Sports Event Management System

 

Sports Event Management System



This project is a sports event management application developed as part of a university database course. It provides a Java-based graphical interface that connects to an Oracle SQL database, allowing users to manage various aspects of sports events, including teams, workers, coaches, referees, materials, and collaborators.

Project Structure

The project is divided into two main components:

  1. SQL Database Structure: The system.sql file contains all the necessary tables and sample data to simulate a sports event. Key tables include:

    • PLAYS: Tracks players in matches.
    • COACH: Records coaching details.
    • MATCH_: Manages match details, including referees and courts.
    • MATERIAL: Stores information about the materials used in events.

  2. Java Application: Developed using the Model-View-Controller (MVC) pattern, the Java application includes modules for database interaction and interface control, allowing the user to add, update, and delete records.

Key Functionalities

  • Worker Management: Add, view, update, and delete workers assigned to events.
  • Collaborator Management: Track companies collaborating in each event and the resources they provide.
  • Match Management: Update referees and view match-related information.
  • Material Management: Manage materials, their providers, and usage in different event editions.

Installation

Prerequisites

  • Oracle SQL Database: Install and configure an Oracle SQL database, or use any other Oracle-compatible SQL database.
  • Java Development Kit (JDK): Version 8 or higher.
  • Eclipse IDE: Recommended for the Java application. The project uses the WindowsBuilder plugin for UI management.
  • SQL Developer (Optional): For managing the SQL database outside of the application.

Setup

  1. Database Setup

    • Execute the SQL commands in system.sql to create tables and insert initial data into the Oracle SQL database.
    • Update the database connection information in the Database.java file (e.g., host, port, SID, user, and password).

  2. Java Application Setup

    • Open the project in Eclipse IDE.
    • Ensure the jdbc library (included in the lib folder) is added to the project’s build path.

  3. Running the Application

    • Run the main class to launch the application.
    • Use the graphical interface to interact with the database for managing sports event data.

Future Enhancements

  • Security: Implement user authentication and encryption for sensitive data.
  • Extended Functionality: Add search, reporting tools, and data visualization features.
  • Internationalization: Support multiple languages and customizable formats for broader accessibility.












Comentarios

Publicar un comentario

Entradas populares de este blog

Sistema de Micrófono Inteligente para Localización de Fuentes Sonoras mediante Procesamiento de Señales

Imagen
  Smart Microphone with Sound Source Localization  h ttps://github.com/diegodl11/Smart-Microphones.git Explanation This project aims to design a  smart microphone  with the capability of  sound source localization . The system is composed of an array of multiple microphones that, through algorithms and signal processing, allows for highly precise determination of the location of a sound within an environment. Main Objective: The goal is to overcome the limitations of traditional sound localization methods by improving precision and sensitivity through an innovative and efficient system. An  Arduino microcontroller  is used for central processing, along with three microphones to capture sounds from different points and triangulate the position of the sound source. Key Components: Arduino  as the control unit. Three microphones  to capture sound waves and determine the location of the source using geometry. Bluetooth module  for wireless c...
Leer más

Procesamiento de imágenes multiespectrales con matlab

Imagen
  Multispectral Imaging in MATLAB https://github.com/diegodl11/Multispectral-Imaging-.git Introduction This project focuses on implementing and visualizing multispectral imaging techniques using MATLAB. Multispectral imaging captures information from multiple wavelengths across the electromagnetic spectrum, unlike traditional RGB images that capture only three bands. These images can be used for applications in agriculture, medical imaging, and remote sensing, among other fields. Project Overview This project uses MATLAB to load, process, and visualize multispectral images from different bands. It implements techniques for image filtering, contrast enhancement, and visual inspection of various bands, allowing users to observe features like vegetation health, water presence, and more. Prerequisites MATLAB installed with the Image Processing Toolbox. A multispectral image file (preferably in  .tif  format with multiple bands). How to Run the Code Load the Image : The path t...
Leer más