Webinar
Time Series to Vectors: Leveraging InfluxDB and Milvus for Similarity Search
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What will you learn?
In this webinar, we’ll explain the powerful combination of time series data and vector similarity search to revolutionize urban traffic management. Learn how to transform raw sensor data from InfluxDB into meaningful vectors, enabling advanced pattern recognition and anomaly detection using Milvus, a high-performance vector database.
Through a practical use case of real-time traffic monitoring, we'll demonstrate how this innovative approach can swiftly identify and categorize traffic anomalies, from accidents to construction zones. This webinar is essential for data scientists, traffic engineers, and urban planners looking to harness the full potential of their time series data for complex, real-world applications.
Topics covered:
- Fundamentals of time series vectorization: Converting InfluxDB data for vector database use
- Integrating InfluxDB and Milvus for a comprehensive traffic monitoring solution
- Implementing similarity search in Milvus to classify traffic anomalies
- Best practices for real-time data processing and anomaly detection
Meet the Speaker
Join the session for live Q&A with the speaker
Anais Dotis-Georgiou
Lead Developer Advocate at InfluxDB
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.