The Advantages of GigE Vision Connectivity for Embedded Vision

Embedded devices are significantly changing machine vision system design with their power and size advantages and edge processing capabilities well-suited to a wide range of traditional and emerging vision and sensor applications. One often overlooked element of embedded device design is networking and integration with other machine vision components and processing. Falconer outlines the opportunities and challenges when designing embedded devices for machine vision applications and highlights how software-based connectivity technologies can ease integration and networking hurdles by converting any device into a standardized GigE Vision, GenICam compliant device. By converting data from embedded devices into GigE Vision, end-users can employ off-the-shelf image processing software and evolve towards advanced factory automation applications, while GenICam allows users to continue to control devices.

About the presenter
James Falconer joined Pleora in 2010 as an application engineer and is now the product manager for the company’s machine vision connectivity products. He is responsible for the company’s hardware and software connectivity product roadmap. Falconer is Pleora’s representative on the Machine Vision Standards body and is vice-chair on the GigE Vision technical committee.