Enhancing IIoT Efficiency with Digital Twins: Scalable Data Pipelines
Session date: Nov 07, 2024 08:00am (Pacific Time)
In this hands-on training, we explore the development of scalable data pipelines for Industrial IoT (IIoT) applications using a dynamic set of technologies, including Kafka, Faust, Telegraf, and InfluxDB. We will focus on the application of digital twins in the context of Continuous Stirred-Tank Reactors (CSTRs), demonstrating how digital replicas of these reactors enhance monitoring and operational capabilities in chemical processes.
By simulating CSTRs in real-time, digital twins facilitate precision in analytics and proactive decision-making. This approach not only focuses on building efficient, real-time data pipelines capable of handling high throughput but also optimizes the performance of industrial operations in manufacturing, energy, and other sectors.
In this training, you will learn:
- The advantages of using InfluxDB for IIoT data collection and analysis.
- How to leverage Faust, Kafka, and Telegraf to build scalable data pipelines.
- The significant role of digital twins in improving the efficiency and safety of CSTR operations, enabling sophisticated and effective data processing without relying on machine learning models.
Anais Dotis-Georgiou
Developer Advocate, InfluxData
Anais Dotis-Georgiou is a Developer Advocate for InfluxData with a passion for making data beautiful with the use of Data Analytics, AI, and Machine Learning. She takes the data that she collects, does a mix of research, exploration, and engineering to translate the data into something of function, value, and beauty. When she is not behind a screen, you can find her outside drawing, stretching, boarding, or chasing after a soccer ball.
