However, the scale of modern retail operations makes even RFID scanning inefficient. Walmart, for instance, reported that in 2013 it lost $3 billion in revenue because of mismatches between its inventory records and its stock. Even with RFID technology, it can take a single large retail store three months to perform a complete inventory review, which means that mismatches often go undiscovered until exposed by a customer request.
To address this challenge, MIT researchers have developed a system that enables small, safe, aerial drones to read RFID tags from tens of meters away while identifying the locations of the tags with an average error of about 19 centimeters. Such a system could be used in large warehouses for both continuous monitoring, to prevent inventory mismatches, and location of individual items, so that employees can rapidly and reliably meet customer requests.
The central challenge in designing the system was that, with the current state of autonomous navigation, the only drones safe enough to fly within close range of humans are small, lightweight drones with plastic rotors, which wouldn't cause injuries in the event of a collision. But those drones are too small to carry RFID readers with a range of more than a few centimeters.
The problem was solved by using the drones to relay signals emitted by a standard RFID reader. This not only solves the safety problem but also means that drones could be deployed in conjunction with existing RFID inventory systems, without the need for new tags, readers, or reader software.
"Between 2003 and 2011, the U.S. Army lost track of $5.8 billion of supplies among its warehouses," says Fadel Adib, the Sony Corporation Career Development Assistant Professor of Media Arts and Sciences, whose group at the MIT Media Lab developed the new system. "In 2016, the U.S. National Retail Federation reported that shrinkage – loss of items in retail stores – averaged around $45.2 billion annually. By enabling drones to find and localize items and equipment, this research will provide a fundamental technological advancement for solving these problems."
The MIT researchers describe their system, dubbed RFly, in a paper they presented at the annual conference of the Association for Computing Machinery's Special Interest Group on Data Communications. Adib is the senior author on the paper, and he's joined by Yunfei Ma, a postdoc in the Media Lab, and Nicholas Selby, an MIT graduate student in mechanical engineering.