设计师 Tiange Wang 的作品 Elf 身体环境健康应用程序荣获了极具声望的 2023 A' Design Award 铜奖，竞赛类别为移动技术、应用与软件设计。

铜移动· 2023

Elf 身体环境健康应用程序

设计师： Tiange Wang

客户: VLab

移动类别A' Design Award 铜奖获奖者

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关于 Elf 身体环境健康应用程序

Elf 是一款创新的移动应用程序，通过提供有关室内环境改善和行为改变的个性化建议，促进环境健康和身体健康之间的联系。通过实时环境和健康数据，Elf 指导和推动用户可以对室内环境采取的行动，以改善他们的感受和表现。该设计将直观的交互式数据可视化与美丽、柔和的颗粒状颜色渐变相结合，并使用对话式 UI 将应用程序的角色与家养小精灵保持一致，以获得更强的情感吸引力。

荣誉认可

关于A' Design Award 铜奖

Elf 身体环境健康应用程序是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Elf 身体环境健康应用程序将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Elf 身体环境健康应用程序出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: Elf fosters the connection between environment health and body health by offering personalized suggestions about indoor environmental improvements and behavioral change. Using realtime environmental and health data, Elf coaches and nudges the user about actions they could take to their indoor environment to improve their everyday wellbeing. Through conversational UI and colors, the user is guided to understand key environmental qualities that are influencing how their body feels and performs.
尺寸与包装: Elf is a mobile app for both iOS and Android users. It incorporates interactive and intuitive data visualization in showing environmental and body health data. The conversational UI supported by AI makes tips and advice easy to digest and helps align the character of the app to a house elf to create stronger emotional appeal. Machine learning algorithm calculates personal comfort zones based on body health profiles and environmental attributes to support personalization of advice.
标签: Smart Environment, Wellbeing, Health, Interaction Design, Interface Design, Behavioral Change, Conversational UI, Data Visualization
生产技术: The project is highly cross-disciplinary. We used lots of desktop research, expert interviews and data collection to gain deep domain knowledge around how key environmental metrics trigger +/- interactions with the human body indoors. We also conducted in-depth competitive analysis to find unique market positioning that intersects smart environment, wellbeing and habit-forming. We used human-centered design thinking to identify design principles, main features and data communication approach.
设计挑战: 1.Balance complexity of data &simplicity of communication. A related goal was to reduce mental load & ensure smooth experience for the most &least data-literate users. It is essential to communicate beyond numbers and we used gradient colors to convey overall qualities and conversational UI for further details. Together they also provide redundancy for enhanced accessibility. 2.Organize information hierarchy between data reading, tips and routines across the app to fit a natural mental model.
研究: Through domain expert interviews and in-depth literature research in environmental science and public health, we obtained deep domain knowledge that informed feature definition, feasibility and UX writing of the app. We collected data around environmental thresholds to calibrate the content and frequency of advice generation. We also interviewed 16 people of different profiles and data literacy levels, and the results led to defining the following: user personas, key use cases, and mental load perception preferences.
灵感: Studies have found that in North America and Europe, we spend90% of our time indoors and the quality of indoor environmental elements like air, sound and light affects comfort, wellbeing and productivity. While there are plenty of apps that monitor environmental and body data separately, less attention has been paid to connecting the two explicitly. How might we help people live healthier lifestyles by leveraging this connection and providing personalized coaching for their indoor health?
项目周期: The project started Jan 2022 and completed this version in Sept 2022 in Cambridge, Massachusetts. It is an ongoing process with updates depending on new needs and business goals. It was selected into Harvard i-Lab’s Venture Incubation Program and was a Semi-Finalist at Harvard’s Presidential Innovation Challenge.
操作流程: Elf takes in environmental and body health data (tracking), identify areas of improvement (analysis), output suggestions (advice) and allows in-app sharing of information (community). Users start by setting up basic demographic profile, geolocation, health interests and data collection. The app has 4 main areas: home (see realtime environmental highlights, actionable tips and personal routine timeline), data (explore detailed data), tribe (share insights) and profile (bookmarks and settings).
团队成员: I-Yang Huang
图片版权: Image #1: Tiange Wang, I-Yang Huang, 2022.
Image #2: Tiange Wang, 2022.
Image #3: Tiange Wang, 2022.
Image #4: Tiange Wang, 2022.
Image #5: Tiange Wang, 2022.