Procrash: A Solution To Procrastination by Limiting Online Distractions using Optical Character Recognition


Corresponding Authors:
Amanda Zhu1, Baoyu Yin2 and Yu Sun3, 1USA, 2Lehigh University, USA, 3California State Polytechnic University, USA

Abstract

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.

Keywords

Procrastination, Optical detection, Software development.