SILs-ICSV dataset(video data)

Citation Author(s):
zitian
Jiang
Submitted by:
zitian Jiang
Last updated:
Tue, 01/09/2024 - 06:49
DOI:
10.21227/yz4m-b684
License:
0
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Abstract 

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.

Instructions: 

This is an additional supplement to the raw data on insecticide counts, which includes video data from six solar insecticidal lamp IoT nodes, a total of 256 hours; the video is collected and saved at 1-minute intervals so as to facilitate scholars in the relevant fields to understand the insecticide counts better, the collated dataset can be found at https://ieee-dataport.org/documents/ solar-insecticidal-lamp-insecticidal-discharge-sound-and-discharge-voltage-dataset