From MQTT to AI Dashboards: Real-Time EV Data Monitoring with TDengine IDMP
TDengine
40:05
Electric vehicles generate massive volumes of telemetry data every second, from battery status and charging cycles to location and performance metrics. Turning that raw data into actionable insights requires real-time processing and intelligent visualization.
In this session, TDengine solutions architect Arun Arulraj will demonstrate how to build an end-to-end pipeline: ingesting EV telemetry data over MQTT, storing it efficiently in the high-performance time-series database TDengine TSDB, and transforming it into AI-powered dashboards with TDengine IDMP. In just 20 minutes, you'll see how to connect devices, manage large-scale data streams, and deliver instant insights for monitoring and decision-making.
Key takeaways:
- How to use TDengine TSDB's zero-code MQTT data connector
- How to manage data in the TDengine system
- How to use TDengine IDMP to perform AI-driven visualization and analysis of your data
Speaker
Arun Arulraj
Solutions Architect
Pursuing a Master’s Degree in Computer Science from the Georgia Institute of Technology and holding dual Bachelor’s degrees in Computer Science and Chemistry, Arun brings expertise in artificial intelligence, machine learning, and industrial data solutions to drive TDengine’s solution engineering efforts. Prior to joining TDengine, he worked as a Software Engineer at C3 AI and Meta, and served as Head of AI at Soundromeda, where he led the development of advanced AI-driven applications. He is currently based in California, USA.
From MQTT to AI Dashboards: Real-Time EV Data Monitoring with TDengine IDMP
40:05