Industrial Evolution Conference 2023

calendar iconWhen
April 13, 2023
location iconWhere
Online
person iconWhat
Virtual Conference
Intellias logo (1)

Welcome to Industrial Evolution 2023, an international virtual conference by Intellias, dedicated to exploring the latest trends, technologies, and applications in the industrial Internet of Things landscape.

The event will gather expert speakers from the manufacturing, construction, industrial automation and software engineering domains, who will share their insights and experience in the field of Industry 4.0 along with practical aspects of implementing IoT solutions.

Meet our expert

 Serhii Seletskyi

Serhii Seletskyi

Head of Architecture & IoT Practice Leader at Intellias

At Intellias, Serhii helps companies harness the right IoT technology stack to scale business and make it future-proof. Strategic thinker with extensive knowledge of the IT Industry in a wide variety of innovative solutions for different business domains.

During the conference, he will share his insights on Azure IoT Digital Twins.

Jonathan Weiss

Jonathan Weiss

global GTM leader, works with industrial manufacturing and AWS strategic industries

As an accomplished innovation and technology executive, Mr. Weiss specializes in partnering with leading manufacturers to drive cost reduction, improve operational efficiencies, and enhance supply chain resilience through the implementation of advanced technologies such as IoT, Industrial IoT, AI, and ML.

During the event, he will speak about the future of manufacturing under the topic Unlocking the Promise of Industry 4.0 (and beyond).

Serdar Uckun

Serdar Uckun

founder and CTO at Novity

Mr. Uckun has more than 15 years of management experience with in depth expertise in genomics, biotech, information technology, systems engineering, artificial intelligence (AI), and data science.

At the conference he will talk about predictive maintenance for manufacturing, a relatively new maintenance approach based on monitoring critical assets’ health and predicting failures in advance.

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