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Mood Monitor

Mood Monitor is an Android application that users can use to track their daily activities like walking, jogging, sitting, standing, walking upstairs and walking downstairs. The application uses a Convolutional Neural Network (CNN) to predict user activity automatically and stores the information in a database stored on the phone. The users can then choose to visualize the statistics.

Java File Structure

  1. MainActivity

    • Registers/unregisters event listener
    • Records readings from the accelerometers
    • Calls RecognitionActivity for prediction and chooses activity with highest confidence score
    • Inserts a predicted activity to a SQLite database in the background

  2. RecognitionActivity

    • Initializes trained CNN classifier
    • Feeds normalized input into the classifier and sends output back to MainActivity

  3. DisplayStatsActivity

    • Queries the SQLite database to display pie chart on the screen

  4. Activity

    • Contains database schema in the form of objects (uses Room Persistence Library)

  5. ActivityDao

    • Provides interface to modify and query the database (through Data Access Objects)

  6. AppDatabase

    • Initializes an SQLite database for the application

  7. Constants

    • Holds constant values used in all class files