Hi reddit team!
Small problems are easier and cheaper to handle when they're caught early. Computer vision can help by analyzing visual data continuously and alerting teams when something unusual happens. It's not about replacing people - it's about reducing the time between an event and a response.
When people talk about AI in mining, the conversation often jumps straight to autonomous trucks and fully automated operations. Those ideas get attention, but some of the biggest benefits may come from much simpler applications.
Modern mines already collect huge amounts of information. There are cameras around facilities, equipment sensors, production data, and weight measurements from machinery. The challenge is that there is far more data than people can realistically monitor in real time.
A human team might review footage after a shift, after an incident, or only when a problem has already happened. That delay creates a gap between something going wrong and someone being able to respond.
A few examples:
A small fire or smoke appears near a stockpile.
A haul truck sits idle longer than expected.
Someone enters an area where they shouldn't be.
Equipment behavior changes overnight.
In each case, the longer it takes to identify the issue, the more expensive it can become. Lost production, safety risks, and wasted resources can add up quickly.
Computer vision can help by analyzing visual data continuously and alerting teams when something unusual happens. Instead of discovering a fuel leak during a later safety review, operators could receive an alert while it is happening. Instead of waiting for an end-of-day report to find production delays, managers could see bottlenecks developing in real time.
The goal isn't replacing people. It is reducing the time between an event and a response. Small problems are easier and cheaper to handle when they are caught early.
NRED is evaluating EyeX computer vision technology as part of its broader intelligent mining strategy, with potential applications in exploration and future operations.
Mining has always been about managing risk and improving efficiency. If AI tools can help companies identify problems earlier and make better decisions with existing data, that could become a meaningful advantage rather than just another technology story.
