InventoryIris — food waste reduction on Bee

Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for InventoryIris — food waste reduction on Bee

Inspiration

We were inspired by the staggering amount of food thrown away in commercial kitchens due to poor inventory tracking. We wanted to create a tool that empowers developers to build sustainable solutions easily. Building this for the Bee track allowed us to focus on a seamless event-driven architecture.

What it does

InventoryIris monitors food stocks and predicts when items are likely to expire. It uses natural language processing to categorize grocery items and alerts users before waste occurs. The system helps both households and businesses minimize environmental impact while saving money.

How we built it

We implemented the core logic using Python and deployed the service via AWS Lambda functions. We utilized Amazon Comprehend to analyze text-based inventory lists and boto3 to interface with our data storage. The integration with the Bee surface ensured real-time processing of all inventory updates.

Challenges we ran into

We initially struggled with mapping various food categories into a standardized schema for the database. It was also challenging to ensure the Lambda functions communicated perfectly with the Bee track environment without latency. We resolved these by optimizing our parsing logic and refining our API calls.

Accomplishments that we're proud of

We are proud of how seamlessly we integrated Amazon Comprehend to extract entities from raw text. The speed of the inventory updates on the Bee track exceeded our initial expectations. Successfully building a functional prototype that reduces waste is a major win for our team.

What we learned

We learned a lot about optimizing serverless workflows using Python within the AWS ecosystem. We also gained deep insights into how natural language processing can be applied to logistics logistics. Understanding the nuances of the Bee track was invaluable for our development process.

What's next for InventoryIris

We plan to add a recipe suggestion engine based on items that are nearing expiration. We also want to expand the mobile interface to allow for faster barcode scanning. Our goal is to make InventoryIris the gold standard for food waste reduction on Bee.

Built With

• amazon-bee
• amazon-comprehend
• aws-lambda
• boto3
• inventoryiris
• pantry