IoT & Connectivity

The IRIS IoT module is the data ingestion layer for your entire manufacturing operation. It collects telemetry from machines, sensors, PLCs, and edge gateways through a high-throughput HTTP API — normalizing, validating, and storing every data point in an optimized time-series database. Whether you're monitoring temperature, vibration, pressure, energy consumption, or custom process parameters, the IoT module handles it all at scale.

But data collection is just the beginning. Every telemetry reading is automatically evaluated against configurable alert rules, fed into AI/ML models for predictive analytics, and synchronized with Digital Twin simulations. The result is a closed-loop system where your physical assets and their digital representations stay perfectly in sync — enabling predictive maintenance, anomaly detection, and data-driven optimization across the entire plant.

With support for 10,000+ concurrent devices, edge computing for offline scenarios, and configurable data retention policies, the IoT module scales from a single production line to a multi-site enterprise deployment — without compromising on latency or reliability.

Every telemetry stream flowing through the IoT module is a training signal for IRIS's AI engine. The DATA_AI module continuously analyzes sensor data to detect anomalies that human operators would miss — subtle vibration pattern changes that predict bearing failure weeks in advance, temperature drift that signals calibration issues, or energy consumption spikes that indicate process inefficiency.

Machine learning models trained on your historical telemetry data provide predictive maintenance recommendations, automatically adjusting alert thresholds based on learned equipment behavior. Instead of static min/max rules, the system evolves with your operations — reducing false positives while catching genuine anomalies earlier.