Welcome to the IIoT Data Quality Assessment Service user documentation. This guide will help you understand and use all features of the application to analyze and assess the quality of your Industrial Internet of Things (IIoT) sensor data.
- Getting Started Guide - Installation, setup, and first steps
- Data Import Guide - Upload and import CSV sensor data files
- Data Loading Guide - Select machine groups and view sensor data
- Data Visualization Guide - Explore data through charts and advanced analytics
- Missing Values Guide - Identify and analyze missing data points
- Invalid Values Guide - Detect and understand invalid sensor readings
- Data Quality Guide - Comprehensive data quality assessment and metrics
- DQA Agent Guide - AI-powered chat assistant for data quality questions
- Troubleshooting - Common issues and solutions
- FAQ - Frequently asked questions
- Methodology and Innovation - Technical approach, value proposition, and innovation highlights
- Install and Setup: Follow the Getting Started Guide to set up the application
- Import Data: Use the Data Import Guide to upload your sensor data
- Explore Data: Start with Data Loading to select your machine group
- Analyze Quality: Use Data Quality for comprehensive assessment
The IIoT Data Quality Assessment Service is a full-stack web application designed to:
- Import sensor data from CSV files
- Visualize sensor readings through interactive charts
- Analyze data quality metrics including completeness, accuracy, and consistency
- Detect missing values and invalid readings
- Assess overall data quality with comprehensive reports
- Chat with an AI agent for data quality insights
Upload CSV files containing sensor data and metadata. The system validates files, detects machine types, and imports data into the database for analysis.
Explore your sensor data through various visualization types:
- Time series charts
- Correlation analysis
- Distribution plots
- Box plots
- Seasonal decomposition
- Anomaly detection
Comprehensive data quality analysis including:
- Completeness metrics
- Accuracy checks against thresholds
- Consistency validation
- Outlier detection
- Correlation analysis
Chat with the DQA Agent to get insights about your data quality, ask questions, and receive recommendations.
The application interface includes the following main pages:
- Home - Overview and quick access to all features
- Data Loading - Select machine groups and view raw/preprocessed data
- Data Visualization - Interactive charts and analytics
- Missing Values - Missing data analysis
- Invalid Values - Invalid readings detection
- Data Quality - Comprehensive quality assessment
- DQA Agent - AI chat assistant
- Check the Troubleshooting Guide for common issues
- Review the FAQ for answers to common questions
- Consult the specific feature guides for detailed instructions
- Main Project README - Project overview and technical details
- Backend API Documentation - API reference for developers
- Frontend Documentation - Frontend development guide
Last updated: Documentation version 1.0