Equipped with a "vision-acoustic-digital signal" tri-modal fusion architecture, this engine supports AI visual measurement (error <3%), dust fan anomaly diagnosis (92% accuracy), and real-time clean transport vehicle data analysis. Distributed computing clusters train emission prediction models, simulating pollution dispersion across 2,000 plant monitoring points in 10 seconds and generating pre-emptive governance device strategies. As the foundational AI hub, it offers open data platform interfaces for extended applications like equipment health management and carbon footprint tracing, continuously expanding the industrial data universe.
Analyzes smoke plume opacity and stockpile coverage via cameras.
Diagnoses dust fan anomalies through noise frequency analysis.
Integrates DCS/PLC system data for real-time emission-energy-production profiling.
Trains trillion-parameter multimodal models (e.g., unorganized dust dispersion prediction, carbon emission tracing).
AI Acceleration Engine reduces governance strategy inference latency to <50ms.
Open APIs enable custom applications (e.g., transport vehicle scheduling, carbon asset reporting).
Nexora serves as the "Eye of Providence" for industrial sustainability—fusing image, sound, and time-series data to diagnose emission root causes and predict facility efficiency decay. It provides elastic computing power to Golden Connection and Synthex, boosting environmental decision speed by 85% and transforming data into a core asset for green transformation.