Smart Online Warehouse Management Support System

This project aims to design and implement a Smart Online Warehouse Management Support System (MSS) tailored for retail stores. The proposed MSS will utilize modern web technologies and machine learning to offer decision-making support, automate routine warehouse tasks, and improve operational efficiency through predictive analytics and inventory forecasting. The system will serve as a centralized platform for warehouse administrators to manage product stocks, sales forecasting, performance tracking, and restocking suggestions.

System diagram of MSS

Installation

Install Smart Online Warehouse with client npm

  git clone https://github.com/sami5671/Smart_WareHouse_Management_System.git
  cd frontend
  npm install

To Run Client Site

  npm run dev

To Run Server Site

  cd backend
  npm install
  nodemon index.js

To Run ML Model

  cd ml_model
  pip install Flask flask-cors pandas scikit-learn matplotlib
  python app.py

Features

• Data Warehouse: Centralized storage for inventory, sales, and historical data
• BI Dashboards: Real-time visualizations using chart libraries (e.g., Chart.js or Recharts).
• Inventory Management Module: CRUD operations for product stock, category-wise filtering.
• Forecasting Module: Predictive ML model (Linear Regression/Random Forest) to estimate future sales and restock quantities.
• Stock Suggestion System: Rules-based engine (e.g., "low sales + high stock -> reduce order") to aid procurement decisions.

WareHouse Data

Predicted Result and Sales

Tech Stack

Client: React, TailwindCSS

Server: Node, Express

Python: Flask, flask-cors, pandas, scikit-learn, matplotlib

Author

• @sami5671