This project aims to develop an AI-powered smart grid monitoring platform using low-code tools integrated with predictive analytics APIs. The system forecasts electricity load patterns and generates automated grid optimization recommendations.
Integrate energy load prediction API.
Design simulated grid data ingestion module.
Implement AI-based load forecasting logic.
Configure automated overload alert workflows.
Build dashboards showing load distribution trends.
Develop optimization recommendation engine.
Conduct predictive accuracy testing.
Document integration architecture.
Present real-time load prediction demonstration.
