# Real-Time Location-Positioning Technologies for Managing Cart Operations at a Distribution Facility
## 1 Introduction  
Big data has been an emerging driver in recent years for the further creation of values for companies and organizations spanning different industries by generating higher revenues, facilitating operations, improving system efficiency and deriving hidden insights. The use of big data has become widespread and is observed to be rapidly growing in the business sector because of its potential to increase productivity and operating margins. According to a report published by McKinsey Global Institute [1], the utilization of big data is estimated to increase sector-wide productivity by at least 0.5% per year through 2020 and operating margins by more than 60%. In a more recent report [2], McKinsey Global Institute estimated that Internet of Things (IoT), which is one of the most critical enablers of big data, will bring a potential economic impact of as much as USD 11.1 trillion per year in 2025. There have been various uses of big data for supply chain management and these applications are promising. The big data levers include inventory management, distribution and logistics optimization, informing supplier negotiations, performance transparency and labor input optimization [1]. In this paper, we focus on one aspect of the use of big data: an application of radio frequency identification (RFID) technologies for managing cart operations in vast and highly dynamic distribution facilities. We alsopresent a real case study of an actual implementation of our proposed system in a large and high-traffic airmail center (AMC). This application can bring significant impact to supply chain management because the efficiency of distribution facilities has become remarkably crucial in the recent years of the age of electronic retailing. The gain in efficiency of a distribution facility is expected to reduce the delivery time of products, resulting in a higher level of customer satisfaction and so an increase in market share. RFID has been a key element in supply chains for over a decade. In 2003, Wal-Mart announced their plans for affixing RFID tags to the pallets and cases of the the items shipped by their major suppliers [3]. A year later, the Department of Defense of the United States finalized the guidelines on which suppliers are required to place RFID tags on their assignments of pallets, cases and precious items [4]. Since then, there have been various popular RFID applications, including monitoring cargoes and shipments [5] and tracking products at an item level for inventory control [6]. More recently, RFID has also been used within supermarkets for self-checkout [7] and tracking the flow of customers via tagged shopping carts [8]. The usage of RFID is expected to be expanding; according to [1], the number of RFID tags sold over the world is estimated to be 209 billion in the year of 2021. Our proposed system of locating carts at mail facilities is different from the traditional RFID applications and was motivated by a real-world problem; we developed an RFID infrastructure to enable tracking and tracing capabilities of carts at a large and high-traffic AMC. One of their major operational problems was that the carts loaded with mail bags were densely staged at the AMC and the staff members were spending a very long time searching for the carts of the departing flights in this highly dynamic environment. Because of this problem, we developed an RFID-based positioning system to help the staff members of the AMC locate carts in real time. This system can improve the operational efficiency of the facility, reduce misplacements of mail bags to flights and enable the capability of analyzing cart movements with the offline locational data. While there are already numerous successful applications of RFID for managing supply chains, to the best of our knowledge, this is the first paper that reports this novel application of RFID for tracking carts at distribution facilities to enhance throughput and operational efficiency.