sMAP

Human activity recognition (HAR) is one of the core topics in wearable and ubiquitous computing, as it allows intelligent systems to be aware of their surrounding context and expect the intentions of humans in the environment. Our physical activities often cause specific patterns in the sensor signals, and sensor-based HAR focuses on inferring the activity contexts based on the signal patterns. One of the greatest challenges in sensor based HAR is the lack of well annotated data to establish the link between signal characteristics and semantic contexts.

The use of digital technologies, such as the Internet of Things (IoTs) and artificial intelligence (AI), continues to grow at an incredible pace and in conjunction with the growing generation of “big data.” One of the hopes and challenges around the globe is to leverage these technologies and harness the data to transform society. Some of the urgent societal challenges are associated with a growing aging population (e.g., increase healthcare needs, decrease mobility/ activity), declining birthrate, regional employment loss, and aging infrastructure to name a few. Recent advances in miniature sensor development and wireless power transmission have the potential to address many of these challenges especially in helping aging population. It is important to reiterate that while the proposed technology clearly benefits the client, we also seek ways to understand how this technology can be better implemented to bring benefits beyond an individual but connect to the broader community. I will discuss our work on developing miniature chemical and biological sensors and single wire electricity delivery technique for powering devices to help aging population.