Applications of Wavelet Transform and Artificial Neural Networks to Pattern Recognition for Environmental Monitoring

Abstract

In this paper, using an automatic tracking system, behavior of an aquatic insect, Chironomus sp. (Chironomidae), was observed in semi-natural conditions in response to sub-lethal treatment of a carbamate insecticide, carbofuran. The fourth instar larvae were placed in an observation cage (6cm × 7cm × 2.5cm) at temperature of 18°C and the light condition of 10(light): 14(dark). The tracking system was devised to detect the instant, partial movement of the insect body. Individual movement was traced after the treatment of carbofuran (0.1mg/l) for four days (2 days : before treatment, 2 days: after treatment). Along with the other irregular behaviors, ventilation activity, appearing as a shape of compressed zig-zag, was more frequently observed after the treatment of the insecticide. The activity of the test individuals was also generally depressed after the chemical treatment. The Wavelet analysis was implemented on the data of the locomotive tracks, and the method was effective for characterizing the response behavior patterns of the organisms treated with the insecticide. This computational patterning could be an alternative tool for automatically detecting presence of insecticides in environment.