Amazon Case study: MEANS - Matching Excess with Need

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Two students had an idea: match excess food with people in need. Maria Rose Belding and Grant Nelson created MEANS, a nonprofit database where people list a donation, food banks and pantries get notified about food near them, and then they claim and pick up the food.

MEANS was built out and integrated on AWS using services including Amazon CloudFront for content delivery, Amazon Simple Storage Service (Amazon S3) for storage, Amazon Mechanical Turk (mTurk) for data validation, and Amazon Machine Learning to predict which food pantry they should be calling to maximize the chance of a donation finding a home.

Full story:
https://blog.mturk.com/case-study-means-matching-excess-with-need-a198524b9033
https://aws.amazon.com/blogs/publicsector/means-matching-excess-with-need/