Machine Learning based feature extraction of electrical substations from satellite data. Powered by IEEE-ICETCI, RRSC-Central, NRSC, and ISRO, this project incorporates instance segmentation of substations using UNet, Albumentations for image augmentation, and OpenCV for computer vision tasks.

The Datasets contain a wide variety of network and physical behaviours of an IEC-61850-compliant zone substation. The datasets are compatible with actual substation network traffic, including benign GOOSE packets, MALICIOUS GOOSE packets, and benign SV packets. The datasets consist of two versions, including raw datasets and labelled datasets.

The Datasets contain a wide variety of network and physical behaviours of an IEC-61850-compliant zone substation. The datasets are compatible with actual substation network traffic, including benign GOOSE packets, benign SV packets, and MALICIOUS SV packets. The datasets consist of two versions, including raw datasets and labelled datasets.