Qimeng Li

Qimeng Li

Advisor

Dr. Raffaele Gravina

Co-advisor

Dr. Gianluca Aloi

Research Topic

Multi-user activity recognition in IoT environment.

Research Abstract

The human activity plays a significant role in various fields, such as manufacturing, healthcare, safety, etc., therefore recognizing human activity is crucial to enable smart innovative services. The development of ubiquitous sensing and pervasive computing allows studying what humans perform in real-time and mobility. Single- and multi-user activity recognition (AR) are two types of human activity recognition (HAR) distinguishing by the number of users; multi-user AR is different from widely studied single-user AR since it not only depends on the activities performed by individuals, but the environment/context has a strong relevance too. Therefore, with multi-sensor and multi-information fusion and thanks to the Internet of Things (IoT) environments, multi-user activity recognition is becoming an emerging and relevant research frontier.