A three part system that consisting of a face-tracking voice assistant that displays emotions on its screen, and sensors that can gather and record plant health information
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Gold in Interactive Design 2020, Non Pro
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Gold in UX, Interface & Navigation 2020, Non Pro
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Silver in Digital Tools and Utilities 2020, Non Pro
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Silver in Apps 2020, Non Pro
Understanding the Problem
Objective
Prototype an interactive product utilizing Arduino, surrounding the theme of Social Robot.
Our Goal
A integrated smart home system that enables the house’s defensible to be visually mapped and simulated on to create a home that is ready (at least in theory) for shelter-in-place in case of a wildfire.
bud- Vision Video
bud Vision Film by: Sheryl Chan (Editor and Motion Graphics), Aparna Somvanshi (Product Renders and Script), Varun Khatri (Voiceover and Actor), Ren Fairly (Voiceover) and Madeline Walz.
Key Findings: Secondary Research
The relationship between Plants and Humans
I've tried to make them more like pets and less like plants. They have names. I’ve stuck some googly eyes on their pots. I like having something to take care of.
~Natasha Sligh, 25
It's really nice having another living thing in my apartment. I don't have any pets, and I live here by myself, so it's nice to water them, and talk to them, and see how they're doing.
~Maxine Mitchell, 30
I know that I have these little things that depend on me for life, and that helps inspire me to take care of myself as well. So when I wake up, the first thing I do is check my plants and make sure their temperature, soil, and sunlight are okay for the day.
~Jordan Woodman, 23
Benefits of keeping a plant
Key findings
then we must be better adapted for fire prone living.
Competitor Analysis
A three part system that consisting of a face-tracking voice assistant that displays emotions on its screen, and sensors that can gather and record plant health information
The Research Overview
Survey
People from various demographics.
Used to gather some preliminary information on demographics to target and the people’s experiences with plants.
User Interviews
People from a more focused demographic
Used to breakdown people’s experiences with plants and to analyze human behavior with plants.
The Package: Cultural Probes
Plant
Houseplant Journal
Plant Information Sheet
Nametag attached within the journal
Pen
Lollipops as a treat
Manilla envelope
The activites and the follow up interviews
Defining the problem and affinitizing our data points
We gathered insights from all of the research and collected around 214 data points. We then categorized these insights into 13 groups and drew design directions from each of the patterns.
Target Audience
+ Aged 18-30, any gender
+ Urban and Suburban Residence Areas
+ Beginner planting skill level
+ High interest in plants
Personas and Journey Maps
How Might We
aid people who have had little or no success grow thriving houseplants?
How Might We
help beginners understand each plant's individual needs?
How Might We
foster a stronger relationship between an individual and his/her plants?
Based on the understanding, we started conceptualizing
Initially, we came up two different concepts from our idea pool.
Concept 1: A stationary voice assistant module with a screen to emulate emotion that connects to separate sensors that can detect plant health.
Concept 2: A planter lamp combination that moves along its hinges and can voice interface base don the sensors it has to detect plant information.
We chose to focus on the first concept but with additional features from the second concept
Introducing bud
A rotating voice assistant module with a screen to emulate emotion that connects to separate sensors that can detect plant health.
Lo-fi Prototype
bud:
+ Made from pink foam,
+ Pan and tilt movement,
+ Swappable face,
+ bud voices by Sheryl Chan and Aparna.
Sensor "seeds":
+ Made from cardboard,
+ Programmed Arduino to change LED colors on a bottom click.
User Testing and Evaluations
In order to truly make our system more usable, empathetic and easy to understand, we conducted evaluation using the Quasi Empirical Method. In order to gain a further quantitative understanding we conducted a System Usability Scale Questionnaire.
We conducted these evaluations over 3 locations:
SUS Questionnaire response
73.2%
For all, the system was not unnecessarily complex.
For one, the various functions were not well integrated.
For one, learning how to use the system was not as easy as it could have been.
For one, enough information wasn’t provided before using the system.
bud: Voice AI
A three part system that consisting of a face-tracking voice assistant that displays emotions on its screen, and sensors that can gather and record plant health information.
The Product
The App Integration
