A digital twin is a digital replica of a living or non-living physical entity. This session discusses the benefits and IoT architectures of a Digital Twin in Industrial IoT (IIoT) and its relation to Apache Kafka, IoT frameworks and Machine Learning.
Kafka is often used as central event streaming platform to build a scalable and reliable digital twin for real time streaming sensor data. A live demo shows a scalable digital twin infrastructure for condition monitoring and predictive maintenance in real time for a connected car infrastructure leveraging Kafka, MQTT and TensorFlow.
Key Take-Aways:
• Learn about use cases and characteristics of a digital twin in various industries
• Understand how to build a digital twin for every single (of tens of thousands) IoT device or machine
• See different IoT architectures with Kafka and other IoT technologies and products, including edge, hybrid and global deployments
• Understand the relation to Machine Learning and bring added value to your IoT infrastructure by enabling use cases like predictive maintenance
• Understand how the Apache Kafka enables scalable and flexible end-to-end integration processing from IIoT data to various backend applications
• Watch a live demo of an end-to-end integration, real time processing and analytics of thousands of IoT devices
More details:
[ Ссылка ]
[ Ссылка ]
[ Ссылка ]
