I-Corps: Translation Potential of a Wearable Device to Enhance Personal Comfort through Automated Environmental Controls
- Institution
- New Jersey Institute of Technology, NJ
- Principal investigator
- Yanxiao Feng
- Funding
- $50K
- Duration
- 2025–2026
Moonbase score
Still being scored
Abstract
This I-Corps project focuses on the development of a smart indoor comfort system that adjusts personal room conditions based on each person’s unique needs. The technology is beneficial for individuals who are sensitive to their environment, such as seniors and those with chronic health conditions. Many buildings rely on fixed temperature settings that overlook personal preferences, often leading to ongoing discomfort and even potential health concerns. This challenge affects people in homes, hospitals, offices, and other indoor spaces. The system integrates wearable sensors, environmental monitors, and a mobile application to collect real-time data and support dynamic indoor condition adjustments. By aligning the environment with how a person actually feels, the system enhances comfort and well-being. Its broader adoption could lower energy costs, support energy efficient building practices, and improve the quality of life for occupants. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a smart, adaptive environmental control device that integrates wearable sensors, environmental modules, and a digital application. Unlike traditional systems, which rely on static settings, this approach dynamically responds to changes in user needs and environmental conditions. The wearable sensor tracks physiological data, such as body temperature and heart rate, while the environmental module measures room conditions, such as temperature and humidity. The digital application collects user feedback on thermal sensation, merging individual and environmental data using online analytics. This solution enables continuous, personalized adjustments based on real-time modeling, offering context-aware adjustments. This system’s flexibility and efficiency could advance smart building systems, energy efficiency, and occupant well-being. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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