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is employed which converts the actual image or a sound into a digital file. The file is then stored and at a later time, it can be analyzed by a computer, or compared with other files in a database to verify identity or to provide authorization to enter a secured system. Capturing data can be done in
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Advocates for the growth of AIDC systems argue that AIDC has the potential to greatly increase industrial efficiency and general quality of life. If widely implemented, the technology could reduce or eliminate counterfeiting, theft, and product waste, while improving the efficiency of supply chains.
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is a professional organization for the automatic identification and data capture (AIDC) industry. This group is composed of individuals who made substantial contributions to the advancement of the industry. Increasing business's understanding of AIDC processes and technologies are the primary goals
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The Auto-ID Labs suggests a concept of a future supply chain that is based on the
Internet of objects, i.e., a global application of RFID. They try to harmonize technology, processes, and organization. Research is focused on miniaturization (aiming for a size of 0.3 mm/chip), reduction in the
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Data encoder. A code is a set of symbols or signals that usually represent alphanumeric characters. When data are encoded, the characters are translated into machine-readable code. A label or tag containing the encoded data is attached to the item that is to be
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One of the most useful application tasks of data capture is collecting information from paper documents and saving it into databases (CMS, ECM, and other systems). There are several types of basic technologies used for data capture according to the data type:
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In biometric security systems, capture is the acquisition of or the process of acquiring and identifying characteristics such as finger image, palm image, facial image, iris print, or voiceprint which involves audio data, and the rest all involve video data.
319:(questionnaires, tests, insurance forms, tax returns, ballots, etc.) have completely the same structure and appearance. It is the easiest type for data capture because every data field is located at the same place for all documents.
325:(invoices, purchase orders, waybills, etc.) have the same structure, but their appearance depends on several items and other parameters. Capturing data from these documents is a complex, but solvable task.
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171:(AVI) systems because of its capability to track moving objects. These automated wireless AIDC systems are effective in manufacturing environments where barcode labels could not survive.
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Automatic
Identification and Data Capture (Barcodes, Magnetic Stripe Cards, Smart Cards, OCR Systems, RFID Products & Biometric Systems) Market - Global Forecast to 2023
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However, others have voiced criticisms of the potential expansion of AIDC systems into everyday life, citing concerns over personal privacy, consent, and security.
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Radio-frequency identification is relatively a new AIDC technology, which was first developed in the 1980s. The technology acts as a base in automated
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price per single device (aiming at around $ 0.05 per unit), the development of innovative applications such as payment without any physical contact (
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These basic technologies allow extracting information from paper documents for further processing in the enterprise information systems such as
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Nearly all the automatic identification technologies consist of three principal components, which also comprise the sequential steps in AIDC:
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Machine reader or scanner. This device reads the encoded data, converting them to an alternative form, typically an electrical analog signal.
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Data decoder. This component transforms the electrical signal into digital data and finally back into the original alphanumeric characters.
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163:, identification, and analysis systems worldwide. RFID has found its importance in a wide range of markets, including
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Proceedings of the Sixth ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining – KDD '00
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132:. AIDC is also commonly referred to as "Automatic Identification", "Auto-ID" and "Automatic Data Capture".
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Palmer, Roger C. (1989, Sept) The Basics of
Automatic Identification . Canadian Datasystems, 21 (9), 30-33
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423:(clothes equipped with radio tags and intelligent washing machines), and sporting events (timing at the
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The documents for data capture can be divided into 3 groups: structured, semi-structured, and
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systems, without human involvement. Technologies typically considered as part of AIDC include
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was founded in 1999 and is made up of 100 of the largest companies in the world such as
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331:(letters, contracts, articles, etc.) could be flexible with structure and appearance.
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Yi, Jeonghee; Sundaresan, Neel (2000). "A classifier for semi-structured documents".
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AIDC is the process or means of obtaining external data, particularly through the
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Methods of automatically identifying objects by computer system
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AIDC 100: Professionals Who Excel in
Serving the AIDC Industry
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743:"Biometrics Are Coming, Along With Serious Security Concerns"
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379:, companies working in the sector of technology such as
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various ways; the best method depends on application.
546:"Automatic Identification and Data Collection (AIDC)"
570:"What is Optical Character Recognition (OCR)?"
8:
175:Overview of automatic identification methods
88:about them, and entering them directly into
213:. Unsourced material may be challenged and
833:Automatic identification and data capture
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233:Learn how and when to remove this message
78:Automatic identification and data capture
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632:"Optical recognition and data-capture"
385:Massachusetts Institute of Technology
261:Capturing data from printed documents
102:radio frequency identification (RFID)
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711:Nanocomputers and Swarm Intelligence
294:DLR – for document layer recognition
211:adding citations to reliable sources
279:– for hand-printed text recognition
460:Automatic number-plate recognition
455:Automatic equipment identification
25:
808:from the original on 24 July 2011
450:Automated species identification
183:
169:Automated Vehicle Identification
34:
853:Radio-frequency identification
741:Glaser, April (9 March 2016).
604:Rouse, Margaret (2009-10-01).
291:BCR – for bar code recognition
288:OBR – for barcodes recognition
273:– for printed text recognition
1:
122:optical character recognition
608:. TechTarget. Archived from
630:Technologies, Recogniform.
335:The Internet and the future
47:to comply with Knowledge's
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848:Human–computer interaction
323:Semi-structured documents
114:facial recognition system
490:Field Service Management
405:University of St. Gallen
165:livestock identification
60:may contain suggestions.
45:may need to be rewritten
606:"bar code (or barcode)"
500:Mobile Asset Management
389:University of Cambridge
343:The global association
285:– for marks recognition
843:Multimodal interaction
707:Waldner, Jean-Baptiste
393:University of Adelaide
329:Unstructured documents
718:John Wiley & Sons
675:10.1145/347090.347164
439:of the organization.
361:Johnson & Johnson
147:. To capture data, a
720:. pp. 205–214.
659:. pp. 340–344.
510:Ubiquitous computing
369:Procter & Gamble
317:Structured documents
207:improve this section
636:www.recogniform.com
574:www.ukdataentry.com
515:Ubiquitous Commerce
505:Smart data capture
137:analysis of images
769:"The New Network"
727:978-1-84704-002-2
495:Mobile Enterprise
475:Device management
403:, as well as the
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130:voice recognition
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49:quality standards
16:(Redirected from
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470:Data privacy
465:Auto-ID Labs
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345:Auto-ID Labs
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311:unstructured
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205:Please help
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54:You can help
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18:Data capture
550:www.mhi.org
250:identified.
126:smart cards
827:Categories
798:"AIDC 100"
713:. London:
684:1581132336
641:2015-01-15
616:2017-03-09
555:2021-04-11
522:References
401:ETH Zurich
149:transducer
106:biometrics
838:Encodings
661:CiteSeerX
353:Coca-Cola
223:July 2021
194:does not
98:bar codes
66:July 2021
58:talk page
812:2 August
806:Archived
709:(2008).
443:See also
436:AIDC 100
431:AIDC 100
421:domotics
373:Unilever
357:Gillette
94:QR codes
90:computer
782:23 June
693:2154084
580:22 July
417:Philips
349:Walmart
215:removed
200:sources
124:(OCR),
752:5 July
724:
691:
681:
663:
365:Pfizer
145:videos
141:sounds
128:, and
108:(like
56:. The
776:(PDF)
689:S2CID
143:, or
814:2011
784:2011
754:2021
722:ISBN
715:ISTE
679:ISBN
582:2016
413:Sony
198:any
196:cite
167:and
112:and
110:iris
86:data
82:AIDC
671:doi
427:).
419:),
381:SAP
377:UPS
304:CRM
300:ERP
283:OMR
277:ICR
271:OCR
209:by
116:),
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