Elf Ķermeņa Vides Labsajūtas Lietotne by Tiange Wang

Elf Ķermeņa Vides Labsajūtas Lietotne by Tiange Wang is a highly esteemed winner of the very prestigious 2023 Bronzas balva A' Design Award in Mobilo tehnoloģiju, lietotņu un programmatūras dizains Competition Category.

BronzasMobilais· 2023

Elf Ķermeņa Vides Labsajūtas Lietotne

by Tiange Wang

Client: VLab

Bronzas balva A' Design Award Winner in Mobilais Category

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Verified Award Winner
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Colors

The Design

About Elf Ķermeņa Vides Labsajūtas Lietotne

Elf ir novatoriska mobilā lietotne, kas veicina saikni starp vides veselību un ķermeņa veselību, piedāvājot personalizētus ieteikumus par iekštelpu vides uzlabojumiem un uzvedības izmaiņām. Izmantojot reāllaika vides un veselības datus, Elf apmāca un pamudina lietotāju par darbībām, ko viņi varētu veikt savā iekštelpu vidē, lai uzlabotu viņu pašsajūtu un veiktspēju. Dizains ietver intuitīvu un interaktīvu datu vizualizāciju ar skaistiem, maigiem graudainiem krāsu gradientiem un izmanto sarunvalodas lietotāja interfeisu, lai saskaņotu lietotnes raksturu ar mājas elfu, lai iegūtu spēcīgāku emocionālo pievilcību.

The Recognition

About the Bronzas balva A' Design Award

Elf Ķermeņa Vides Labsajūtas Lietotne ir Bronzas balvas A' Design Award ieguvējs, ļoti prestiža atzinība, ko piešķir izciliem dizainiem, kas izceļas ar radošumu, atjautību un viedumu. Bronzas ieguvēji ir pietiekami prasmīgi un pārsteidzoši radoši darbi, kas apliecina to dizaineru plašo pieredzi, iztēli un izdarību. Sagaidāms, ka Elf Ķermeņa Vides Labsajūtas Lietotne būs augsti vērtēts, apbrīnots un cienīts priekšmets, ievērojami profesionāls un inovatīvs. Šis ar Bronzas balvu apbalvotais dizains iekļauj labāko praksi mākslā, zinātnē, dizainā un tehnoloģijās un izceļas ar uzmanību detaļām. Elf Ķermeņa Vides Labsajūtas Lietotne lieliski apmierina vajadzības, skar vēlmes, valdzina jūtas un piesaista zinātkāri.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: 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.
Dimensions & Packaging: 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.
Tags: Smart Environment, Wellbeing, Health, Interaction Design, Interface Design, Behavioral Change, Conversational UI, Data Visualization
Production Technology: 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.
Design Challenge: 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.
Research: 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.
Inspiration: 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?
Project Duration: 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.
Operation Flow: 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).
Team Members: I-Yang Huang
Image Credits: 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.