The role of time series data in creating intelligent IIoT systems - with Evan Kaplan

Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – the platform which enables predictive maintenance at scale across all of your assets, across all of your plants.For this session, we were joined by Evan Kaplan, CEO of InfluxData, to discuss the role of time series data in creating intelligent IIoT systems. In this episode we:Discussed the significance of IIoT and the importance of time series data in monitoring and optimizing industrial processes.Explored real-world examples and case studies of industries successfully using time series data to enhance their IIoT systems.Covered the role of sensors in capturing data, challenges in data collection, and methods for storing and analyzing large volumes of time series data.Highlighted how time series data enables predictive maintenance and anomaly detection, preventing equipment failures and improving operational efficiency.Discussed emerging technologies, future trends, and the evolving role of time series data in advancing intelligent IIoT systems.Learn more about InfluxData: Website: InfluxDB | Real-time insights at any scale | InfluxDataFree Trial: Get InfluxDB | #1 Ranked Time Series Database | InfluxDataPlease subscribe via your selected podcast provider to be notified about future episodes.You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenance