An Anti-Collision Scheme for RFID for Patient Tracking Using Linear Interpolation Estimation
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SYSTEMS-LEVEL QUALITY IMPROVEMENT
An Anti-Collision Scheme for RFID for Patient Tracking Using Linear Interpolation Estimation Bernard Fong 1 Received: 10 January 2019 / Accepted: 21 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Radio Frequency Identification (RFID) tags are widely used in the healthcare industry for patient tracking. A mainstream RFID implementation is based on a series of readers installed in a fixed location within a hospital or a nursing home and tags are embedded in the clothing worn by patients. Caregivers can readily obtain near real-time location information of individual patients from the tag locations. For implementation in washable clothing tags are often passive such that tag collision is a common problem within co-operation mechanism between tags. Tag anti-collision scheme is there an important consideration that affects the identification effectiveness. To address this issue, this paper proposes a dynamic frame slotted Aloha algorithm based on linear interpolation based estimation that adaptively adjusts the frame length. Simulation results show that the proposed algorithm yields an estimation error below 1.5% achieved in less than 10 iterations, it provides reduction in identification time while reduces the tags leakage probability in a clinical environment where patient tracking is automatically managed. Keywords Collision avoidance . Patient tracking . Radio frequency identification (RFID)
Introduction Radio frequency identification (RFID) has been widely used for patient and sample identification in the healthcare industry [5]. In a typical RFID system deployment, there is at least one of a reader and multiple identification tags [30]. Each tag is embedded in the clothing worn by the patient that conveys certain information about the patient [2]. As the number of tags within a confined area increases, the likelihood of a tag collision increases [27]. Three mainstream anti-collision methodologies have been widely used in RFID implementation over the past decade, namely random Aloha, binary search and Hybrid; with the common goal of coordinating tag transmission for collision avoidance [31]. In the clinical setting where many patients are simultaneously tagged, binary search method is not suitable due to the time needed for execution [23]. While Darcy and This article is part of the Topical Collection on Systems-Level Quality Improvement * Bernard Fong [email protected] 1
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Stantic [6] proposed that Aloha anti-collision method is particularly suited for clinical applications due to its anti-collision properties, many healthcare facilities need more effective schemes to cope with the increase in number of patients. In particular, the demand for nursing homes have been growing steadily in recent years due to population aging across many metropolitan cities [20]. The risk of tag collision increases as the number of patients increases. This is particularly problematic w
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