IntelliInspect
Real-Time Predictive Quality Control Using Kaggle Production Line Data
Project Overview
IntelliInspect is a comprehensive AI-powered web application that enables real-time predictive quality control using Kaggle production line sensor data. The system features an intuitive step-based workflow with seamless file uploads, advanced machine learning model training, and live prediction streaming.
The platform supports large-scale data handling with up to 2.5GB CSV uploads via chunked transfers, sophisticated date range segmentation, and fully containerized deployment using Docker.
Key functionalities include:
- CSV file upload with real-time progress and validation
- Date range configuration and validation against the dataset
- XGBoost model training with comprehensive performance metrics
- Real-time simulation and prediction streaming via WebSockets
- JWT-based authentication and role management
- Professional containerized deployment with Docker Compose
Key Documents
📋 Software Design Document
Comprehensive system design specification including architecture decisions, component relationships, and technical trade-offs in PDF format.
View Document🔗 API Contract
Complete API documentation with detailed request/response formats, endpoint specifications, and interactive examples.
View Documentation📅 Project Timeline
Detailed project milestones, development phases, and deliverable schedule with progress tracking.
View TimelineSystem Diagrams
🏗️ Software Architecture Diagram
Three-tier architecture showcasing Angular frontend, .NET backend, and Python ML service with Docker orchestration.
🔄 Data Flow Diagram
Complete data journey from CSV upload through model training to real-time prediction streaming.
Sample Data
📊 Kaggle Production Line Datasets
Pre-processed sample datasets for testing and demonstration purposes. These files contain synthetic timestamps and are ready for immediate use with the application.