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Open AccessArticle

A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats

1
Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Korea
2
Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Korea
3
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Korea
4
School of Electrical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Daejeon 34141, Korea
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2019, 19(12), 2785; https://doi.org/10.3390/s19122785
Received: 9 April 2019 / Revised: 16 June 2019 / Accepted: 18 June 2019 / Published: 21 June 2019
(This article belongs to the Section Intelligent Sensors)
Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the preliminary results of an automated system that detects the presence of mosquitoes via image processing using multiple deep learning networks. The Fully Convolutional Network (FCN) and neural network-based regression demonstrated an accuracy of 84%. Meanwhile, the single image classifier demonstrated an accuracy of only 52%. The overall processing time also decreased from 4.64 to 2.47 s compared to the conventional classifying network. After detection, a larvicide made from toxic protein crystals of the Bacillus thuringiensis serotype israelensis bacteria was injected into static water to stop the proliferation of mosquitoes. This system demonstrates a higher efficiency than hunting adult mosquitos while avoiding damage to other insects. View Full-Text
Keywords: mosquito; vector control; deep learning; urban habitat; drug spray mosquito; vector control; deep learning; urban habitat; drug spray
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MDPI and ACS Style

Kim, K.; Hyun, J.; Kim, H.; Lim, H.; Myung, H. A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats. Sensors 2019, 19, 2785.

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