In this session, we will dive into building a comprehensive Edge/IoT anomaly detection solution by combining event-driven architecture with the power of local AI and Timeplus’ real-time SQL engine. Utilizing Ollama’s AI capabilities at the edge, we eliminate reliance on cloud infrastructure, resulting in a low-latency and highly scalable approach.

The session will cover how to integrate real-time and historical data for a rich context, essential for precise AI-driven applications, all within a streamlined SQL-based environment. This presentation will highlight an edge-based DDoS detection system as a practical example of event-driven IoT anomaly detection, showcasing how localized processing can provide rapid threat identification and mitigation.

Key Point
– How event-driven design enhances the responsiveness of IoT anomaly detection.
– Utilizing a simple SQL-based interface to develop LLM-powered AI applications with ease.
– Real-world application of a DDoS detector as an example of edge AI in action.

Edge AI and Anomaly Detection

Speaker

Gang Tao

CTO

Timeplus

Gang has over 20 years experience in software development, and is a recognized expert of AI, BI, Big Data and Data Visualization. He was...

More about Gang Tao