How Emesent Hovermap technology helped Petra Diamonds save millions
Petra Diamonds save millions in remediation costs at its Finsch Mine.
BHP’s Olympic Dam mine: improving stope design and efficiency
Hear how BHP is improving the efficiency of their Olympic Dam mine. Evan Jones, Principal Geotechnical Engineer, talks us through how the geotechnical team utilizes Hovermap’s LiDAR data to improve stope design.
LKAB’s Kiruna mine: inspecting seismic event damage
Swedish mining giant LKAB suffered a significant seismic event at their Kiruna iron ore mine.
Evolution’s Mungari Gold mine improves stope design and reconciliation
Hear how Mungari Gold operation replaced its CMS with Hovermap, and capture rich stope data sets that help improve stope design and reconciliation.
Deploying and operating Hovermap in underground excavations
Hear from Unmanned Aerial Services Inc, experts in scans and inspection in underground mining operations.
Emesent takes part in Navy’s Autonomous Warrior 2020
Even though the Royal Australian Navy is over a century old they are pushing boundaries, constantly looking for better and innovative ways to keep Australians safe.
Hovermap wins Innovative Mining Solution Award
We’re proud to have been announced the winner of the Innovative Mining Solution award in the 2020 Prospect Awards. The awards are held by Australian Mining and recognize Australia’s outstanding mining and minerals processing achievements.
How Digital Terrain is Putting Emesent’s Hovermap to Work
Mining information systems specialist Andrew Rouse is the founder and CEO of Digital Terrain, an IT mining services provider that improves the productivity and efficiency of underground mines through digitisation and IoT technologies.
Using Hovermap data in Deswik.AdvSurvey
In July 2020, we partnered with Deswik to help mining companies incorporate the high-quality data captured with Hovermap into their mine plans and surveys.
Interpine are speeding up forest imagery plotting with Hovermap
Hovermap datasets combine with Interpine’s customized deep learning algorithms for fast and accurate quantitative tree assessment.