Solar insecticidal lamp insecticidal discharge sound and discharge voltage dataset

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zitian Jiang
Last updated:
Mon, 12/04/2023 - 20:03
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Solar insecticidal lamps are only a kind of green, low-carbon, non-polluting physical plant protection equipment that can effectively eliminate phototropic pests. In addition, the insecticidal lamp's statistics of pest population density is an essential task. Determining the population density of the farmland area is vital to the precise application of medicine. The insecticidal lamp will kill the number of pests each night as a measure of the population density of the farmland area indicators. Existing insecticidal counting methods are based on voltage counting, but voltage counting is prone to repeat counting; to solve the problem, we propose to use the raw sound data when the insecticidal is discharged to analyze the insecticidal counting methods, which can significantly reduce the repeat counting data. In addition, the simultaneous voltage pulse data and insecticidal discharge sound machine learning can improve the robustness of its method, which is suitable for application on top of solar insecticidal lamps.


This dataset is used to count the number of pests killed by the sun killer lamp; the data are the discharge sound and discharge voltage pulse when killing pests; the sound and voltage data correspond one to one, and each data is collected according to 5s, there are 4000 pieces of data in total. These 4000 data are divided into four categories: killing one pest, killing two pests, killing three pests, and killing four pests, with 1000 data for each type.



This is supplementary data(SILs-ICSV dataset(video data)); the subsequent author of the compilation of the recorded video data of the solar insecticide lamp insecticide count, which includes five sub-files, each sub-file inside the video data collected by different nodes 8 hours a day; the video is saved for one minute of automatic storage, the format of the video is mp4, a total of 256 hours.This data can be found at

Submitted by zitian Jiang on Tue, 01/09/2024 - 06:55