Bringing together innovation and safety, across Monadelphous we’ve been adopting new technology to keep us safe when operating vehicles and equipment – trialling new systems for pedestrian avoidance and fatigue management.
One of our fatal risk controls, People interacting with mobile plant, has been on the top of our agenda when it comes to safety technology to increase awareness, and improve our behaviours, when working around mobile plant.
Pedestrian avoidance systems with artificial intelligence (AI) technology, is one way to proactively alert mobile plant operators when people move within the no-go zone during operation. Current systems available on the market were investigated, and two pedestrian avoidance systems were identified as meeting Monadelphous’ and our customer’s minimum requirements, and subsequently trialled across our operations.
Speedshield aiva was installed onto a telehandler at the Mine Services Area (MSA) project at Talison Lithium’s Greenbushes, and Blindsight was installed on a franna and telehandler working across FMG projects and BHP’s MAC dust suppression project.
The systems utilise AI camera technology to monitor risks around the operating piece of equipment. AI technology allows the camera to specifically detect people, plant or infrastructure that may present a risk, sending audible alerts to the operator and person, when risk is detected.
During the trial, feedback was captured from the plant operators, and results were fed back to the team working with the equipment on the project. The operators reported the system gave them greater awareness of people that were working around the equipment and enabled them to better judge how close they were to the equipment or load they were carrying. This allowed them to stop and manage the situation if anyone was moving too close to them during operation.
The trials have now been completed, with results assessed and a recommendation being made to our senior leaders for use of the systems across Monadelphous on different plant and equipment types. Key criteria assessed included:
The system alerted the operator to people working too closely to the telehandler and the operator was able to notify their teammates to relocate themselves and reduced the risk.
Fatigue accounts for a significant amount of vehicle incidents across Australia. Research indicates approximately 20 – 30% of all car crashes in Australia are attributable to fatigue, and it’s becoming a growing concern for us and our customers.
As a solution the Guardian Seeing Machine system was trialled on five vehicles including light vehicles, frannas and a heavy rigid truck. The system uses video sensor technology to send audible alerts and seat vibrations to the driver if it picks up a potential fatigue or distraction event. In real time the driver is alerted as well as managers to be able to take immediate action to keep everyone safe.
It tracks eyes, face and head position to determine whether a driver is fatigued or distracted. If there are signs of either two, the system activates in-cab alerts.
Feedback was captured from 16 drivers / operators which showed positive results as well as areas of improvement.
The fatigue management system exploration continues. The Guardian Seeing Machine presents a good option; however, the safety team are continuing to assess alternate options and costs for our entire fleet.
Stay tuned for more. If you have any innovative suggestions on how we can improve safety, or use technology better, share your ideas with your supervisor.
**Notes on privacy: The Guardian system is not a CCTV. This means that no one can under any circumstances connect to the system and monitor you while you drive or while you are in cabin. The system is only activated during a fatigue or distraction related event, at which a 10 sec video is captured before and after the event.
Seeing Machines respects your privacy. A Privacy Policy which sets out the types of data Guardian may collect about drivers, and how we collect, use, disclose and protect this data comply with relevant privacy laws.