Author: Zach Winn | MIT News<\/p>\n
When you picture a worker at a retail store, you probably think of someone at a cash register or helping a customer. But employees also spend a lot of their time combing through stockrooms and shop floors, fulfilling requests or online orders and generally trying to keep track of all their inventory.<\/p>\n
Keeping track of inventory takes so much time, in part, because retailers don\u2019t always know where everything is located. That\u2019s why when you ask a store associate to check if they have a shirt in your size, it may take them 20 minutes to get back to you.<\/p>\n
Cartesian is helping retailers keep track of inventory with a technology invented at MIT. The system uses wireless signals from radio frequency identification (RFID) tags attached to items to find their precise location in a store, from the stockroom to the shop floor.<\/p>\n
Last year, Cartesian did a study with a retailer and found its platform delivered meaningful annual savings at the store level by streamlining inventory tracking, optimizing workflows, and improving customer experiences.<\/p>\n
\u201cThe big problem we\u2019re solving is that about 50 percent of working hours in retail stores go to managing inventory,\u201d says co-founder Fadel Adib SM \u201913, PhD \u201917, an associate professor at MIT. \u201cThat is roughly a $15 billion problem in the U.S. alone. We use algorithms to decipher indoor locations using wireless signals. The core technology enables a new level of indoor localization.\u201d<\/p>\n
Cartesian is already deployed in more than 700 stores across 15 countries and is working with one of the world\u2019s largest fashion groups, Inditex, which is the parent company to brands like ZARA, Pull&Bear, and Oysho.<\/p>\n
Beyond retailers and warehouses, Cartesian\u2019s platform could also improve indoor location tracking for manufacturers, logistics operators, and robotics companies.<\/p>\n
\u201cThe broad vision for what we are doing is spatial AI,\u201d says Adib. \u201cToday, AI does extremely well in the digital world. Now it has to move into the physical world. That means allowing machines to perceive their environment in such a way that they can interact with it. That\u2019s where spatial AI comes in and where Cartesian sits.\u201d<\/p>\n
From technology to product<\/strong><\/p>\n Adib, who holds a joint appointment in MIT\u2019s Media Lab and Department of Electrical Engineering and Computer Science, has been studying wireless signals at the Institute for more than 15 years, dating back to research during his master\u2019s degree.<\/p>\n \u201cMy group today researches how to use wireless signals to sense the world in ways that were not possible before,\u201d Adib says. \u201cWe develop the fundamental technology and then we build systems around them. Our goal is to see these systems deployed in the real world for impact.\u201d<\/p>\n When Adib joined MIT\u2019s faculty, the first project he worked on was indoor localization using RFID tags. Isaac\u00a0<\/strong>Perper \u201920, MEnG \u201921 later joined his lab as a student, and together they developed machine-learning algorithms to process RFID data to translate them into location patterns, with an initial focus on helping robots locate RFIDs indoors.<\/p>\n In 2021, Adib went through the National Science Foundation\u2019s I-Corps program, which challenges researchers to interview potential customers to find the right problems to solve with their technologies. That\u2019s when he realized how big of a problem inventory management is for retailers.<\/p>\n Cartesian was officially founded by Adib and Perper\u00a0<\/strong>in the beginning of 2023, after they received a small business award from the National Science Foundation. The pair worked with MIT\u2019s Technology Licensing Office to license patents from Adib\u2019s lab. They also received support from MIT\u2019s Venture Mentoring Service.<\/p>\n \u201cOur goal was to reduce the cost of the technology to make it scalable,\u201d Adib recalls. \u201cIsaac focused on simplifying the product, leveraging progress in machine learning, and making it fast. It was a lot of iterating and testing early on.\u201d<\/p>\n Retail workers spend much of their time locating items for a number of reasons. They might get an online order to fulfill, need to restock store shelves, or get a customer inquiry about items in the back.<\/p>\n Stores differ in how they organize their inventory. Most separate items by categories in specific shelves and bins then use barcodes or inventory systems that tend to get outdated fast.<\/p>\n \u201cIt\u2019s a big problem for stores because customers may just leave before asking an employee to look for their size, or customers may get frustrated and leave if it takes too long,\u201d Adib says. \u201cThe associate also wastes time looking for items they could spend doing higher-value work.\u201d<\/p>\n Cartesian\u2019s platform works with retailers\u2019 existing handheld RFID readers, which store associates already use to manage inventory. Each store installs Cartesian\u2019s software into their existing inventory apps or uses a custom app for employees to access directly.<\/p>\n \u201cThe RFID readers are how stores tell what\u2019s in stock and what\u2019s out of stock,\u201d Perper\u00a0<\/strong>says. \u201cWe figured out a way to leverage the same scans they\u2019re already using with the reader, put the data they generate into our machine-learning algorithms, and generate maps of where all the items are.\u201d<\/p>\n Customers can build analytics on top of Cartesian\u2019s technology to keep track of inventory levels, show customers maps of where each item is located, and create other services.<\/p>\n \u201cThey use our location intelligence platform and build different products on top,\u201d Adib says. \u201cWe can work with any device, any store, any type of RFID. It\u2019s a simple interface. All the sophisticated location algorithms sit in the cloud.\u201d<\/p>\n Beyond retail<\/strong><\/p>\n Cartesian signed its first big contract in 2025 and soon expanded to several hundred stores. One of Cartesian\u2019s advantages is its ability to quickly scale. Perper says they can add a store in about one minute. Cartesian\u2019s team doesn\u2019t even have to travel to a new store to turn on its system if it\u2019s already working with the company.<\/p>\n \u201cIt\u2019s as simple as flipping a switch, preparing the data, and sending it to our customers,\u201d Perper says. \u201cOne of our first big bets was, \u2018Can we build this entirely on existing hardware?\u2019 That bet is starting to pay off.\u201d<\/p>\n Cartesian\u2019s models can also work with Wi-Fi and Bluetooth signals, which the company plans to use with customers in other verticals.<\/p>\n \u201cRight now, we\u2019re focused on applications in retail, but this technology has a lot of value in manufacturing, warehouses, and other locations,\u201d Adib says.<\/p>\n Cartesian\u2019s team aims to be deployed in tens of thousands of stores over the next year and then begin expanding beyond retail into industries like manufacturing and robotics.<\/p>\n \u201cWhat\u2019s most exciting about Cartesian to me is we\u2019ve built a lot of the technology foundation, and now that we have the fundamentals in place, we hope to build specific application layers,\u201d Perper says. \u201cThen we can ask customers in different verticals about their problems and apply our technology in different ways to solve it.\u201d<\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"