Datasets:
Languages:
English
Size:
n<1K
Tags:
artificial-intelligence
industrial-ai
logistics-optimization
supply-chain-analytics
predictive-maintenance
smart-factory
License:
| license: mit | |
| task_categories: | |
| - tabular-classification | |
| - time-series-forecasting | |
| - anomaly-detection | |
| language: | |
| - en | |
| tags: | |
| - artificial-intelligence | |
| - industrial-ai | |
| - logistics-optimization | |
| - supply-chain-analytics | |
| - predictive-maintenance | |
| - smart-factory | |
| - industrial-iot | |
| - fleet-management | |
| size_categories: | |
| - n<1K | |
| # Industrial & Logistics AI Research Dataset Collection (2024 Edition) | |
| ## Overview | |
| This repository provides a structured collection of industrial and logistics datasets | |
| designed for artificial intelligence training, operational simulation, | |
| and supply chain optimization research. | |
| The datasets represent realistic industrial environments including | |
| manufacturing production lines, warehouse inventory systems, | |
| fleet management operations, predictive maintenance logs, | |
| smart factory automation metrics, port logistics throughput, | |
| and global trade analytics. | |
| All datasets are structured in CSV format and suitable for | |
| machine learning, forecasting models, anomaly detection systems, | |
| and industrial AI benchmarking experiments. | |
| --- | |
| ## Dataset Domains | |
| The collection includes: | |
| - Manufacturing Production Metrics | |
| - Warehouse Inventory Tracking | |
| - Fleet & Transportation Management | |
| - Supply Chain Delivery Performance | |
| - Predictive Maintenance Logs | |
| - Port & Maritime Logistics Throughput | |
| - Last-Mile Delivery Analytics | |
| - Demand Forecasting Data | |
| - Industrial IoT Sensor Monitoring | |
| - Transportation Cost Optimization | |
| - Export & Import Trade Statistics | |
| - Smart Factory Automation Performance | |
| --- | |
| ## Technical Characteristics | |
| - Structured tabular datasets | |
| - Time-series compatible format | |
| - Multi-domain industrial coverage | |
| - Suitable for supervised & unsupervised learning | |
| - Supports predictive analytics & optimization models | |
| --- | |
| ## Intended Applications | |
| This dataset collection can be used for: | |
| - AI model training for industrial systems | |
| - Logistics optimization research | |
| - Supply chain risk analysis | |
| - Predictive maintenance modeling | |
| - Smart factory efficiency benchmarking | |
| - Transportation cost modeling | |
| - Industrial anomaly detection | |
| --- | |
| ## Format | |
| All datasets are provided in CSV format. | |
| Each file contains clearly defined headers for structured data processing. | |
| --- | |
| ## License | |
| MIT License – Free for research and educational use. |