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NMP-Detector

Made with Python Flask, Dash

Made for KAIST Undergraduate 2020 Spring Semester [IE481]: Special Topics in Industrial Engineering (Data Visualization) Class

** Service discontinued

Background

This application was developed for the [IE481] Special Lectures in Industrial Engineering (Data Visualization) class in the 2020 spring semester at the Korea Advanced Institute of Science and Technology (KAIST), taught by Professor Uichin Lee. The application was created by students Jae Sung Park and Geon Ho Lee

Motivation

Nomophobia. A relatively new word defined as the fear of not having your phone with you. Do you think you suffer from symptoms of Nomophobia? Just a decade ago people would’ve laughed at the idea of being scared of not having your phone with you, but it’s become a real medical problem in the modern internet-connected world. It’s become the norm to take out your smartphone from your pocket, unlock the phone with a simple fingerprint, and scroll through the endless Tartarus of news feeds, attempting to satisfy an insatiable hunger for virtual stimulation for hours at a time. It’s just too easy and enjoyable. This means it’s too easy to develop symptoms of NMP as well. Such habits can lead to a whole wave of health issues both physiologically and psychologically.

The need for self-monitoring our smartphone usage is clear. There is an overwhelming amount of evidence of the negative effects of smartphones. Similarly to how people self-monitor their food intake so that they don’t suffer from obesity, people should be self-monitoring their smartphone usage.

Data Visualization

Three forms of visualization were applied in making the web application:

  • Gantt Chart
  • Horizontal Bar Chart
  • Grouped Bar Chart

The visualizations were made using Plotly.

Use of Data

Sample data provided by the KAIST K-EmoCon & K-EmoPhone project was used in visualization. A End-User License Agreement (EULA) was signed. In the web application, partial data about only one anonymous participant was used for data visualization solely for educational purposes.

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  • Python 50.7%
  • HTML 35.5%
  • CSS 13.8%