Independent Living with Ultra-Dense Sensing
The world population is rapidly ageing. Therefore, recognizing human activities is important to assist the older adults to stay in their homes for a longer period of time. With recent developments in cheap sensors and networking technologies embedded into a "things" capable of connecting to the Internet, it has become possible to develop a wide range of valuable applications such as remote monitoring and intervention. Therefore, in this project we will explore the potential for using battery-less, chep and tiny sensors embedded into the environment, ultra dense sensing, for recognizing human activities to support independent living.
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Citations for the Dataset
- Asanga Wickramasinghe, Roberto Luis Shinmoto Torres, and Damith C. Ranasinghe. "Recognition of falls using dense sensing in an ambient assisted living environment." Pervasive and mobile computing (2016).
- Torres, Roberto Luis Shinmoto, Asanga Wickramasinghe, Viet Ninh Pham, and Damith C. Ranasinghe. "What if Your Floor Could Tell Someone You Fell? A Device Free Fall Detection Method." In Conference on Artificial Intelligence in Medicine in Europe, pp. 86-95. Springer International Publishing, 2015.