ITTIA DB Platform source code demonstrations help developers rapidly understand, evaluate, integrate, and deploy ITTIA technologies in real-world embedded and Edge AI applications. These demonstrations provide production-quality reference implementations and best practices that showcase deterministic data management, time-series processing, data ingestion, streaming analytics, feature engineering, AI-ready data pipelines, data synchronization, and visualization.
By presenting complete end-to-end solutions for use cases such as predictive maintenance, motor health monitoring, robotics, battery management, medical devices, and industrial automation, the demonstrations enable developers to accelerate learning, reduce integration risk, validate architectural decisions, shorten time-to-market, and gain confidence in deploying reliable, scalable, and intelligent edge systems using the ITTIA DB Platform.
Edge AI Medical Device Demo
This demonstration showcases how motor and actuator data from infusion pumps, medical robotics, ventilators, laboratory automation systems, and other intelligent medical devices can be acquired, processed, and managed deterministically at the edge. Attendees will see how current, vibration, temperature, speed, and operational telemetry are transformed into AI-ready features to enable motor health monitoring, anomaly detection, predictive maintenance, and reliable, explainable device intelligence directly on the medical device.
Edge AI Weather Station Monitoring Demo
This demonstration showcases how weather data, including wind speed, wind direction, temperature, humidity, and barometric pressure, is acquired, processed, and managed deterministically at the edge and transformed into AI-ready features for on-device inference. You will see how sensors, MCUs, Edge AI frameworks, and production-grade data management software work together to detect anomalies, identify environmental trends, and deliver real-time weather intelligence directly at the edge.
Edge AI Motor Health Monitoring Demo
This demonstration showcases how motor-related data, including current, vibration, temperature, and speed, is acquired, processed, and managed deterministically at the edge and transformed into AI-ready features for on-device inference. You will see how MCUs, sensors, Edge AI frameworks, and production-grade data management software work together to detect anomalies, predict failures, and deliver reliable motor health intelligence in real time.
