AI-Powered Cooking Assistant

Developed an AI-driven cooking assistant aimed at reducing household food waste by optimizing meal planning and ingredient utilization.

AI-Powered Cooking Assistant

Developed an AI-driven cooking assistant aimed at reducing household food waste by optimizing meal planning and ingredient utilization.

My Focus

Product Design

UI/UX Design

Front-end Development

Timeline

2 months

Tools

Figma

Next.js

React

Problem Statement

Household food waste contributes significantly to environmental issues and financial loss. Studies show that 25-30% of all food purchased by individuals is wasted, equating to approximately 1.3 billion tons of food wasted globally each year. This waste not only impacts the environment but also represents a significant economic loss for households. The challenge was to create a solution that assists users in efficiently utilizing available ingredients, thereby minimizing waste.

45%

Reduction in food waste

12.5%

Reduction in weekly food purchases

25-30%

Household food is wasted globally

User Research:

Conduct interviews to understand cooking and waste habits of individuals who cook two meals daily.

Prototype Design:

Design a prototype in Figma to visualize the user interface and core functionality.

Development and Testing:

Explore using React and VS Code to create a functional webpage.
Test the prototype by using it myself, tracking my own ingredient usage and applying a waste reduction formula.

Feature Development:

AI-Powered Recipe Suggestions: Implement algorithms to recommend recipes based on users' existing ingredients.
Smart Shopping Lists: Develop features to generate shopping lists that complement available ingredients, preventing over-purchasing.

Iteration:

Conduct a study to assess the assistant's effectiveness in reducing food waste.

User Research:

Conduct interviews to understand cooking and waste habits of individuals who cook two meals daily.

Prototype Design:

Design a prototype in Figma to visualize the user interface and core functionality.

Development and Testing:

Explore using React and VS Code to create a functional webpage.
Test the prototype by using it myself, tracking my own ingredient usage and applying a waste reduction formula.

Feature Development:

AI-Powered Recipe Suggestions: Implement algorithms to recommend recipes based on users' existing ingredients.
Smart Shopping Lists: Develop features to generate shopping lists that complement available ingredients, preventing over-purchasing.

Iteration:

Conduct a study to assess the assistant's effectiveness in reducing food waste.

User Research:

Conduct interviews to understand cooking and waste habits of individuals who cook two meals daily.

Prototype Design:

Design a prototype in Figma to visualize the user interface and core functionality.

Development and Testing:

Explore using React and VS Code to create a functional webpage.
Test the prototype by using it myself, tracking my own ingredient usage and applying a waste reduction formula.

Feature Development:

AI-Powered Recipe Suggestions: Implement algorithms to recommend recipes based on users' existing ingredients.
Smart Shopping Lists: Develop features to generate shopping lists that complement available ingredients, preventing over-purchasing.

Iteration:

Conduct a study to assess the assistant's effectiveness in reducing food waste.

User-Friendly Interface

Ensure simplicity in design to cater to users of all skill levels.

Ingredient Matching

Enable real-time matching of user inputs with recipe suggestions.

Sustainability Focus

Promote reduced food waste through optimized meal planning.

User Research

Conducted interviews with 10 individuals who cook two meals daily, gathering insights on their cooking habits, ingredient usage, and common sources of food waste.

Prototype Design

Designed an interactive prototype in Figma to visualize the user interface and core functionality, focusing on ease of use and clarity.

Development & Testing

Built the platform using React, Next.js, and VS Code, integrating the Open AI API for AI-powered recipe suggestions and real-time ingredient matching.

Waste Reduction Formula

Personally tested the platform to track ingredient usage and applied the waste reduction formula, iterating based on feedback and observed results.

The Study

The study involved 2 participants who used the assistant over a two-week period, following a two-week period without it.

Without AI Assistant:

Average Weekly Food Purchased: 16 lbs
Average Weekly Food Waste: 4 lbs (25% of total food purchased)

With AI Assistant:

Average Weekly Food Purchased: 14 lbs
Average Weekly Food Waste: 2.2 lbs (15% of total food purchased)

Using the formula, it shows a 45% reduction in food waste

Final Design

Cook delicious meals while reducing food waste

Cook delicious meals while
reducing food waste

Cook delicious meals while reducing food waste

AI-powered meal planning helped users optimize ingredient usage, reducing food waste by 45% and grocery purchases by 12.5%. Smart recipe suggestions and automated shopping lists minimized over-purchasing and improved meal efficiency, validating the impact of AI-driven solutions.

45%

Reduction in food waste

12.5%

Reduction in weekly food purchases

25-30%

Household food is wasted globally

I learned the importance of creating solutions that address users' daily routines.

Simplify Existing Patterns

Used familiar design principles to streamline ingredient matching and recipe suggestions.

Focus on Iterative Learning

Refined features based on user feedback and improve ingredient matching and substitutions.

Prioritize Clarity and Usability

Focused on simplicity to create a user-friendly experience.