Research And System Design Of Human Posture Recognition Based On Wearable Device

In recent years,with the development of microelectronics and computer technology,the craft of wearable devices has been improved,and cloud computing service providers are gradually able to provide corresponding computing resources.Wearable devices have the advantages of small size,easy portability,simple operation,and no restrictions on location.With the aging of the population and the increasing concern for people's health,human posture recognition based on wearable device is becoming an indispensable part of medical surveillance and personal health.According to the related research,this paper proposes a general scheme of human posture recognition based on wearable device,studies the data preprocessing methods and recognition methods in the field of human posture recognition.Respectively using SVM-KNN,AdaBoostRandom Forest and neural network based algorithm construct the classifier to identify the human posture.The experiment shows that SVM-KNN algorithm achieves better recognition results.In addition,based on the human posture recognition algorithm,this paper proposes a design scheme of human posture recognition system.The system is designed separately from both hardware and software.The IMU in the wearable device is used to collect the human motion data,and uses Bluetooth Low Energy as the data transfer protocol between wearable device and smartphone.The server provides computing resources in the form of cloud computing,and uses micro-services architecture to decouple the various business logics of the system.Combined with the idea of container service,the container orchestration technology is used for automating deployment of containerized applications,which enhances the scalability and management capabilities of the system.Human posture recognition system proposed in this paper is successfully deployed in the practice of municipal sanitation,which is convenient for real-time monitoring and dispatch management of outdoor workers through smart watches and cloud applications.