achieved with this technique are demonstrated with the existing monitoring system ‘Field Nose’ from ARC Seibersdorf research.