Inspiration

In homes worldwide, there is a common dilemma of fridges filled with neglected ingredients and pantries cluttered with rotting food. It raises a compelling question: "What if you could use every ingredient efficiently and deliciously?"

As ChatGPT's popularity soared, an idea sparked: Why not develop a handy tool that can suggest recipes from just a snapshot of ingredients, helping to minimize food waste? This idea gained urgency as we saw a startling United Nations statistic: approximately 1.3 billion tons of food intended for human consumption is lost or wasted annually, while about 690 million people face hunger.

To solve this, we have created SnapCook, a revolutionary transformation of these wasted ingredients into culinary creativity. Doing so not only helps with food wastage but also encourages inventive cooking and provides a more convenient alternative to tediously listing each ingredient.

What it does

Snap Cook is a mobile application that transforms your food photos into plenty of delicious recipes. Users simply snap a picture of available ingredients, and the app's sophisticated AI recognizes the food items, fetching a range of recipes that can be created with them. In addition to providing recipes, Snap Cook offers unique customization, making it easy for users to make informed, healthy choices. The app acts as a smart kitchen assistant, helping users create delicious dishes, optimizing resource usage, and minimizing food waste.

How we built it

Building Snap Cook was an arduous process involving various technologies. We used MIT App Inventor for the initial app construction, providing a user-friendly interface for our users. The backend was developed using Node.js, a platform built on Chrome's JavaScript runtime, which helped us manage our data and APIs efficiently. We utilized the LogMeal API for image recognition, which recognizes food from images and gives us the necessary ingredient data. We leveraged SerpAPI for fetching image data. We integrated ChatGPTto analyze possible recipes, a state-of-the-art language model that generates human-like text based on the input. By threading together these different technologies, we were able to build Snap Cook, an app that transforms the way we perceive and interact with food.

Challenges we ran into

Ensuring the API works as desired and integrating it into our system.
Determining the most efficient way to incorporate ChatGPT to generate the most - relevant recipes.
Interfacing MIT App Inventor with our backend posed a significant technical challenge.
Debugging and fixing bugs was an extraordinarily time-consuming yet essential part of the process.
File transfer between MIT App Inventor and other platforms was difficult.
Food detection AI is still a developing technology, and improving its accuracy was a hurdle.

Accomplishments that we're proud of

Crafting a fully functional product within a short span of one day.
Designing a logo that beautifully encapsulates our mission and vision.
Overcoming the many technical challenges and delivering a working, impactful application.

What we learned

We honed our teamwork and coding skills, streamlined our planning and design approach, and learned to manage time more efficiently.
We gained invaluable insights into the world of AI and image recognition, as well as the world of app development.

What's next for Snap Cook

Snap Cook is not just an app; it's a stepping stone toward a more efficient, waste-free, and healthier future. We envision improving our AI's accuracy and widening our recipe database to include more global cuisines, making Snap Cook impactful globally. We also plan to introduce features like voice input for easy accessibility and personalized recipe suggestions based on dietary preferences. We aim to position Snap Cook as essential to every sustainable, smart kitchen worldwide.