Siemens's RIF Management Talk.

cribabsurdΗλεκτρονική - Συσκευές

27 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

93 εμφανίσεις

RFID Topics

Mo Liu

Bart Shappee



Temporal Management of RFID Data

Worcester Polytechnic Institute

2

OUTLINE


RFID Background


DRER Model


Overview of Syntax


Data Acquisition


Tool for efficiency


Siemens Work

Worcester Polytechnic Institute

3

RFID
-

Background


Radio Frequency Identification


Major Characteristics:


Streaming Data


Temporal and Dynamic


Unreliable Data


Mainly Missed Reads & Duplicates


Very Large Volume of Information


Integration


RFID Data needs to be handled by existing
applications

Worcester Polytechnic Institute

4

Cont’d


Integration & Information
-

What we
need to consider:


Time


Location


Being in the physical world


Aggregation

Worcester Polytechnic Institute

5

Dynamic Relationship ER Model (DRER)



RFID entities are static and are not altered in the
business

processes


RFID relationships: dynamic and change all the time


Dynamic Relationship ER Model




Simple extension of ER model


Two types of dynamic relationships added:




Event
-
based dynamic relationship. A
timestamp
attribute added to

represent the occurring timestamp
of the event




State
-
based dynamic relationship.
tstart
and
tend
attributes added

to represent the lifespan of a state


Worcester Polytechnic Institute

6


Dynamic Relationship ER Model (DRER) (cont’d)


Worcester Polytechnic Institute

7

cont’d


Static entity tables


OBJECT (epc, name, description)



SENSOR (sensor_epc, name, description)



LOCATION (location_id, name, owner)







TRANSACTION (transaction_id, transaction_type)

Worcester Polytechnic Institute

8

cont’d


Dynamic relationship tables



OBSERVATION (sensor_epc, value, timestamp)





SENSORLOCATION (sensor_epc, location_id, position, tstart, tend)

Worcester Polytechnic Institute

9

OBJECTLOCATION(epc, location id, tstart,tend)


CONTAINMENT(epc, parent epc, tstart,tend)

TRANSACTIONITEM

(transaction_id, epc, timestamp)

Worcester Polytechnic Institute

10

Tracking and Monitoring RFID Data



RFID object tracking:

find the location history of object

“EPC”


SELECT * FROM OBJECTLOCATION WHERE epc='EPC‘



Missing RFID object detection: find when and where object

“mepc” was lost



SELECT location_id, tstart, tend


FROM OBJECTLOCATION


WHERE epc='mepc' and tstart =(SELECT MAX(o.tstart)








FROM OBJECTLOCATION o







WHERE o.epc=‘mepc')


RFID object identification: a customer returns a product


“XEPC”. Check if the product was sold from this store



SELECT * FROM OBJECTLOCATION


WHERE epc='XEPC' AND location_id='L003'


Worcester Polytechnic Institute

11

Cont’d


Temporal aggregation of RFID data: find how many items

loaded into
the store “L003” on the day of 11/09/2004


SELECT count(epc)FROM OBJECTLOCATION


WHERE location_id = 'L003'


AND tstart <= '2004
-
11
-
09 00:00:00.000'


AND tend >= '2004
-
11
-
09 00:00:00.000‘



RFID Data Monitoring

monitor the states of RFID objects


RFID object snapshot query: find the direct container of object “EPC”
at time T


SELECT parent_epc FROM CONTAINMENT


WHERE epc='EPC' AND tstart <= 'T' AND tend >= 'T'



Worcester Polytechnic Institute

12

RFID
-

Data Acquisition


Data is automatically
generated from the
physical world
through Readers and
Tags


Modes if Acquisition


Full/Half Duplex


Sequential Mode


This information
includes EPCs and
timestamps


Other stored values
may also be
transmitted


PHYSICAL WORLD


TAG

2

Antenna (interface)

2

Controller

2

Application

Worcester Polytechnic Institute

13

RFID
-

DATA Acquisition Part 2

Data is also pre
-
porocessed


Data Filtering


Local Transformation


Data Aggregation

How do we improve on this?

OBSERVATION(Rx, e, Tx),

OBSERVATION(Ry, e, Ty), Rx<>Ry,

within(Tx, Ty, T)
-
> DROP:OBSERVATIONS(Rx, e, Tx)

OBSERVATION(“R2”, e, t)
-
>


UPDATE:OBJECTLOCATION(e, “L002”, t, “UC”)

Seq(s,”r2”);OBSERVATION(“r2”. E. t)
-
>


INSERT:CONTAINMENT(seg(s, “r2”, Tseq), e, t, “UC”)

Worcester Polytechnic Institute

14

RFID
-

DATA Acquisition Part 3

Data is also handled with rules

some examples are:


Sate Modification (i.e. time at toll)


Creation


Deletion


Containment (1000 ipods in a case)


Change location of the 1000 ipods

How do we improve on this
(even more)?

Worcester Polytechnic Institute

15

A Tool to improve query efficiency

Worcester Polytechnic Institute

16

Data Partitioning



Increase of data volumes slows down queries


Data have a limited active cycle




Non
-
active objects can be periodically

archived into history

segments




Active segments with a high active object ratio is used for
updates


This partition technique assures efficient update and

queries


Worcester Polytechnic Institute

17

Siemens's Product


Middleware


Automatic acquisition and filtering


Have built a working prototype


Worcester Polytechnic Institute

18

Conclusion


Laid a framework for the problems of
RFID data acquisition and handling


This paper introduced and pushed
the DRER model