Selection of the optimal location for installing smart banners on campus and an automated promotional materials management equipped with recommendation system.

• 1-classroom-data-EDA:
  EDA of student lecture data for optimal location of smart banners

• 2-classroom-data-visualization:
  Analyze the optimal location for installing smart banners with visualization

• 3-crawling-promotional-materials:
  Collection of promotional material data from various online communities

• 4-recommendation-system:
  Promotional material recommendation system

• 5-LSTM-material-subject-matching:
  LSTM model that suggests the categories of promotional materials registered by the users

• 6-app-implementation:
  App implementation using React Native, Flask, and MySQL

• Foot traffic of students was identified using student classroom/classtime data
• Visualization using the Folium library

• (Recommendation System) Hybrid recommendation system based on combination of simple recommendation, content-based filtering recommendation, and collaborative filtering recommendation
• (Category Predictor) LSTM model that suggests the categories of promotional materials registered by users