Bibo Smart AI Companion
Bibo is an AI-enhanced mindful eating companion that assists users in achieving nutritional and emotional balance at meal times. By engaging in discussions about their meals, Bibo helps users practice mindful eating, reflecting on both the nutritional content and emotional impacts of their food.
Role Independent Project
Project Duration 01/2024 - 05/2024
System / Product Design
Scroll to Explore
About the Project
Research
Persona
Insights & Design Goal
Final Design
Design Process
Prototyping
Conclusion
Other Projects
Back to Top
About the Project
Our research and interviews highlight a significant issue: many people, especially those living alone or following strict diets, are distracted during meals by technology like TV or TikTok, leading to a disconnection from the spiritual aspect of eating. This often results in unhealthy eating habits and various health problems due to a lack of attention to what and how they eat. Bibo addresses this gap by reintroducing the joy and nourishment that mindful eating brings, positively affecting both physical and emotional health.
Problem
Before we delve into the features of Bibo, let's first explore the user research that informed its design. Post discussions with individuals who previously suffered from diet-related eating disorders, and consultation with a dietary expert, we amalgamated the insights into a persona and user journey map to afford us a clearer comprehension of the challenge.
Persona
Post conducting one-on-one conversations with folks that previously suffered eating disorders due to irresponsible eating habits, and conferring with dieticians, we assimilated the insights into a user profile and a journey map. This approach offered us a comprehensive understanding of the issue at hand.
User Journey Map: Before
This journey underlines the frequent hazards of detrimental dietary practices. Subsequently, let's delve into how Bibo can distinctly aid individuals such as Emily through innovative functionalities and compassionate design.
Design Goal
Final Design
Bibo Usage Steps
Upon activation, Bibo initiates dialogue with the user, prompting them to share the content of their meal.
Subsequently, Bibo establishes a linkage with Chatgpt's API, aiding Bibo in determining the portion sizes for all food items based on the user's total daily energy expenditure (TDEE), and concurrently compiling a list of each ingredient along with its weight in grams. The consequent data from GPT is then transferred to the Ninja Nutrition API, a leading API in nutrient computation. This contributes to Bibo's ability to calculate the caloric content of each food item, appointing a broad nutritional score varying from A to F. The Python language is used to consolidate the calories from every food item and juxtapose the sum with the individual’s TDEE, to weigh the suitability of the intake. Lastly, the nutrition grade is incorporated to work out the ultimate nutritional score.
Following the dietary analysis, Bibo will prompt users: “Squeeze on my antenna to indicate your satisfaction with the food!” For understanding, when an initial user begins to interact with Bibo, Bibo will guide them to exert their highest and lowest force during the initiation to determine the scope of pressure measurements. When the user applies pressure to the sensor, the data is relayed back to the Arduino IDE. The IDE will then gauge the pressure value against the user's predefined pressure spectrum and attribute a sentiment rating from 0 to 100 for the dish.
Once the two ratings are in hand, the mechanism compares them, evaluating the degree of variation between the two to gauge the disparity in nutritional and emotional aspects of the specific dish.
The disparity is then reflected on the rotation of the antenna. If it rotates to the left side it means the user is more leaned toward the nutritional side. On the contrary, if it rotates to the right side, the user is more leaned towards the emotional side.
The rotation is accumulating and the final goal is for the user to retrieve the middle balance as much as possible, which aligns our goal to help users to keep track of their eating habits and find balance
User Journey Map: After
xxx
Iteration & Construction
Our initial concept and model, Balance/Bite, utilizes a mobile camera for food analysis imagery and a physical apparatus for pressure detection and visual balance indication. We received beneficial insights from the midterm evaluation. Our conclusions focus on:
1. The structure and user interaction may be overly daunting for susceptible user groups, considering the prominent balancing scale resemblance. Plus, the user journey lacks sufficient engagement.
2. There's a disjoint between the tangible product and the use of a phone to capture a food picture. Progressing from Balance/Bite, we have refined our initiatives — and that's the genesis of Bibo.
Form Exploration
Bibo CMF Design
Fabrication
Structure Map
Bibo's Expression Design
Prototyping Process
Conclusion
Bibo represents a significant leap forward in integrating AI with everyday well-being. Our project has not only delivered a practical tool to foster healthier eating habits but has also introduced a compassionate companion into our users' daily lives. By focusing on the emotional and nutritional aspects of eating, Bibo encourages a holistic approach to wellness. We have seen firsthand how our mindful eating companion can transform routine mealtimes into opportunities for self-reflection and improvement. Moving forward, we are committed to refining Bibo's interactive capabilities and expanding its accessibility to help more individuals achieve balance and satisfaction in their nutritional lives. Our journey with Bibo has been immensely fulfilling, and we are excited about the potential of this innovative product to make a lasting impact on public health and personal happiness.
©2024 CARINA LEE PORTFOLIO
GO BACK TO TOP