This talk explores how AI-enhanced radar technology can revolutionize healthcare in long-term care (LTC) facilities. ElephasCare, an AI-driven platform, utilizes non-invasive radar sensors to autonomously monitor LTC residents' daily activities while maintaining privacy and improving health outcomes.
The rapid advancements in artificial intelligence are transforming embedded sensing systems, bridging the physical and digital worlds in unprecedented ways. In health and wellness, embedded AI empowers everyday environments and devices to proactively support both physical and mental well-being. This talk highlights projects from the Columbia Intelligent and Connected Systems Lab (ICSL) that exemplify this convergence.
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.
