1. Reliability
improvement for an
RFID-based psychiatric
patient localization
system

2. 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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3. Outline
 Introduction
 System overview
 Reliability improvement with field generator scheduling
 Experiments
 Conclusion
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4. 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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5. System overview
 The Department of Psychiatry, National Cheng Kung University
Hospital (NCKUH) uses an RFID-based psychiatric patient
localization system
 The 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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6. System overview
6

7. 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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8. Reliability improvement with
field generator scheduling
8

9. 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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10. 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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11. 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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12. 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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13. 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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14. Experiments
 Elucidating system performance
 Fixed-points test
 Route test
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15. 15

16. 16

17. Elucidating system performance
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18. 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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19. 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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20. 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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21. 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 T
represents 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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22. Fixed-points test
 positions 1–6 reside in single Field Generator range
 positions 7–10 are located in the overlapping region of two
Field 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
1s
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23. Fixed-points test
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24. Fixed-points test
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25. Fixed-points test
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26. 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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27.  (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)
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28. Route test
28

29. Route test
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30. Route test
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31. Route test
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32. 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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33. Reliability comparison for original system and the
system with proposed GCMD algorithm
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34. 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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