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AllerScan is an allergy detection iOS application that scans food labels (in multiple languages!) for a given set of allergies. Built by Pingry students Rhea Kapur (Pingry '21), Eva Schiller (Pingry '21), Emma Huang (Pingry '21), and Olivia Taylor (Pingry '23) at FemmeHacks 2021.

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AllerScan

Built by Pingry students Rhea Kapur (Pingry '21), Eva Schiller (Pingry '21), Emma Huang (Pingry '21), and Olivia Taylor (Pingry '23) at FemmeHacks 2021, a virtual, all-female hackathon sponsored by the University of Pennsylvania's WICS group. All attended FemmeHacks as either members or leaders of the Pingry Girl Code Club.

AllerScan is an allergy detection iOS application that scans food labels (in multiple languages!) for a given set of allergens so that users can eat safely and without worries. Perfect for those who are traveling in foreign countries where an unfamiliar language is spoken, those with trouble discerning small-size text, or those who simply want to rid themselves of the tedious and stressful process of examining long ingredient lists for their allergens.

The AllerScan interface was built by Rhea Kapur and Eva Schiller in Xcode using SwiftUI. The allergy detection process relies on text recognition for image techniques, which was implemented by Rhea Kapur and Eva Schiller using Google Cloud's Firebase ML Toolkit. The translation features were implemented by Olivia Taylor through Google's Cloud Translation API. Emma Huang created all visuals and product design features.

AllerScan won first place for the Best Use of Google Cloud prize, awarded by a team of Google engineers, at FemmeHacks 2021!

Check out the project listing on Devpost for screenshots and a demo video: https://devpost.com/software/allergy

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AllerScan is an allergy detection iOS application that scans food labels (in multiple languages!) for a given set of allergies. Built by Pingry students Rhea Kapur (Pingry '21), Eva Schiller (Pingry '21), Emma Huang (Pingry '21), and Olivia Taylor (Pingry '23) at FemmeHacks 2021.

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