Our Inspiration
42% of Canadians between the age of 16 and 65 have low literacy skills and over 50% of working adults have insufficient health literacy skills. While with every passing day, technology continues to evolve at staggering rates, literacy skills have not changed. Reading and note taking, two of the most quintessential skills in education have remained stale for several decades. With this problem in mind, we designed and developed Noter, the note taking program ready to revolutionize education.
What does it do?
Noter utilizes natural language algorithms and statistics to help users understand complex texts better and faster. Noter currently allows users to paste text to be analyzed, however, Noter will soon offer OCR functionality by incorporating Google's Cloud Platform for Vision as well. OCR functionality will allow users to take pictures and even scan textbook pages which can then be analyzed. Noter currently acts as a stand alone Python desktop application, but will soon be available for mobile operating systems (Android and IOS) as well as web based platforms. Noter begins by emphasizing main ideas in the text to the user by either bolding or highlighting keywords based on importance and relevance to the overall text. Aside from emphasizing key ideas and words, Noter also provides the user with a glossary with easy access to quick definitions through a single click. In the future, Noter will also be capable of saving the notes which it created for future reference by the user.
How does it work?
All of the software for Noter is written in Python which incorporates various packages and libraries. Noter begins by analyzing the text which the user inputs using Google's Natural Language API. After some further analyses, keywords are chosen to be emphasized and to be put in the glossary. Between analysis, data is always stored in JSON format.
Challenges we ran into
Initially, we were planning on developing an Android application which would incorporate OCR (Optical Character Recognition) to accomplish the same goals as Noter. However, we came to realize that our Android development experience as a team was not enough to successfully accomplish our goals. However, we managed to pivot our focus and create a desktop application instead. Another problem which we ran into was that
Accomplishments that we're proud of
Utilizing JSON to store and transfer data. We are very proud of this accomplishment because JSON is something which none of us were familiar with coming in to this Hackathon.
Designing and implementing a user interface completely within Python. At the beginning of the Hackathon, none of us believed that Python could be used for any form of front end developement, however, Noter is written completely in Python.
What's next for Noter
Multi-platform support: Noter will eventually come out for IOS, Android and Web based platforms to make it even more accessible to it's target demographic.
Optical Character Recognition: Noter will use Google Cloud's Vision API to convert pictures which users take to text which can then be analyzed and annotated with ease.
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