Elf 身體環境健康應用程式

由 Tiange Wang

客戶: VLab

流動類別嘅 A' Design Award 銅獎得獎者

19,088

經驗證嘅獲獎者

驗證設計 #147452 嘅獲獎狀態

訪問網站喺 A' Design Award 查看新聞稿獎項徽章

色彩

設計

關於 Elf 身體環境健康應用程式

Elf 是一款創新的行動應用程序，透過提供室內環境改善和行為改變的個人化建議，促進環境健康和身體健康之間的聯繫。透過即時環境和健康數據，Elf 指導和推動用戶可以對室內環境採取的行動，以改善他們的感受和表現。該設計將直覺的互動式數據視覺化與美麗、柔和的顆粒狀顏色漸變相結合，並使用對話式 UI 將應用程式的角色與家養小精靈保持一致，以獲得更強的情感吸引力。

榮譽認可

關於A' Design Award 銅獎

Elf 身體環境健康應用程式是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Elf 身體環境健康應用程式將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Elf 身體環境健康應用程式出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: 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.
尺寸同包裝: 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.
標籤: Smart Environment, Wellbeing, Health, Interaction Design, Interface Design, Behavioral Change, Conversational UI, Data Visualization
生產技術: 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.
設計挑戰: 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.
靈感: 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?
項目時長: 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).
團隊成員: I-Yang Huang
圖片來源: 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.