Webinar Recap: Building an AI Anomaly Detection Pipeline with InfluxDB

In a recent webinar hosted by InfluxDB and HiveMQ, the focus was on how businesses can quickly deploy AI models for tasks like anomaly detection using new tools in the AI and database ecosystem. The demo application used HiveMQ and InfluxDB to collect sensor data from machines and analyze it with a machine learning model that monitors for anomalies. InfluxDB 3.0 was highlighted as a purpose-built tool for time series data workloads, offering improved write throughput and faster queries, while HiveMQ provided a platform for developing MQTT applications, including an embedded lightweight broker ideal for IoT use cases. Quix was also introduced as a platform to simplify the development of streaming applications, and Hugging Face offered tools and services for building and deploying machine learning models. The webinar demonstrated how these tools can be used together to create efficient anomaly detection pipelines.

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