Smarter Internet of Things with Stream and Event Processing
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The meetup will be held on Google Hangouts and you will be able to watch the live stream directly on YouTube.
This is a virtual Meetup occurring at 8AM Pacific Time (11AM Eastern, 5PM Central European Time). For help with your timezone calculation, refer to this (https://time.is/compare/0800_20_Sept_2017_in_PT).
https://www.youtube.com/watch?v=mHcYkR1GsNA
Today, the Internet of Things is the one of the fastest growing innovative proving grounds of the industry. Everyone is trying to build better, faster, smarter products, but they are still in their infancy, especially regarding "true smartness". Aside from the nowadays widespread but possibly unfounded belief that AI will solve everything, many tough challenges remain, including how to help software make sense of the plethora of data our smart devices are collecting every second. Stream processing frameworks such as Apache Spark, Storm, Samza, and Flink are emerging to tackle this issue, however true smartness requires more.
In this talk, I will talk about how stream processors can be augmented or even replaced with more advanced complex event processing frameworks such as Drools Fusion or VIATRA-CEP, in order to solve typical IoT challenges such as on-the-fly filtering and high-level sensor data fusion for smart home gateways or smart sport equipment.
Speaker: Istvan Rath
Dr. Istvan Rath the CEO of IncQuery Labs Ltd. and he is also a research expert working for the Fault Tolerant Systems Research Group of the Budapest University of Technology and Economics. He is active in the Eclipse community as the co-lead of the VIATRA reactive model transformation framework (formerly known as EMF-IncQuery) and a regular presenter at EclipseCon conferences. He has more that 12 years of research and development experience, having contributed to many European and national research initiatives, startups, industrial collaborations and product development projects. His recent work focuses on smart and safe systems, complex event processing, and computer vision.
