PFI-TT: Bridging the Information Gap in Supply Chain using Internet of Things (IoT)

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to address multi-billion dollar challenges facing supply chain logistics. The complexity of today’s supply chains makes it difficult to optimize micro-logistics processes such as quality control, inventory tracking, re-stocking, traceability, deadline projections, and indoor transport.

This project will develop a novel system that can identify and locate billions of items in a scalable, cost-effective, and reliable manner. The resulting system may bridge the physical with the digital world, providing significant visibility and analytics to improve processes and save costs. The innovations in this research may advance scientific and technological understanding of how to design and build practical, scalable, and robust micro-location systems.

The primary educational outcome of this program is to train entrepreneurial leaders that are capable of building strong, diverse teams and leading these teams toward societal impact through commercialization. Furthermore, the program includes various activities to ensure broad participation of students and researchers from under-represented demographics.

This project focuses on designing and building a practical, scalable system for tracking Radio Frequency Identification (RFID) tags. RFIDs are passive, inexpensive (3-cent) tags that have already been deployed in the hundreds of billions as barcode replacements by many industries. Unfortunately, existing RFID solutions are too coarse and inaccurate for high-precision tracking, especially in highly dynamic and harsh environments such as warehouses, outlets, and factories.

To address this challenge, a new RFID sensor is proposed that is highly accurate (i.e., sub-centimeter), robust (i.e., multipath resilient), and cost-effective. The new sensor uses a novel radar-inspired RFID positioning module for time-of-flight measurement and a split-computing framework for efficient and low-cost location extraction. A distributed sensor network architecture will be used to scale across large areas.

The main goal of this project is to provide an easy to deploy and scalable solution that is horizontal across various applications and use cases in the supply chain.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.