Human factors is the bridge between our core technology and its application to solving real world problems. We partner with customers and universities to generate vast data-sets that provide us with a second-to-none understanding of operator performance across our three transport verticals: fleet; automotive and aviation.
We use this knowledge to define benchmarks for the measurement of many high-level states; from drowsiness and distraction in truck driving, to workload and engagement in semi-automated driving, through to workload in air traffic control and situational awareness in pilot training. These data and knowledge are then used by our computer vision engineers to develop advanced algorithms and product features that set our technology apart from anyone else in the world.
Seeing Machines leads the world in operator monitoring technology.
Working closely with our customers, the team at Seeing Machines also engage in customer-focused research projects, working with automotive, commercial fleet and aviation customers, to name a few, to design and lead programs that showcase how our world leading technology can be applied to real-world operational settings, to measure real people as they go about their business in real time.
Some of our current programs are showcased below.
TACKLING DRIVER DROWSINESS AND DISTRACTION IN COMMERCIAL FLEETS:
THE ADVANCED SAFE TRUCK CONCEPT
Seeing Machines, already protecting over 200 commercial transport and logistic fleets worldwide with Guardian, is committed to world class product development as we continually enhance our best in class operator monitoring technology.
In partnership with Monash University Accident Research Centre, Ron Finemore Transport Services and Volvo Trucks Australia, Seeing Machines is leading one of the Australian Federal Government’s funded Cooperative Research Centre Projects.
The Advanced Safe Truck Concept (ASTC), a A$6.5M project aims to reduce fatal truck crashes by developing new vehicle technologies, through the intense study of driver behaviour, in a range of settings, with a focus on driver fatigue and distraction.