Fine-grained Humidity Sensing With Millimeter Wave Signals

Atmospheric humidity is a significantly important factor in our daily lives,as it has many important applications in many ways.Atmospheric humidity is closely bound up with meteorology and medical research,industrial and agricultural production,human health,social life and so on.Therefore,efficient and precise humidity measurement techniques are indispensable.Researchers have proposed various measurement equipments and research techniques for various types of humidity measurement.However,the existing off-the-shelf technologies of humidity measurement,including the dry and wet bulb hygrometer,humidity sensor,and detectors based on wireless networks such as ZigBee?WiFi,all have some flaws in terms of sensitiveness to respond,convenience and large-scale deployment and so on.With the development of society and the improvement of people's living standards,people are increasingly demanding the precise control of environmental humidity,making the various problems caused by these flaws more and more serious.In view of this,this paper proposes a method for detecting indoor environmental humidity using the 60 GHz millimeter wave signal and existing equipment in a specific indoor environment.The main research work of this paper mainly includes:First,we revealed that different levels of water vapor have certain significant effects on 60 GHz millimeter wave(mmWave)signals in indoor environments.Therefore,we propose a fine-grained environmental humidity sensing technology via wireless signals in the 60 GHz millimeter wave band,and we use Channel State Information(CSI)to help to research on humidity detection.Second,mmWave signals are not only sensitive to humidity,but also other environmental factors,such as oxygen.In order to eliminate the interference of other influencing factors,we use the Subspace Projection Method(SPM)to remove the noise in the environment,thus establishing a linear relationship between humidity and mmWave signal propagation.Finally,we preprocess the collected data of channel state information,then,by extracting the humidity-associated features from the denoised signal data,we use a support vectormachine(SVM)classifier to model the humidity measurement classifier of a certain place in the confined space,in order to improve the accuracy of the system's humidity detection.In order to verify the effectiveness of the proposed system,we conducted extensive experiments in different scenarios in a specific shielding room.The experimental results show that the average accuracy of the humidity measurement is as high as 85% when the humidity interval in the environment is 3% RH,,and is 95%when the humidity interval is 5% RH.We further prove that the measurement method we proposed is very sensitive to the humidity dynamics,and the response speed of this method is faster than the traditional hygrometer.