The Changing Role of Oversight in Mining – TechEconomy.ng

Over the past 24 months, the conversation around surveillance has changed dramatically. Instead of being solely a security or facilities side of a business, the ability to take raw video and audio footage, convert it to data, and analyze it has become a hot topic in many industries, including mining.

Surveillance has become something that affects an organization’s physical security measures as well as the areas of IT and risk management.

Stephanie Rosenmayer, Business Unit Manager at Datacentrix

“With the addition of intelligence, the humble camera has essentially become the ‘eye’ in the IoT, and suddenly there’s so much more value to be gained from an already deployed asset,” says Stephanie Rosenmayer, Business Unit Manager at Datacentrix, a hybrid IT systems integrator and managed services provider. “If captured correctly, it’s here, at the source of the data, that we can bring actionable insights to the business.”

Technology at the service of surveillance

According to Rosenmayer, several trends are driving the evolution of surveillance. “We know that artificial intelligence (AI) and surveillance are moving to the cloud and it’s a fact that surveillance is now an integral part of the enterprise architecture.

Additionally, we understand that this has a huge impact on bandwidth requirements, and this is now a conversation that needs to include IT. We’ve also seen analytics move to the edge, which includes the incorporation of analytics into new smart camera technology.

“There was an AI explosion,” she continues. “Consider the Open Security & Safety Alliance (OSSA), a not-for-profit corporation created to establish a common standardized platform for security and safety solutions available to everyone. These standards relate to operating systems, real infrastructure, privacy and data. The goal is to reach a point where we can apply or select any AI application and deploy it to any camera, regardless of brand, that is specifically required in this business environment.

Monitoring in mines
Mining Monitoring

A good example of this for the mining environment would be if there is a need for an application that only deals with crushers. “OSSA’s latest engine will remove the barrier to entry for high-level AI development skills to enter the surveillance market, which has traditionally been limited to OEMs. This means that you will be able to find the right crusher app for your needs and deploy it to any camera.

“It’s not a pipe dream, and we’ll see it play out in the next year or two, as the biggest camera manufacturers start joining OSSA and start adding processing capabilities to the cameras themselves. themselves.”

Cameras play a key role in safety and efficiency gains

Rosenmayer says: “Ultimately, the source of our data comes from sensors – cameras, environmental sensors or power distribution systems – and all of this information needs to be collected in a place where it can be used for two things. First, it can be used for an emergency alert, where the right person can be dispatched to deal with an issue, and second, to take unstructured content and organize it into output that can be useful and actionable for the organization. , adding value in terms of the bottom line.

For example, typical safety issues that can be tracked and addressed using monitoring in this context may include personnel violations (such as employees not wearing the appropriate personal protective equipment (PPE) or workers in the field walking a lane), sudden changes in the operating environment, poor forecasting of risks, and challenges in supervising underground personnel.

Monitoring could also address the need to improve efficiency, or yield, due to poor performance of production equipment or a lack of dynamic balance between production, transport and storage.

A good example here would be the system’s belt performance challenges, says Rosenmayer. “For a coal mine using an underground conveyor belt in the coal transmission process, a lack of real-time monitoring and poor communication could mean the organization is unaware that the conveyor belt, which covers a long distance, is transporting at some times zero charge, which could even stretch for hours.

“The conveyor belt is a major consumer of a mine’s overall electrical power usage, spending up to 40 percent of operational cost. This means that at times when there is no load, the mine consumes energy – and pays for it – at a time when it is completely unnecessary.

There may also be instances where foreign objects falling onto the conveyor belt, or oversized ore, cause blockages or even damage to the belt, often leading to greater economic losses in transportation. Perhaps there has been an abnormal stoppage of the conveyor, people approaching it when they shouldn’t be, or there may be deviations from the conveyor.

“These are all challenges that a real-time view of critical parts of your facility and the overall state of the underground environment could help solve.”

In fact, according to Rosenmayer, case studies of international mines using AI technologies have shown a proven reduction in conveyor belt downtime from three days a month to one. No-load power consumption was also reduced from $650,000 per year to $280,000 per year.

“In addition, these mines have seen several benefits for improved management, such as the ability to anticipate major hazards, identify personnel violations and contain major accidents. They were able to avoid the shutdown of the mine due to serious accidents. They also now have access to intuitive metrics for supervising mining operations; reliable evidence for accident retrospection; and can provide statistical reports on abnormal mining operations to support scientific decision-making.

“From a mining perspective, the key question to ask in monitoring today is: how useful is it for your organization to have this information in real time, instead of finding out how it got there? affected production at the end of the day? she asks.

Bonny J. Streater