Inspiration
EcoPaw was inspired by a common household problem: we often buy food with good intentions, then forget what is already in the fridge until it expires. Many food waste apps try to become perfect inventory trackers, but that creates too much work for users. We wanted to build something lighter, friendlier, and easier to keep using.
The idea behind EcoPaw is simple: if a virtual pet can react to our choices, then reducing food waste can feel less like a chore and more like a daily habit.
What it does
EcoPaw helps users reduce household food waste by focusing on the moments where waste is most likely to happen.
Users can add food through manual entry, receipt/image recognition, or demo data. Before buying more food, the app checks the shopping list against the current inventory and warns users about duplicate or high-risk purchases. Each day, EcoPaw recommends the most important “rescue actions,” such as using, freezing, sharing, or checking food that may soon go bad.
The virtual pet reacts to user behavior. When users avoid overbuying or rescue food, the pet becomes healthier and happier. When food is ignored or discarded, the pet’s state changes gently without blaming the user. The app also shows impact metrics such as avoided waste and completed rescue actions.
How we built it
We built EcoPaw as a Vite + React + TypeScript web app. The app uses local-first storage so it works well for hackathon demos without requiring accounts or a database.
The main modules include:
- Inventory management for food items and item states
- Purchase guard logic to detect duplicate or risky purchases
- Daily planning logic for food rescue recommendations
- AI/OCR adapters for receipt and image-based recognition
- A virtual pet state engine that responds to user actions
- Impact tracking to show estimated food waste avoided
For deployment, the project supports Cloudflare Workers. The app can run in a stable demo mode with mock recognition, while optional Google AI or OpenAI integrations can be used for image recognition and rescue planning.
Challenges we ran into
One major challenge was avoiding the trap of building a “perfect fridge tracker.” Real users do not want to update every bite, quantity change, or leftover container. We had to redesign the product around lower-friction actions: preventing overbuying and rescuing the few items that matter most today.
Another challenge was making AI useful without overtrusting it. Receipt OCR and food image recognition can be wrong, so EcoPaw treats AI output as editable suggestions instead of automatically changing the inventory.
We also had to balance gamification carefully. The pet needed to create motivation, but not guilt. Food waste is already frustrating, so the feedback had to be supportive and recoverable.
Accomplishments that we're proud of
We are proud that EcoPaw has a clear product focus: it helps users act at the right moments instead of asking them to maintain a perfect database.
We built a complete demo loop: add or recognize food, check a shopping list, get warned about risky purchases, complete rescue actions, see impact metrics, and watch the pet respond.
We are also proud of the explainability in the app. Recommendations are not just random reminders; they explain why an item should be used, frozen, shared, or checked.
What we learned
We learned that reducing food waste is not only a data problem. It is also a behavior design problem. The best solution is not always the most automated one; sometimes the better product is the one that asks less from the user.
We also learned that AI works best here as an assistant, not an authority. It can reduce typing and suggest plans, but users still need control, especially when food safety and personal judgment are involved.
Most importantly, we learned that a small daily intervention can be more realistic than a complex tracking system.
What's next for EcoPaw
Next, we would like to improve real receipt recognition and food image recognition, add barcode or product database lookup, and support shared household inventories.
We also want to add smarter reminders, browser notifications, and better recipe suggestions based on what users already have. In the long term, EcoPaw could connect users with local food sharing or donation options so that extra food can be rescued before it becomes waste.
Built With
- ai
- cloudflare-workers
- css
- eslint
- food-waste
- gemini
- google-ai-studio
- html
- image-recognition
- localstorage
- ocr
- openai-api
- react
- sustainability
- typescript
- vite
- vitest
- web-app
- zustand
