Research On Human Activity Recognition And Target Localization Algorithm Based On Mobile Terminal

With the development of intelligent mobile devices and pervasive computing,mobile terminals play a more and more important role in the fields of commercial,medical,and convenient life in daily life.Especially,the mobile terminal built-in rich sensors have showed the great use-value in human activity recognition and indoor localization,which make life more comfortable and convenient.Activity recognition via mobile sensors has been a research focus in the fields of sensor data processing and pattern recognition.In some cases,it is difficult to distinguish the similar sensor data,especially the data of walking,ascending stairs,and descending stairs,so it is a big difficulty to recognize those three activities correctly.According to the above question,in this paper,a method of activity recognition based on feature enhancement and decision fusion is proposed to recognize similar activities such as walking,ascending stairs,and descending stairs,which is implemented by enhancing a part of features and fusing several classification results.Experimental results show that the method can overcome the situation of low correct recognition rate and high recognition error due to the similarity of sensor data,which will effectively improve the correct recognition rate of human activity and distinguish human activities in actual applications in real time.As the existing indoor localization algorithm based on Dead Reckoning has the disadvantages of high cumulative error and low localization accuracy,a target localization approach based on map information and Particle Filter with position adaptive correction is proposed.The approach uses the known map information to control the birth and death of the particles during the localization process,and adaptively adjusts the positions of the compensating particles in the resampling stage according to the situation of particle degeneracy,thereby correcting the object position.The experimental results show that the proposed approach overcomes the shortcoming of cumulative error of Dead Reckoning algorithm and improves the localization accuracy.Based on the research on human activity recognition and target localization algorithms based on mobile terminal,we designed and implemented a system of activity recognition and indoor localization,which confirmed the feasibility and validity of the proposed methods.