Human Activity Recognition Using Wearable Sensors in IoT Environments: Challenges and Opportunities

One of those applications, Human Activity Recognition, uses wearable sensors, made possible by the rapid rise and development of Internet of Things technology. HAR is the automated process of identifying and classifying human activities from sensor data with wearable devices such as smart watches/fabric bands. Given its utility in healthcare, HAR has immense possibilities, especially within IOT environments such as health & fitness, safety, and security. But, at the same time, it introduces new challenges of handling massive real-time sensor data streams and providing privacy for people when their daily routines are reconstructed, as well as developing accurate and reliable algorithms. In addition, human activities are diverse, and the data that sensors collect may also differ, making HAR in IOT very complicated. HAR can also provide various opportunities, e.g., real-time monitoring and analysis of human activities, personalized health/fitness advice, and safe/smart environmental improvements. Implementing artificial intelligence and machine learning models in HAR can also improve performance. HAR based on wearable sensors in an IOT environment holds promise for changing our views of and tracking human activities to a new level that could be applied to many different sectors and improve quality of life.