MarketWatch, May 4, 2021. Caspar.AI uses the whole home as a sensor – already existing elements like sensors on switches and appliances. From automated control of lights, shades and temperature to more complex tasks such as fall detection, the Caspar system works without cameras and without “wearables” such as resident pendants.
NSF funds Caspar.AI’s partner university for research on enhancing human health
The proposed project, led by Prof. Haiying (Helen) Shen, aims to build a human-centered context-aware responsive smart building that can provide personalized services to enhance the performance, comfort and health of occupants. The novelty of this project lies in its leveraging human behaviors in addition to the data from the physical world to provide context-aware automatic and personalized services that can better meet human needs. This smart building is unique by two features: 1) it provides personalized service rather than a universal service for all users; and 2) the building can automatically make context-aware adjustments to proactively meet user needs. This project consists of two innovations: 1) Social-based Context-aware Prediction/Response, and 2) Environmental Control for Human Health.
With CASPAR’s home computing platform, is in a unique position to support such research activities towards human comfort and health of the occupants. At CASPAR, we are building the intelligent operating system for the homes (which are equipped with 100s of IoT devices each in partnership with real-estate developers). Our goal is not only to develop a commercially viable business in smart homes, but also target open-ended research challenges in this area.
CASPAR’s previous efforts with university collaboration (such as with Stanford and Cornell) have resulted into new algorithmic techniques (such as about deep learning on graphs, award winning paper at CVPR 2016). With our goal to reach millions of homes next decade, we can have a huge impact on research challenges for workforce, for elderly living, and so on.