Reliability

improvement for an

RFID-based psychiatric

patient localization

system

Reference

Chieh-Ling Huang, Pau-Choo Chung, Ming-Hua Tsai,

Yen-Kuang Yang, Yu-Chia Hsu Reliability improvement

for an RFID-based psychiatric patient localization

system IEEE Computer Communications 31 (2008)

2039–2048

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Outline

Introduction

System overview

Reliability improvement with field generator scheduling

Experiments

Conclusion

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Introduction

Psychiatric patients often cannot control their actions, occasionally resulting in dangerous behavior

RFID technology has been utilized in various applications, including supply chain management, entry and exit control

Localizing moving objects, e.g., freight localization or human localization is a challenging and relatively unexplored task

presents a novel graph coloring with merging and deletion (GCMD) algorithm

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System overview

The Department of Psychiatry, National Cheng Kung University Hospital (NCKUH) uses an RFID-based psychiatric patient localization systemThe second floor serves as a clinic for psychiatric patients, and the third floor

is an activity area

Nurses : scheduling daily activities and providing basic care

Doctors : medical treatment

This RFID-based psychiatric patient localization system uses a ultra high frequency (UHF) long range tracker. The Field Generators operate on 433 MHz when triggering the Tag to respond, and the Tag replies to a Reader with 916 MHz signal once it is triggered

Psychiatric patients in the care center wear watch-like Tags, Tag transmits information, including Tag ID and Field Generator ID

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System overview

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Reliability improvement with

field generator scheduling

This system relies on the Tag correctly receiving signal from the Field Generators to estimate the Tag location

Two Field Generators with overlapping transmission ranges simultaneously issuing trigger signals to a Tag causes signal interferences in the overlapped region

This interference results in loss of signal and, therefore, decreases localization accuracy

Transform the relationships among all Field Generators into a graph

Vertex deletion and merging

Vertex coloring

Operation slot allocation

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Reliability improvement with

field generator scheduling

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Transform the relationships among

all Field Generators into a graph

The relationships among Field Generators are

transformed into an undirected graph G, whereas V and

E are sets of vertices and edges, respectively. Where V

and E are derived based on the Field Generators and

their signal region overlapping situations, respectively

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Vertex deletion

When the range of one Field Generator, FGx, is

completely covered by other Field Generators, the

function of FGx can be replaced by a combination of

these other Field Generators

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Vertex merging

The entire overlapping region is covered by a union of

Field Generators, so other Field Generators can cover

the overlapping region

Consequently, the two vertices associated with the two

Field Generators can be merged, and no special care is

required to avoid signal interference from the two Field

Generators

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Vertex coloring

A coloring algorithm is applied to the trimmed graph, in

which connected vertices are assigned different colors

The Field Generators with the same color are assigned

to the same group, and, therefore, can transmit signals

simultaneously

Conversely, the Field Generators with different colors

are assigned to different groups; scheduling must be

applied to avoid signal conflict

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Operation slot allocation

A weighted TDMA is applied to assign time slots for operation to each group

Consider that each partitioned group can occupy different levels of importance

Another consideration is the size of an area covered by a group of Field Generators

The importance factor for each group wi can be

approximated

The time slot ratio for each group

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Experiments

Elucidating system performance

Fixed-points test

Route test

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Elucidating system performance

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Elucidating system performance

Tags

send out responses periodically (reciprocated regularly)

only when triggered by Field Generators

A patient’s location is computed based on the

communication range of the patient’s Tag within the

Field Generators with respect to ranges of reference

Tags

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Elucidating system performance

More than two Tags are sending reports back to the

Reader simultaneously Repetitive transmission

Repetitive transmission times are set at 6 and the

associated lasting time is Trep

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Elucidating system performance

Time in field (TIF) time: a Tag can be programmed with

a TIF Time (TTIF) that specifies the time duration before

the Tag can be triggered again

A Reader receives two consecutive reports from the same Tag.

How can the Reader determine whether the two reports are

issued due to two separate triggers, or whether the two reports

are due to a repetitive response trigger?

Another aim of TIF time is to prevent Tags from wasting

energy replying to the same trigger from a Field Generator

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Elucidating system performance

Trep + TTIF is defined as one round; if one of the six responses in one round is received, this round is regarded as successfully received

lost rate of responses L as the total number of lost rounds divided by the total number of rounds that should trigger the Tag: r denotes the number of rounds that the Reader successfully received Tag’s reply signal and Trepresents time cost

In this system, it takes roughly three rounds for a patient to move from the building exit to the main gate. Under this scenario, we define response rate Rn as: n is the number of rounds – 3 in this case

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Fixed-points test

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positions 1–6 reside in single Field Generator range

positions 7–10 are located in the overlapping region of twoField Gen-erators

positions 11–14 are in the overlapped region for three Field Generators

position 15 is in the overlapping region of four Field Generators

people wearing Tags stand at each fixed position for 1 min

group1 is assigned 2 s for operation and group2 is assigned 1 s

Fixed-points test

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Fixed-points test

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Fixed-points test

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Route test

5 routes

(a) Route1 is the path passing the 15 representative points

(b) Route2 is the path connecting with poor reliability in the

fixed-point test

(c) Route3 is the path connecting points with high reliability

(d) Route4 is the path of shortest distance from the building

exit to the main gate and

(e) Route5 is a route tracing through a region that is rarely

covered by routes (a–d)

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(a) The route connecting 15 representative points

(b) The route connecting the lowest reliability points

(c) The route connecting the highest reliability points

(d) The route having the shortest path from exit to main gate

(e) The route tracing a region not tested in (a–d)

Route test

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Route test

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Route test

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Route test

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Experiments

position 3: The Field Generator has difficulty reaching

this sharp corner and the Tag cannot reach the Reader.

Thus, a Reader is added at position 10

Experimental results: response rate for position 3 improves

from 0% to 57.81% in the unscheduled original system,

and from 14.26% to 83.36% using GCMD scheduling

Transmission time slots should be based on group

importance

For group covering important regions or large areas

should be allocated increased time periods

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Reliability comparison for original system and the

system with proposed GCMD algorithm

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Conclusion

The RFID devices that are small and relatively cheap are

very appropriate for use in localizing psychiatric Patients

In this study, a GCMD scheduling model is utilized for

scheduling Field Generator transmissions in an RFID-based

psychiatric patient localization system, thereby reducing

interference caused by Field Generators located near one

another

Experimental results demonstrated that the system is highly

effective when using the proposed scheduling algorithm

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