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Machine Vision and RFID Improve Inventory Tracking
There is enormous potential to utilize both technologies in tandem for tracking applications.
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.
Combining Computer Vision and RFID Technologies With Machine Learning
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.
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