DeeptanshuM / Diario_MHacks9

iOS app coded at MHacks9 - hackathon at Univeristy of Michigan Ann Arbor - March 2017. Please checkout https://devpost.com/software/eventify-8chjzv to learn about the project.

Home Page:https://devpost.com/software/eventify-8chjzv

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What it does

We have created an app that uses an Optical Character Recognition API to parse and auto-fill information from images of event flyers to make creating reminders an easier process, in addition to allowing you to create reminders the ordinary way. If the reminder is urgent then our app becomes your personal assistant: it gives you a call to remind you about it - you can even select the song you want to hear in the call before the big event.

Some examples of when and how you can use it

Scenario 1 So the next time you are walking on campus and see a flyer to a talk you want to go to - simply snap a picture of the event flyer - our app will autofill most details for you - you have to do minimum work to create that reminder.

Scenario 2 You are your in calc class - the professor shows a slide - there's a morning exam coming up soon - snap a picture of the slide- our app will create a new reminder event - it will populate the date field for you and you set the other parameters - while you are at it, enter the name of the song you want to hear to get you in the right frame of mind before your test (we recommend Eye of the Tiger :) ) - on the morning of the exam our app will give you a wake up call - and you will wake up listening to the song of your choice to get you in the state of mind ready to take on the world- a good start to a day :)

How we built it

Google Cloud Vision, Firebase, Facebook Login SDK for Swift, Twilio, Swift, Python, Flask, Requests, CocoaPods, AVFoundations, CameraManager3.1

About

iOS app coded at MHacks9 - hackathon at Univeristy of Michigan Ann Arbor - March 2017. Please checkout https://devpost.com/software/eventify-8chjzv to learn about the project.

https://devpost.com/software/eventify-8chjzv

License:Apache License 2.0


Languages

Language:Swift 93.3%Language:Python 6.1%Language:Ruby 0.6%