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 wel...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.展开更多
基金The financial support provided by the Cooperative Education Fund of China Ministry of Education(201702113002,201801193119)the Scientific Research Fund of Hunan Provincial Education Department(20A191)the National Natural Science Foundation of China under Grant(61702180)are greatly appreciated by the authors.
文摘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.
