Recent Big Data Project : Load Prediction for a Power Transmission Organization

Agri-tech using Deep Learning

Objective: Deep-learning application for crop health, recommendations, weather forecasting, and farmer support.

Models: VGG16-based disease detection (93% accuracy), regression for crop choice and price trends, 12-day weather forecasts.

Stack: Python, TensorFlow, OpenCV, scikit-learn, Azure & Google APIs.

Power Transmission Prediction

This product for a power transmission company processes the SCADA measurement data for more than 200 substations and provides insight into data including anomaly detection, Peak Loads and prediction of future load. The sample screen attached shows prediction over a 24 hour period, comparing with previous 24 hour period. Historic data of last one year is used for prediction. Load Prediction Chart

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Agri-tech using Deep Learning

Power Transmission Prediction

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