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MineWare’s Optical Character recognition system (OCR) takes human error out of the safety equation.

Optical Character Recognition (OCR) is the recognition of printed or written characters by a
computer. The process of using OCR on a mine or business involves creating check sheets
using management data and relevant exploratory questions. These sheets can range from
information pertaining to safety, production or just general employee feedback questions.
Information is captured on physical sheets and collected at a central point for digital
scanning. The system reads, populates and actions data in less than 30 seconds per sheet,
so that all data is available digitally. By linking predefined answers to certain questions
defined in the risk model, called mapped questions, the system can automatically trigger
predefined actions by utilizing the action manager.

Mobile device capability allows data to be captured immediately and
on-site, while data is fresh and visually available. The use of OCR
systems eliminates the need for data to be read and captured by
humans, negating the possibility of human error.

To date the OCR system has been used to scan and check operational and SHEQ capture
sheets, which would then populate relevant databases, all as part of the Syncromine
software suite. In response to the Covid-19 crisis, this technology is now being used to
scan health checklists that have to be filled in by all visitors to the mines. This data is
then seamlessly converted to digital information and analyzed. MineWare’s OCR
software feature is working around the clock to scan and verify the avalanche of
Covid-19 health assessment forms that the mines have instated, in an effort to keep
visitors and workers safe, while ensuring compliance with national guidelines.Two
new installations of this functionality are currently taking place at Gold Fields
Limited and Impala Platinum in South Africa.

This system will benefit any business that wishes to streamline operational safety, improve
efficiency and eliminate the factor of human error in data gathering.

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