Open AccessProcrash: A Solution To Procrastination by Limiting Online Distractions using Optical Character Recognition
Author(s) -
Amanda Zhu,
Baoyu Yin,
Sun Yu
Publication year - 2021
Publication title -
international journal on computational science and applications
Language(s) - English
Resource type - Journals
ISSN - 2200-0011
DOI - 10.5121/ijcsa.2021.11402
Subject(s) - procrastination , limiting , computer science , character (mathematics) , internet privacy , world wide web , cloud computing , human–computer interaction , psychology , engineering , social psychology , mathematics , mechanical engineering , geometry , operating system
For this project, I decided to relieve the tension of procrastination that commonly happens in students and adults. To find a solution to this, I created a program that uses Google Cloud Vision API (Optical Character Recognition) to detect the distracting forms of media such as Twitter, YouTube, and Facebook, and counts the number of times the user visits these websites. After a certain number of visits, the program sends a notification to remind the user to stay focused. If the user ignores the notification message while staying on the unapproved website, the program forces the tab to close. This application was applied to a small user study where a qualitative evaluation of the approach was conducted. After collecting data for two weeks, it concluded that the program was able to effectively reduce and limit the uses of online distractions, allowing the user to manage their time more efficiently by staying off websites they should not visit.