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We study how the behavior and wing-beat frequency of hymenopteran flying insects depend on environmental conditions, such as temperature and relative humidity. We use flight data from seven bee species and two wasp species collected in Brazil in a completely non-invasive way under field conditions employing a lowcost optical sensor. With this data, we demonstrate that it is possible to accurately classify each insect species into two groups based on their flight frequency signal. The signals, however, are not the same under distinct environmental conditions. We statistically show that the bee and wasp wing-beat frequencies are significantly different, given distinct temperature and humidity ranges. This study's findings, along with our discussion of the species' flight activity, are crucial elements in developing intelligent methods for automatic detection, recognition, and monitoring of flying insects.Hymenoptera / eusocial insects / insect flight / optical recognition / flight activity