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An Anti-Collision Scheme for RFID for Patient Tracking Using Linear Interpolation Estimation.

¹Providence University, Taiwan Blvd Sec 7 No 200, Taichung City, 433, Taiwan. bfong@ieee.org.

Journal of Medical Systems

|September 4, 2020

Summary

This study introduces a new Radio Frequency Identification (RFID) anti-collision algorithm for patient tracking. The dynamic frame slotted Aloha method significantly reduces identification time and tag leakage in healthcare settings.

Keywords:

Collision avoidance Patient tracking Radio frequency identification (RFID)

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Area of Science:

Biomedical Engineering
Computer Science
Healthcare Technology

Background:

Radio Frequency Identification (RFID) tags are crucial for patient tracking in healthcare.
Passive RFID tags in washable clothing face tag collision issues, impacting identification effectiveness.
Effective tag anti-collision schemes are vital for reliable healthcare RFID systems.

Purpose of the Study:

To propose a novel dynamic frame slotted Aloha algorithm for RFID tag anti-collision.
To improve the efficiency and reliability of patient tracking systems in clinical environments.
To adaptively adjust frame length for enhanced RFID identification.

Main Methods:

Development of a dynamic frame slotted Aloha algorithm.
Integration of linear interpolation-based estimation for adaptive frame length adjustment.
Simulation of the proposed algorithm in a healthcare patient tracking scenario.

Main Results:

Achieved an estimation error below 1.5%.
Required less than 10 iterations for accurate estimation.
Demonstrated reduction in identification time and tag leakage probability.

Conclusions:

The proposed dynamic frame slotted Aloha algorithm effectively mitigates RFID tag collision.
The algorithm enhances patient tracking accuracy and efficiency in healthcare.
This method offers a robust solution for automated patient management in clinical settings.