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Elf: Fostering a Healthier Lifestyle Through Environmental Awareness

Elf, a groundbreaking mobile app designed by Tiange Wang and I-Yang Huang, aims to revolutionize the way people approach indoor health and wellbeing. The app is the result of extensive research and development, offering personalized suggestions for indoor environmental improvements and behavioral changes. By leveraging real-time environmental and health data, Elf provides users with tailored coaching and nudges to enhance their everyday wellbeing. The app's conversational UI and intuitive data visualization guide users to understand the key environmental factors influencing their body's performance and comfort.

The project, which began in January 2022 and was completed in September 2022 in Cambridge, Massachusetts, has already garnered significant recognition. Elf was selected into Harvard i-Lab’s Venture Incubation Program and was a Semi-Finalist at Harvard’s Presidential Innovation Challenge. Additionally, the design received the prestigious Bronze A' Design Award in Mobile Technologies, Applications, and Software Design in 2023.

Elf is a cross-disciplinary endeavor that incorporates smart environment, wellbeing, health, interaction design, interface design, behavioral change, conversational UI, and data visualization. The app is available for both iOS and Android users and utilizes machine learning algorithms to calculate personal comfort zones based on body health profiles and environmental attributes, ensuring personalized advice for each user.

The app's functionality includes tracking environmental and body health data, analyzing areas of improvement, providing actionable suggestions, and enabling in-app information sharing. With features such as real-time environmental highlights, actionable tips, and personal routine timelines, Elf empowers users to take control of their indoor environment and overall wellbeing.

Through domain expert interviews and in-depth literature research in environmental science and public health, the design team obtained deep domain knowledge that informed the app's feature definition, feasibility, and user experience. The team also conducted extensive user interviews to define user personas, key use cases, and mental load perception preferences, ensuring the app's accessibility to users of all data literacy levels.

One of the key challenges overcome during the design process was balancing the complexity of data with the simplicity of communication. The team utilized gradient colors to convey overall environmental qualities and implemented a conversational UI to provide detailed information, ensuring a smooth and accessible experience for all users.

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