IIoT & Big Data in Machine Vision
March 17, 2020
Noon - 1 PM ET
ABOUT THIS WEBINAR
This webinar will cover advancements in IIoT and big data and the machine vision technologies that make it possible for a company to be a part of Industry 4.0 and the factories of the future. Networked machine vision is offering ways to harness and interpret an abundance of data, improve quality processes, and increase productivity. And thanks to ever-evolving technologies like deep learning based inspection and improved connectivity, the possibilities and value in machine vision are greater than ever.
Attendees can expect to learn:
- What challenges and benefits are inherent in IIoT and big data
- Methods for using data from machine vision, including reporting, normalization of data, and data integrity.
- Practical tips for making IIoT improvements to their operations.
SPONSORS:
IDS Imaging Development Systems GmbH
IDS Imaging Development Systems GmbH is a leading manufacturer of digital industrial cameras with USB 2.0, USB 3.0, USB 3.1 Gen 1 or GigE interfaces. True to our philosophy "It's so easy!" they are all perfectly compatible and easy to handle. Simplicity means efficiency. Our Ensenso 3D cameras represent a solution for 3D image capture that is impressively precise, cost-efficient and fast. Since it was founded as a two-person company back in 1997, IDS has developed into a successful, independent and ISO certified family company. Our approximately 240 employees around the world are real team players and work with joy and by conviction for you and your projects.
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Tom Brennan
Tom Brennan is president and founder of Artemis Vision, which builds repeatable, tested vision systems for automated inspection and quality control. An AIA Advanced Level Certified Vision Professional, he has been working in the industrial machine vision and imaging processing software market for the past ten years. He has successfully delivered numerous industrial machine vision systems for industries from medical to automotive to defense. Tom got his start in the vision industry designing machine vision vehicle detection algorithms as a research effort for the DARPA Urban Challenge, and holds a BSE in Computer Science from Princeton University.
