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Automatic identification and data capture (AIDC) refers to the methods of automatically identifying objects, collectingdata about them, and entering them directly intocomputer systems, without human involvement. Technologies typically considered as part of AIDC includeQR codes,[1]barcodes,radio-frequency identification (RFID),biometrics (likeiris andfacial recognition system),magnetic stripes,optical character recognition (OCR),smart cards, andvoice recognition. AIDC is also commonly referred to as "Automatic Identification", "Auto-ID" and "Automatic Data Capture".[2]
AIDC is the process or means of obtaining external data, particularly through theanalysis of images,sounds, orvideos. To capture data, atransducer 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 various ways; the best method depends on application.
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.
Radio-frequency identification is relatively a new AIDC technology, which was first developed in the 1980s. The technology acts as a base in automateddata collection, identification, and analysis systems worldwide. RFID has found its importance in a wide range of markets, includinglivestock identification andAutomated Vehicle Identification (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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Nearly all the automatic identification technologies consist of three principal components, which also comprise the sequential steps in AIDC:
One of the most common applications of data capture is extracting information from paper documents and saving it into databases (CMS, ECM, etc.). Basic technologies used for data capture vary by data type:[citation needed]
These technologies enable data extraction from paper documents for processing in enterprise systems likeenterprise resource planning (ERP) andcustomer relationship management (CRM).[citation needed]
The documents for data capture can be divided into 3 groups: structured, semi-structured, andunstructured.[citation needed]
Structured documents (e.g., questionnaires, tests, tax returns, insurance forms, ballots) have identical layouts, making data capture straightforward since fields are always in the same location.[9]
Semi-structured documents (e.g., invoices, purchase orders, waybills) follow a general format, but layout varies by vendor or parameters. Capturing data requires more advanced methods.[10]
Unstructured documents (letters, contracts, articles, etc.) could be flexible with structure and appearance.[9]
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.[11] However, others have voiced criticisms of the potential expansion of AIDC systems into everyday life, citing concerns over personal privacy, consent, and security.[12]
The globalAuto-ID Labs association, founded in 1999, includes major corporations such asWalmart,Coca-Cola,Gillette,Johnson & Johnson,Pfizer,Procter & Gamble,Unilever,UPS, and tech firms likeSAP, Alien, and Sun, along with five academic research centers.[13] These centers are based at theMassachusetts Institute of Technology (USA),University of Cambridge (UK),University of Adelaide (Australia),Keio University (Japan),[14]ETH Zurich andUniversity of St. Gallen (Switzerland).
Auto-ID Labs envisions a future supply chain based on the Internet of Objects — a global application of RFID. Their goal is to harmonize technology, processes, and organization. Research focuses on miniaturization (targeting 0.3 mm per chip), cost reduction (around $0.05 per unit), and innovative applications such as contactless payments (Sony/Philips),domotics (e.g., tagged clothing and intelligent appliances), and sporting events (e.g., timing at theBerlin Marathon).
AIDC 100 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 of the organization.[15]