Home Internet of Things Aerospace Apparel Energy Defense Health Care Logistics Manufacturing Retail

Machine Vision and RFID Improve Inventory Tracking

There is enormous potential to utilize both technologies in tandem for tracking applications.
By Megan Ray Nichols
Feb 16, 2020

You'll often see inventory-management experts comparing machine vision and radio frequency identification (RFID) technologies to each other when helping people determine which one would work best for their needs. However, a growing number of companies and academic researchers see abundant potential in using both of them together for tracking purposes. That concept is still in its early stages and not yet an idea that has hit the mainstream. However, it'll soon be clear why more people believe the two technologies can work together and need not remain separate.

RFID enables improved inventory tracking by using radio waves to read the digital data embedded in tags and labels. It's more advanced than bar codes because an RFID reader must only be in the range of a tag to read it. In contrast, bar codes require line-of-sight nearness. Computer vision is a subset of artificial intelligence (AI) concerned with teaching computers to get information from images or multidimensional objects. The technology can replace many instances of humans performing manual inspection tasks.

One company that offers computer vision tech integrated with drones for warehouse management can reduce costs by 60 percent compared to solutions that solely rely on people. Also, inspections that used to take eight hours can now be finished within 15 minutes.

Combining Computer Vision and RFID Technologies With Machine Learning
RFID and machine vision are both, in a broad sense, related to verification. Some brands noticed the connection and concluded that putting them into the same product would be a smart decision that would appeal to their customers.

Some companies go even further and build machines that include machine learning as well. Adding that capability allows for predictive insights. The equipment could learn the most likely locations of certain products in a warehouse, or what kinds of tags those things will have, saving time with tasks.

For example, Simbe Robotics evolved to meet changing customer needs when it released an RFID-enabled version of its computer vision robot, Tally. The bot also uses machine learning to work. RFID is particularly useful when checking stock levels of products that are not easy for a computer vision camera to discern.

Login and post your comment!

Not a member?

Signup for an account now to access all of the features of RFIDJournal.com!

Case Studies Features Best Practices How-Tos
Live Events Virtual Events Webinars
Simply enter a question for our experts.
RFID Journal LIVE! RFID in Health Care LIVE! LatAm LIVE! Brasil LIVE! Europe RFID Connect Virtual Events RFID Journal Awards Webinars Presentations