An eXplainable AI system to elucidate short-term speed forecasts in traffic networks obtained by Spatio-Temporal Graph Neural Networks.

Traffic Congestion Prediction System using Data Mining

IFN-Transport is an extension of Ideal Flow Network (IFN) for transportation networks synthesis and analysis.

The project introduces a Multi-Stage Traffic Anomaly Analysis Framework for identifying and analyzing urban traffic congestion, particularly in Dhaka. Originally utilizing Faster R-CNN and DBSCAN, it has been upgraded to state-of-the-art YOLOv9e and YOLOv10l models for enhanced accuracy and efficiency.

Manhattan -- Traffic Congestion Zone -- Animated Map and Charts-- BranchAnalysis -- Python -- Public Data

shell script to fetch network statistics and monitor bottleneck issues on x64 device with wifi interface chip.

visualize congestion data of seoul subway line9