Smart Basketball Court Management System

Overview

This project is an IoT solution for automating the lighting system of a high-traffic basketball court facility. Developed for a popular basketball hub in Colombo, Sri Lanka LOLC Basketball Court, this system seamlessly integrates reservation management with smart lighting control, enhancing operational efficiency and user experience.

Key Features

• Automated Lighting Control: Dynamically manages court lights based on real-time reservation data.
• API Integration: Fetches reservation data from a custom booking system API.
• IoT Device Management: Controls smart switches using the TinyTuya library.
• Intelligent Scheduling:
  • Implements complex scheduling logic including early morning activations, off-hours, and extended operation times.
• Fail-Safe Mechanisms: Robust error handling and status checking for reliable operation.
• Remote Monitoring: Includes a web interface for real-time system status monitoring and manual control.

Technical Stack

• Backend: Python
• IoT Communication: TinyTuya library
• Web Interface: Flask
• Deployment: Headless Raspberry Pi

System Architecture

1. Reservation Fetcher: Periodically retrieves booking data from the API.
2. Scheduler: Manages the timing of light operations based on reservations and predefined rules.
3. Device Controller: Interfaces with IoT switches to control the physical lighting system.
4. Status Monitor: Continuously checks device statuses and implements retry mechanisms.
5. Web Server: Provides a user interface for monitoring and manual control.

Setup and Configuration

Prerequisites

• Python 3.7+
• pip (Python package manager)

Required Libraries

Install the following libraries using pip:

pip install flask python-dotenv tinytuya schedule requests

Clone this repository:

git clone /~https://github.com/yourusername/smart-basketball-court-management.git
cd smart-basketball-court-management

Set up the environment:

a. If you have smart devices:

Create a .env file in the project root directory Add the following configurations to the .env file:

IS_PRODUCTION=true
API_URL=https://your-api-endpoint.com
API_SECRET=your_api_secret
HALF_COURT_A_ID=device_id_for_half_court_a
HALF_COURT_A_IP=ip_for_half_court_a
HALF_COURT_A_KEY=device_key_for_half_court_a
HALF_COURT_B_ID=device_id_for_half_court_b
HALF_COURT_B_IP=ip_for_half_court_b
HALF_COURT_B_KEY=device_key_for_half_court_b
FULL_COURT_ID=device_id_for_full_court
FULL_COURT_IP=ip_for_full_court
FULL_COURT_KEY=device_key_for_full_court

Replace the placeholder values with your actual device and API configurations

b. If you don't have smart devices:

You can use the mock setup included in the project. Create a .env file and set:

IS_PRODUCTION=false
API_URL=https://your-api-endpoint.com

This will use simulated devices for testing purposes

Running the Project

Start the web interface and the main application:

python web.py