Inventory Management System - Prototype

🖥️ System Overview

This repository features a fully functional, three-tier desktop application built entirely from scratch without heavy framework layers. It integrates an offline-first HTML5 and JavaScript user dashboard directly with a native backend Java web server, allowing immediate data streaming out of a localized PostgreSQL database.

Development Methodology: This system was built using a systematic back-to-front approach. The foundational database schemas and constraints were established first, followed by wiring the Java server socket controllers, and finally constructing the frontend dashboard to display the processed data streams securely.

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🎯 The Business Problem

Many industrial warehouses rely on slow, manual spreadsheet entries or paper logbooks to track stock. This manual process causes delayed reporting, human calculation errors, stockouts, and massive waste of operational resources.

💡 The Engineered Solution

This application completely automates inventory tracking and reporting. By building a direct data pipeline, warehouse managers can view real-time stock levels and calculate bulk order metrics instantly with a single click. This eliminates manual logs, saves operational hours, and prevents wastage of warehouse resources.

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📸 System Preview

1. Web Operations Dashboard

This is the webpage where users click a button to pull live data from the database instantly without reloading the page:

2. Java Backend Web Server

This is the backend Java program running in the terminal. It listens for web requests and streams database records back to the webpage:

3. PostgreSQL Database Terminal

This is the local database terminal where we run scripts to build tables and insert our 19 default inventory rows.

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🛠️ Tech Stack Used

• Operating System: Linux Ubuntu (VirtualBox Environment)
• Database: PostgreSQL SQL Database
• Backend Language: Java (Version 11)
• Web Server Engine: Java Built-in HttpServer Framework
• Frontend Interface: HTML5/CSS3 and JavaScript (Fetch API)

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🗂️ Project Directory Structure

This map shows the location of every file created inside the project:

~/ifs-warehouse-db/
├── index.html               # Frontend dashboard viewport page (HTML, Local CSS, JS Fetch)
├── postgresql.jar           # Database driver package file (The Translator Bridge)
├── README.md                # System documentation and setup guide
├── LICENSE                  # Open-source MIT License terms and conditions
├── images/
│   ├── web-dashboard.png    # Frontend dashboard interface screenshot
│   ├── backend-server.png   # Active Java backend server console log preview
│   └── database-terminal.png # Terminal view of database connections and queries
├── schema/
│   └── schema.sql           # Database table structural blueprints
├── seeding/
│   └── seeding.sql          # Core inventory data records (19 initial entries)
├── queries/
│   └── analytics.sql        # Reference SQL JOIN calculation script
└── src/
    └── WarehouseApp.java    # Monolithic Java Backend Source Code

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📋 System Prerequisites

You must install the following software packages before running the application:

1. Java Development Kit (JDK 11 or higher): Required to compile and run the Java server.
   • Ubuntu command to install: sudo apt install default-jdk
2. PostgreSQL Server: Required to host the local database vault.
   • Ubuntu command to install: sudo apt install postgresql postgresql-contrib
3. Git: Required to clone the project files from GitHub.
   • Ubuntu command to install: sudo apt install git

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📟 Setup and Execution Guide

Follow these steps in order to download, build, and run the application:

Step 0: Clone and Enter the Project Folder

Open your Linux terminal, download the repository, and enter the main project folder:

# Clone the repository onto your machine
git clone https://github.com

# Move into the project directory
cd ifs-warehouse-db

Step 1: Initialize and Seed the Database

Run this command to create your database tables and insert the 19 default transaction records:

sudo -u postgres psql -d ifs_warehouse -f schema/schema.sql -f seeding/seeding.sql

Step 2: Configure Database Password Security

Update your PostgreSQL user permissions to authorize backend data connectivity:

sudo -u postgres psql -c "ALTER USER postgres WITH PASSWORD 'postgres';"

Step 3: Compile the Java Backend Code

Compile the Java source code while linking the required PostgreSQL driver package:

javac -cp .:postgresql.jar src/WarehouseApp.java

Step 4: Run the Application Engine

Launch the application and open the interactive main menu:

java -cp src:postgresql.jar WarehouseApp

Step 5: Start the Web Server API Panel

When the terminal menu appears, type option 2 and press Enter. This instructs Java to listen for incoming web requests on port 8080.

Step 6: Open the Dashboard in Your Browser

You can open the user interface using either of the following methods:

• Method A (Java Server): Open a browser tab and go to: 👉 http://localhost:8080/
• Method B (VS Code Live Server): Right-click index.html in VS Code and select Open with Live Server to access: 👉 http://127.0.0.1:5500/index.html.

Click the EXECUTE LIVE PORT POLL button. The dashboard will instantly fetch your live database records without reloading the page!

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📊 Core Analytical Query (queries/analytics.sql)

This is the database query the backend executes to calculate inventory metrics across multiple tables:

SELECT products.product_name, products.stock_level,
       SUM(purchase_orders.order_quantity) AS total_ordered
FROM purchase_orders
INNER JOIN products ON purchase_orders.product_id = products.product_id
GROUP BY products.product_name, products.stock_level
ORDER BY total_ordered DESC;

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Optional: Verify Your Database Tables

If you want to log into your PostgreSQL database manually to verify that your tables loaded correctly, run these quick commands in your terminal:

1. Log in to the database:

   sudo -u postgres psql -d ifs_warehouse

2. List all active tables: Type \dt and press Enter to see your products and purchase_orders tables.
3. Print your rows: Type SELECT * FROM products; to view your data records.
4. Exit the database: Type \q to return to your normal terminal prompt.

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🧠 Lessons Learned

• System Architecture: Learned and gained some knowledge on the architecture behind full-stack development.
• Database Integration: Practiced how database tables pass records up to a backend server.
• Browser Connections: Handled how a webpage talks to an active server over local network ports.
• Offline Performance: Learned how to make a webpage load instantly from a local drive without needing the internet

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🤝 Acknowledgments & Collaboration

• AI Collaboration: Developed in partnership with Google AI as an engineering peer. Used Google AI to brainstorm system architecture, troubleshoot cross-origin network ports, and refine professional code documentation.

🚀 Future Upgrades

1. Two-Way Data Flow (Write Access): Add an HTML input form to allow operators to insert new records into the database directly from the browser window.
2. JSON Data Serialization: Convert the Java API output from raw text tables into standard JSON format arrays.
3. Data Visualizations: Connect the JSON stream to a JavaScript charting library (like Chart.js) to display dynamic inventory graphs.