I-Corps: Translation Potential of Low-Cost Passive Radio Frequency Identification Tags

This I-Corps project is based on the translation from lab to market of low-cost passive radio frequency identification (RFID) tags. The tags track assets commonly used in firefighting such as hand tools or equipment within a few meters accuracy from a reader mounted on a mobile platform. During emergency situations such as wildfires, this technology tracks hundreds to thousands of individual items in a cost-effective way by using inexpensive, passive RFID tags. The commercialization of this solution has the potential to benefit the society by enabling better real-time situational awareness and better emergency response to more effectively.

This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. Passive radio frequency identification (RFID) tags are used to track individual items to within a couple of meters. This solution consists of novel machine learning algorithms used for identification that are capable of performing in a variety of forested environments. This solution is cost-effective and efficient, as RFID tags are inexpensive, do not require power, operate on the backscatter principle utilizing energy emitted by a nearby reader device, and do not require maintenance. The RFID tags provide a considerable advantage over conventional wireless technologies. The benefits of this approach include a reduction in the overall costs involved in tracking numerous assets and the development of a real-time situational awareness practical even during large fires.

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.

Award Number: 2514784
Principal Investigator: Sriram Narasimhan
Funds Obligated: $50,000
State: CA