Design of Intelligent Mosquito Nets Based on Deep Learning Algorithms

An intelligent mosquito net employing deep learning has been one of the hotspots in the field of Internet of Things as it can reduce significantly the spread of pathogens carried by mosquitoes, and help people live well in mosquito-infested areas. In this study, we propose an intelligent mosquito ne...

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Bibliographic Details
Published inComputers, materials & continua Vol. 69; no. 2; pp. 2261 - 2276
Main Authors Liu, Yuzhen, Wang, Xiaoliang, She, Xinghui, Yi, Ming, Li, Yuelong, Jiang, Frank
Format Journal Article
LanguageEnglish
Published Henderson Tech Science Press 2021
Subjects
Algorithms
Artificial neural networks
Data collection
Decision making
Deep learning
Feature extraction
Flow mapping
Infrared detectors
Internet of Things
Machine learning
Medical research
Mosquitoes
Optical flow (image analysis)
Perception
Pressure sensors
Sensor arrays
Sensors
Three dimensional models
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Summary:An intelligent mosquito net employing deep learning has been one of the hotspots in the field of Internet of Things as it can reduce significantly the spread of pathogens carried by mosquitoes, and help people live well in mosquito-infested areas. In this study, we propose an intelligent mosquito net that can produce and transmit data through the Internet of Medical Things. In our method, decision-making is controlled by a deep learning model, and the proposed method uses infrared sensors and an array of pressure sensors to collect data. Moreover the ZigBee protocol is used to transmit the pressure map which is formed by pressure sensors with the deep learning perception model, determining automatically the intention of the user to open or close the mosquito net. We used optical flow to extract pressure map features, and they were fed to a 3-dimensional convolutional neural network (3D-CNN) classification model subsequently. We achieved the expected results using a nested cross-validation method to evaluate our model. Deep learning has better adaptability than the traditional methods and also has better anti-interference by the different bodies of users. This research has the potential to be used in intelligent medical protection and large-scale sensor array perception of the environment.
ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2021.015501