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