

This project is an AI-powered industrial energy monitoring platform designed to address real-world reliability and transparency challenges in industrial digitalisation systems.
The platform combines realtime energy monitoring, historical analytics, anomaly detection, and operational awareness into a unified production-oriented dashboard experience.
A key objective of the project is to move beyond traditional dashboards that only focus on data visualization. Instead, the system explicitly reflects backend worker states, data freshness, and system health to ensure that realtime information is never misleading when services become unavailable.
The architecture includes:
MES data ingestion workers AI anomaly detection workers Realtime and historical monitoring modes KPI snapshot management Worker-aware UI states Time-series analysis Industrial monitoring dashboards Backend APIs and microservices
Main Features:
Realtime industrial energy monitoring Historical analysis with selectable time ranges AI-based anomaly detection Worker health and availability tracking Snapshot-based KPI visualization Transparent realtime data freshness indicators Production-ready monitoring behavior Modular and scalable architecture