Deep-Learning-Enhanced Human Activity Recognition for Internet of Healthcare Things

Along with the advancement of several emerging computing paradigms and technologies, such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of Things (IoT) technologies have been applied in a variety of fields. In particular, the Internet of Healthcare Things (IoHT) is becoming increasingly important in human activity recognition (HAR) due to the rapid development of wearable and mobile devices. In this article, we focus on the deep-learning-enhanced HAR in IoHT environments. A semisupervised deep learning framework is designed and built for more accurate HAR, which efficiently uses and analyzes the weakly labeled sensor data to train the classifier learning model. To better…

• NS
  Natural Science Foundation of Hunan Province

  Award: 2019JJ40150
• NK
  National Key Research and Development Program of China

  Award: 2017YFE0117500