Environmental information systems in Slovenia—the present and future state

Industrial air pollution is still one of the biggest environmental problems in Slovenia. To monitor air pollution, automated environmental information systems were built. These are complex computerized networks that couple automated measuring techniques and information technology. A typical environmental information system is described. Guidelines are given for the strategy of air pollution monitoring in complex terrain, attempting to find a balance between costs, the available funds and system performances desired. In the paper a strategy for achieving desired system performances is described. The most important parameters are measuring accuracy, reliability and maintenance simplicity. In complex terrain an environmental information system cannot cover the whole domain. Appropriate dispersion models should be added to the system to reconstruct the whole movement of the pollutant plume and to estimate its harmful effects in regions without measurements

Ozone prediction based on neural networks and Gaussian processes

The urban environment in Slovenia is confronted with the air pollution problem of harmfully high ozone concentrations. In the last two decades the automatic ozone measuring network was extended and now covers regions where the highest values are expected. Due to topographical and climatological conditions and the presence of extensive urban environments, the most critical locations are the ones in the western part of Slovenia. In the city of Nova Gorica a modern automatic urban air pollution measuring station was installed. Measurements at this station clearly showed that ozone is a considerable pollutant there, especially in the summer time. In this work a perceptron neural-network–based model and a Gaussian-process–based model for ozone concentration forecasting for the city of Nova Gorica was developed and evaluated. The methods of feature determination and pattern selection for the model training process are delineated. The shortcomings of the models and possibilities for improvements are discussed with respect to evaluation of the effectiveness of the methods

Karst show caves : How DTN technology as used in space assists automatic environmental monitoring and tourist protection - experiment in Postojna cave

The paper presents an experiment demonstrating a novel and successful application of delay- and disruption-tolerant networking (DTN) technology for automatic data transfer in a karst cave early warning and measuring system. The experiment took place inside the Postojna Cave in Slovenia, which is open to tourists. Several automatic meteorological measuring stations are set up inside the cave, as an adjunct to the surveillance infrastructure; the regular data transfer provided by the DTN technology allows the surveillance system to take on the role of an early warning system (EWS). One of the stations is set up alongside the railway tracks, which allows the tourist to travel inside the cave by train. The experiment was carried out by placing a DTN "data mule" (a DTN-enabled computer with WiFi connection) on the train and by upgrading the meteorological station with a DTN-enabled WiFi transmission system. When the data mule is in the wireless drive-by mode, it collects measurement data from the station over a period of several seconds as the train without stopping passes the stationary equipment, and delivers data at the final train station by the cave entrance. This paper describes an overview of the experimental equipment and organization allowing the use of a DTN system for data collection and an EWS inside karst caves where there is regular traffic of tourists and researchers.Validerad; 2014; 20140210 (maud)</p