Presenting
Your Meal Buddy
Innovative smart fridge, designed to revolutionize meal preparation for college students
Motivation
“Empower college students with busy schedules and limited time to live healthier, more organized lifestyles by simplifying meal preparation, offering personalized recipe suggestions, and optimizing ingredient management through innovative IoT technology.”
Convenience
"Preparing meal is hard during final exams or when you have class early"
Budget
"I don't like spending too much knowing that sometimes I don't have time to cook"
Sustainability
"I don't like to throw food away which is why I tend to not shop too much either"
Project Overview
01
Ideation
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We used the 10x10 matrix process to brainstorm problems or topics for which we wanted to generate ideas.
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In each cell of the matrix, we brainstormed ideas that align with the corresponding category. All the ideas were minimized to one using an affinity wall.
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Our team voted for the most interesting ideas and decided the target users to be college students.
03
Prototype & Planning
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We conducted user enactments to test our ideas and gather additional data.
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We determined the sensors and other IoT components that will enhance our users' meal preparation experience during this milestone.
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We finalized the information architecture for the mobile and fridge screens.
02
User Research
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We conducted a diary study to gather detailed data about participants' behaviors, experiences, and thoughts over a period of time.
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Along with the diary study we deployed a survey to collect holistic data.
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All of the data was analyzed using affinity mapping, and various charts
04
Physical Prototype & Video
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We leveraged a combination of voice output, camera, digital screen, and mobile application functionalities for the physical prototype
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We initiated the design process for our user interface prototype using Figma. Our initial steps involved crafting wireframes and low-fidelity prototypes.
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We created our Demo video to walk through a typical user scenario using our product.
Ideation
We used the 10x10 matrix process as done in class where we brainstormed problems or topics for which we wanted to generate ideas. For example, given the environment of a smart kitchen, we were able to brainstorm different problems in the space and create ideas to tackle those problems. The 10x10 matrix was the best ideation process as it allows for a more detailed exploration of the problem space as well as generating a wide array of ideas. We created a matrix in FigJame In each cell of the matrix, we brainstormed ideas that align with the corresponding category.
As seen in the figure below, using the 10x10 matrix process we were able to each create at least 15 different ideas. We created an affinity wall in Figma, and categorized the different ideas into clusters.
On the affinity wall, we used a voting system, the first step was to brainstorm individually and read and understand each other's ideas. Secondly, we started to generate central themes, where if we saw similar ideas we put them under an umbrella. From there, when we had a clear idea of each opportunity present on the board, we each used three votes and voted on the opportunities that would be more viable and attractive to us as a team. Each opportunity with more than 2 votes was separated and a second voting took place where we were able to narrow down to the top three opportunities. As seen in the figure below, these three opportunities had the most votes as well as the most interest.
We decided to select idea #1 - Grocery/Meal Plan because it addresses a fundamental need for a large segment of the population. There is a growing trend towards healthier eating habits and an increasing demand for quick and healthy meal planning. Our product can offer students with busy lifestyles convenient, healthy, cost-effective, and time-saving solutions while supporting our users to maintain a healthy diet. We received very positive feedback from our classmates during the M0 presentation. Many classmates expressed their intention to purchase such a product, as it provides comprehensive meal planning solutions and management, aiding them in eating more healthily or reaching their fitness goals.
User Research
Diary Study
Diary studies allow us to collect qualitative data about user behaviors, activities, and experiences over time and in detail, and since we asked the participants to fill out the survey right after each meal, we can have real-time data in case the participants forget about details later.
We designed the study to collect mainly qualitative data, but we didn’t want our participants to spend too much time filling out the survey. So we made only one short answer question and made that optional.
Data was analyzed through graphs generated by Google Forms. Even though we didn’t have many responses to short answer questions, we still found out a few major issues that were helpful for us.
Survey
Surveys allow us to gather quantitative data from a large number of participants efficiently in a relatively short amount of time. We planned to analyze the qualitative data using the charts generated by Google Forms. The data was also collected and organized in a Google Sheet document.
Key Results
36.7% of participants spend less than 10 minutes on meal prep daily
63% participants prefer shopping in person than online
28.6% of participants usually spend from 20-30 minutes on meal prep
28.6% of participants usually spend from 20-30 minutes on meal prep
8.2% of participants said they never do meal prep
75% of participants said meal planning is time-consuming
Persona
Empathy Map
Journey Map
User Criteria
User Satisfaction: Prioritizing features that enhance user satisfaction and overall experience.Engaging and user-friendly interface: Focusing on intuitive, user-friendly interface design that facilitates seamless interaction with the smart fridge prototype. Easy to Use: The interface is easy to understand, explore, and navigate without extensive guidelines or instructions.
Efficiency and Convenience: Emphasizing features that improve efficiency in meal preparation tasks and enhance convenience for users. Self-explanatory and efficient design: We aim to create features which can help users to easily grasp information when needed. The interface should provide user immediate feedback to user actions. Users should be able to have features which can show them all the possible recipes or cooking ideas at a first glance.
Feasibility: Considering the feasibility of implementing proposed features within the constraints of technology and resources.
Final System Concept
Our system is an innovative, IoT device embedded in the refrigerator to help individuals manage their kitchen tasks, from ingredient inventory management to meal preparation. By integrating advanced image recognition technology, user-friendly interfaces, and personalized meal suggestions, our system aims to address key user needs around sustainability, convenience, and budget. The system is proposed to be developed with current technological capabilities and refined to be market-ready within the next 5 years.
Basic Features:
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Camera Module with Object Recognition: identify and track inventory in real-time.
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Auditory Feedback System: Provides audible alerts for successful item scans
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Mobile Application Integration: Offers remote inventory management and recipe access
The proposed system utilizes existing technologies such as RFID (a device that reads information contained in a wireless device or “tag” from a distance without making any physical contact or requiring a line of sight), barcode scanning, and particularly object recognition. The integration of a camera to detect what is inside the fridge is technically feasible today and will be developed to have greater performance and lower costs over the next few years. The auditory feedback mechanism and touch-screen interface are well-established technologies, so implementing them into our system is straightforward. Developing the personalized meal recommendation requires data collection and machine learning, and it is achievable within the proposed time frame. Overall, the system we designed is a plausible project that could be brought to market readiness in approximately 5 years.
Physical & Digital Prototype
Circuit Design
Controlled by Particle mobile app
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Digital Monitor
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Brief messages
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System status
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RGB LED
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Red for in the process of scanning
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Green for ready-to-scan/Done updating
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Code Snippet
High-Level Architecture
Video Demo
Reflection
An area of further research would be in regards to different cuisines and dietary restrictions. The device is not competent to generate unique recipes from different cuisines, which may be a turn-off for some users. Additionally, experimentation with alternative interface types such as gesture or voice control could provide insights into preferred interaction methods among users.
We will prioritize creating a seamless, automated, and user-friendly experience. To achieve this, we have chosen to employ digital screens, light and voice output functionalities, along with the integration of mobile applications for our IoT product. To evaluate our design, we will rely on three key criteria: user satisfaction, efficiency, convenience, and feasibility. These criteria will enable us to develop more user-friendly design solutions and provide guidance for making effective design decisions.
We prioritized inclusivity by integrating various sensors to address accessibility concerns. Leveraging an array of sensory inputs, including lights, voice recognition, audible sensors, and touch, along with a clean and simple user interface, we aimed to create a seamless user experience catering to diverse needs. The integration of lights not only enhances visibility but also serves as an intuitive indicator for users with visual impairments. Voice recognition technology enables hands-free interaction, empowering users with mobility limitations or those who prefer verbal commands. Audible sensors offer real-time feedback, aiding users with visual or cognitive impairments in understanding fridge status and alerts. Moving forward, for the design to be accessible, we would want the already existing features to be researched further to determine the faults.