Identification of rfid tags from a sensor field using uavs

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Abstract

Radio Frequency Identification (RFID) technology is widely used in scientific and engineering applications, including integration with Unmanned Aerial Vehicles (UAVs) for object identification in hard-to-reach environments. Two key performance characteristics of such systems are the probability of successful tag reading and the reading time, both of which can be quantitatively described using semi-Markov process models. This paper considers two fundamentally different scenarios. In the first scenario, tags are sparsely distributed, which eliminates collisions. An analytical model is proposed to describe the interaction between the reader and a single tag. In the second scenario, densely placed tags lead to collisions. To evaluate system performance in this case, a discrete-event simulation model is developed. The model takes into account the specifics of the EPC Gen2 protocol, radio channel parameters, spatial configuration of tags, and data reading strategies. The paper compares analytical and simulation results and investigates how tag density, data volume, and UAV altitude affect reading performance metrics.

About the authors

Vilmen Vil'men Abramian

V.A. Trapeznikov Institute of Control Sciences of RAS

Author for correspondence.
Email: abramian.vl@phystech.edu
Moscow

References

  1. 1. CHOI H.W., KIM H.J., KIM S.K. An Overview of DroneApplications in the Construction Industry // Drones. – 2023. –Vol. 7, No. 8. – Art. No. 515.
  2. 2. FINKENZELLER K. RFID Handbook. – New York: JohnWiley and Sons, 2003.
  3. 3. GOPE P., MILLWOOD O., SAXENA N. A Provably SecureAuthentication Scheme for RFID-Enabled UAV Applications //Computer Communications. – 2021. – Vol. 166. – P. 19–25.
  4. 4. GORTSCHACHER L.J., GROSINGER J. UHF RFID SensorSystem Using Tag Signal Patterns: Prototype System // IEEEAntennas and Wireless Propagation Letters. – 2019. – Vol. 18,No. 10. – P. 2209–2213.
  5. 5. LARIONOV A.A., IVANOV R.E., VISHNEVSKY V.M.UHF RFID in Automatic Vehicle Identification: Analysis andSimulation // IEEE J. Radio Freq. Identif. – 2017. – Vol. 1,Iss. 1. – P. 3–12. – doi: 10.1109/JRFID.2017.2751592.
  6. 6. LAZARO A., GIRBAU D., VILARINO R. Effects ofinterferences in UHF RFID systems // Progress InElectromagnetics Research. – 2009. – Vol. 98. – P. 425–443.
  7. 7. LI C. et al. ReLoc 2.0: UHF-RFID Relative Localizationfor Drone-Based Inventory Management // IEEE Trans. onInstrumentation and Measurement. – 2021. – Vol. 70. – P. 1–13. – Art. No. 8003313. – doi: 10.1109/TIM.2021.3069377.
  8. 8. LONGHI M., MARROCCO G. Ubiquitous Flying SensorAntennas: Radiofrequency Identification Meets Micro Drones //IEEE Journal of Radio Frequency Identification. – 2017. –Vol. 1, No. 4. – P. 291–299.
  9. 9. LONGHI M., CASATI G., LATINI D. RFIDrone: PreliminaryExperiments and Electromagnetic Models // Proc. of the 2016URSI Int. Symposium on Electromagnetic Theory (EMTS-2016). – 2016. – P. 450–453.
  10. 10. LUBNA et al. IoT-Enabled Vacant Parking Slot DetectionSystem Using Inkjet-Printed RFID Tags // IEEE SensorsJournal. – 1 April 2023. – Vol. 23, No. 7. – P. 7828–7835.
  11. 11. MA Y. et al. RAPP: A Radio Tomography Localization MethodCharacterized by Performance Parameterization in Rapid-Moving RFID System // IEEE Trans. on Vehicular Technology. –2023. – Vol. 72, No. 1. – P. 1265–1278.
  12. 12. MOHSAN S.A.H., OTHMAN N.Q.H., LI Y. et al. UnmannedAerial Vehicles (UAVs): Practical Aspects, Applications, OpenChallenges, Security Issues, and Future Trends // IntelligentService Robotics. – 2023. – Vol. 16, No. 1. – P. 109–137.
  13. 13. NIKITIN P.V., RAO K.V.S. Performance limitations of passiveUHF RFID systems // IEEE Antennas and PropagationSymposium. – 2006. – P. 1011–1014.
  14. 14. QUINO J., MAJA J.M., ROBBINS J. et al. RFID and Drones:The Next Generation of Plant Inventory // Agri. Engineering. –2021. – Vol. 3, No. 2. – P. 168–181.
  15. 15. QUINO J., MAJA J.M., ROBBINS J. et al. The Relationshipbetween Drone Speed and the Number of Flights in RFID TagReading for Plant Inventory // Drones. – 2022. – Vol. 6, No. 1. –doi: 10.3390/drones6010002.
  16. 16. EPC TM Radio-Frequency Identity Protocols Generation-2 UHFRFID Standard. Specification for RFID Air Interface Protocolfor Communications at 860 MHz – 960 MHz, rel. 2.1. –Wellington: EPCGlobal, 2015.
  17. 17. SHARMA D.K., MAHTO R.V., HARPER CH. et al. Role ofRFID Technologies in Transportation Projects: A Review // Int.Journal of Technology Intelligence and Planning. – 2020. –Vol. 12, No. 4. – P. 349–377.
  18. 18. TAJIN M.A.S., JACOVIC M., DION G. et al. UHF RFIDChannel Emulation Testbed for Wireless IoT Systems // IEEEAccess. – 2021. – Vol. 9. – P. 68523–68534. – doi: 10.1109/ACCESS.2021.3077845.
  19. 19. XU H., YIN X., ZHU F. et al. RF-Ray: Sensing Objects inthe Package via RFID Systems // IEEE Systems Journal. –March 2023. – Vol. 17, No. 1. – P. 558–568. – doi: 10.1109/JSYST.2022.3196462.
  20. 20. XUE C., LI T., LI Y. et al. Radio-Frequency Identification forDrones With Nonstandard Waveforms Using Deep Learning //IEEE Transactions on Instrumentation and Measurement. –2023. – Vol. 72. – P. 1–13. – Art. No. 5503713. – doi: 10.1109/TIM.2023.3306822.

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