Overview

This repository contains files representing iterations in the simulation development process. The final result is located in the "simulation2" folder, with the main file being "v4_simulationWithCases.py". Sample event logs are stored inside folders.

Demo: https://vimeo.com/883906069/c506d45580

Simulation Overview

The code simulates the daily activities of users within a facility. Users move between different rooms, consume coffee, and respond to messages from an autonomous agent.

Constants

• SIMULATION_START_TIME: The start time of the simulation in minutes (9:00 AM).
• SIMULATION_END_DAYS: Number of days for the simulation (7 days).
• ROOMS: A list of rooms in the facility.
• MESSAGE_THRESHOLD: Number of coffees after which a stronger message is displayed.

User Class

Attributes

• user_id: Identifier for each user.
• sleep_pattern: Sleep pattern of the user (not explicitly used in the simulation).
• heart_rate: Initial heart rate of the user.
• current_room: The room where the user is currently located.
• case_id: Identifier for each case (day) of user activity.
• last_day: The last day the user was active.

Methods

• start_new_case(): Initializes a new case (day) for the user.
• move_between_rooms(): Simulates user movement between rooms, recording events.
• coffee_consumption(): Simulates coffee consumption and its effects on heart rate.
• respond_to_message(): Simulates the user's response to messages.

AutonomousAgent Class

Attributes

• users: List of users being monitored.

Methods

• monitor_users(): Monitors users and sends messages based on their heart rates.

CoffeeMachine Class

Attributes

• users: List of users.

Methods

• display_message(): Displays messages to users and records corresponding events.

Simulation Environment

• env: SimPy environment.

Simulation Execution

• Users, coffee machine, and an autonomous agent are created.
• Processes for user movement, coffee consumption, and agent monitoring are initiated in the simulation environment.
• The simulation runs for the specified number of days.
• User activity events are recorded in a CSV file.
• The plot visualizes user movement over time.

Visualization

• A plot is generated to visualize user activity over time.

Output

• The resulting CSV file (user_activity_log.csv) contains recorded events.
• A plot (user_activity_simulation.png) visualizes user activity.

This code provides a flexible framework for simulating user activities in a facility over multiple days, capturing events such as room changes, coffee consumption, and responses to messages.