Industrial assets are often in remote locations, yet they produce large amounts of critical data that can be used to improve safety, increase production, and reduce downtime. This session walks through how Cognite uses Cloud IoT Core to extract relevant data from ships at sea and how it optimizes data transfers to enable real-time aggregation, contextualisation, and ultimately visualization and prediction, leveraging, among other GCP technologies, Cloud Bigtable and Cloud ML Engine.
Serverless and Multi-Cloud API Management → https://bit.ly/2K7WlAr
Watch more:
Next ’19 IoT Sessions here → https://bit.ly/Next19IoT
Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions
Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform
Speaker(s): Stein H. Danielsen, Adam Michelson, Geir Kokkvoll Engdahl
Session ID: IOT201
product:Cloud ML Engine,TensorFlow; fullname:Jason Baek,Etsuji Nakai;
Related Post:
- IoT at the Edge: Bringing intelligence to the edge using Cloud IoT (Cloud Next ’18)
- Connect and Manage IoT Devices at Scale with Cloud IoT Core | Google Cloud Labs
- What is a Core i3, Core i5, or Core i7 as Fast As Possible
- IoT and Cloud for Industrial Applications (Google Cloud Next '17)
- Industrial Asset Maintenance with Google Cloud IoT and AR (Cloud Next ‘18)
- IoT and Cloud for Industrial Applications (Google Cloud Next ’17)
- Making an Internet of Things scale with PyPortal @adafruit #adafruit #iot #scale
- BITCOIN ⚠️How Bearish Is It REALLY? ⚠️❗️LIVE Crypto Analysis TA & BTC Cryptocurrency Price News
- Reveals ZEC’s plot to rig 2018 elections on an industrial scale: Jonathan Moyo strikes again
- Redis Edge On Azure IoT Edge