Week 1 Update
The Data Capturing System will be adopting the ALCOAC-CEA Principles, which are
discussed as follows:
Attributable – Who collected the data, performed a test, completed the documentation or
edited the document and when.
Legible – The documentation and all subsequent changes should be permanent and easy
to read.
Contemporaneous – Documentation should be completed and dated in real time.
Original – Study documents should be the originals, or it should be noted where the
originals are located.
Accurate – Documentation should be comprehensive and truthfully reflect what was
observed.
Complete – Maintenance of complete and up-to-date study documents.
Consistent – The data’s sequence of events is in the expected sequence of operations and
date and time stamped.
Enduring – Paper and electronic data are appropriately recorded in company books,
spreadsheets, databases etc.
Available – Paper and electronic data are required to be readily available for review, audits,
or inspections.
While the following are the steps that the researcher will go through towards
finishing the said data capturing system:
● Development
● Testing
● Training
The system aims to maximize:
● Remote Data Capture
● Automation
While it aims to minimize:
● Risk of Double Entries
● Faulty Audit Trail
● Errors in Company Reports
For us to make sure that we develop an efficient and convenient Data Capturing
System, on our side as the developer of this project, we will be utilizing the use of
Automatic Identification and Data Capture (AIDC). It can be noted that AIDC is to identify,
verify, record, communicate and store information on discrete, packaged or containerized
items. AIDC is rapidly becoming an integral and necessary component in any organization.
These technologies are capable of performing automatic data capture. Modern technology
allows data capture to be quick, accurate and reliable. AIDC is a technology driven solution
to document processing. Prior existing technology was unable to accurately process forms
such as invoices because of the various fields that such documents contain. The data is
then saved electronically for access at a later point. This will make document work
efficient and convenient.
There are many different kinds of AIDC softwares but for this specific system
development, we as the developer, chose to use Optical Character Recognition (OCR)
because it has a recorded accuracy rate of 99.95%. It can be noted that To convert a
document image to electronic text, OCR is suitable software to bring up the TIFF image of
the scanned document, select the necessary text portion and put it into a format where we
can edit the text for accuracy and usability.
OCR converts scanned or photographed images of machine-printed characters into
electronic data. OCR is most extensively used in business to capture high-volume
documents, which delivers the best ROI. OCR technology has several solutions depending
on the size, volume, and content of the paper, and "template recognition" is a common OCR
technique in item processing. Template recognition requires a "template" or "mask" for
each character. An analog or digital representation of a character is compared to each mask
in the system's lexicon. When a printed or handwritten page is scanned with an OCR
application, the document saves as a bit-mapped TIF file. After scanning, an image appears
on screen. Where computer texts are the same. Also, it checks every image line to see if the
dots match a number or letter. OCR software automatically detects and recognizes text from
scanned documents, allowing you to copy, extract, search, and change the contents.
OCR reads text from scanned PDFs (including multi page files), photos, and digital
camera images. OCR converts archival TIFF photos into editable text. OCR does not affect
picture files; it reads text from photos and creates text files for long-term storage and online
document marking. Once OCR documents, proofread. Proofreading checks each letter,
number, word, punctuation mark, symbol, etc. to ensure they match the printed content.
Checking each paragraph, sentence, word, and punctuation mark for damaging content
takes patience and concentration.
At the end or during the completion of this system, it is the hope of the developer to be able
to provide a Data Capturing System that will bring the following to its users:
● Remote and Faster Access
● Ease in Gathering Information from Files
● Save times
● Save cost
● Quick Retrieval
What to expect from the next coming weeks:
● August 28 - presentation and discussion of the 25% of the ongoing system
development
● September 4 - presentation and discussion of the 60% of the ongoing system
development
● September 11 - presentation and discussion of the 80% of the ongoing system
development
● September 18 - presentation and discussion of the 100% of the ongoing system
development
● ABBYY FLEXICAPTURE will be used as the OCR
FlexiCapture is used to analyze and automatically categorize and recognize (OCR) invoices
of varying formats, automatically extracting data needed for entry such as the business
partner’s name, the invoice number, and the billing date. All a human operator does is
confirm the OCR results, then RPA software automatically inputs them into the company
database.
1. Acquiring images
There are several ways to feed invoice images to the program:
● Scanning hardcopy invoices
● Downloading invoice images from an e-mail inbox
● Downloading invoice images from a folder on a computer or an FTP server
2. Recognition and rule checks
After input, invoices are automatically recognized by the program. Data from the invoices is
then checked using rules and a status is assigned to the invoice based on the results of these
checks. Invoices that do not require any editing receive the Valid status and are ready for
export.
3. Verification and correction of errors
Invoices with a status other than Valid need to be reviewed by an Operator. Operators check
these documents and correct errors and warnings that were issued by checking rules.
When all defects have been corrected, an invoice receives the Valid status. Operators can
also confirm statuses that were assigned automatically. The status of an invoice can be
changed manually by an Operator, who has to specify the reason for the status change.
If the program systematically fails to locate fields on invoices, it can be trained by Operators
during the document capture process.
4. Data export
Data export is the final processing stage, during which data is exported as specified in the
program's settings. Documents with different statuses can be exported in different ways,
e.g. documents with the Valid and Exception statuses may be exported to a different folder
than documents with the Rejected status. Several export destinations may be set up, and
invoices can be exported to each of these destinations.
If the status of an invoice was changed manually, the reason for the status change that was
provided by the Operator is exported as well.
The program supports export to data and image files, ODBC-compatible databases, and
Microsoft SharePoint. Its easy-to-use API enables integration with any system.
Steps Undertaken:
1. In the photo below, it can be seen that the application for flexicapture has been
installed in the test mobile device. Said application should be launched in the said
mobile.
2. Once the application was already launched, we created a sample account for the
duration of this project. It can also be seen that said sample account should be
logged in in the SETTINGS page. See photo below:
3. The log-in page should look like this and for us to proceed, we inputted the created
sample account.
4. After logging in, we proceeded in choosing the kind of project that will be used for
this project. Please see photo below:
5. From the parameters shown, the “mobile” option was selected for this specific
project.
6. After such, the sample account was already established and ready for customization
to incorporate other functions that can be attributed to the needs of a business.
On the next update on August 28, we will be able to add:
-
Creation of a database
-
Customization and creation of homepage (log-in page)
-
Trial scanning