Southampton 'space archaeology' solution awarded Royal Academy of Engineering Enterprise Fellowship
Postgraduate researcher Iris Kramer from the University of Southampton is being supported by the Royal Academy of Engineering as she scales deep learning software that identifies buried ancient sites from space.
The archaeologist turned computer scientist has been awarded an Enterprise Fellowship for her ArchAI start-up, which is based on techniques developed in the Vision, Learning and Control research group.
The venture has also received backing from the UK Space Agency this month, through funding from the national Space Research and Innovation Network for Technology (SPRINT) programme.
Iris' AI solution helps smooth expensive planning processes for developers and saves historical sites from unnecessary destruction by automating archaeological assessments.
Iris says: "I'm delighted to receive this award and recognition from the Royal Academy of Engineering. Using ArchAI's technology over conventional techniques, developers could save hundreds of thousands of pounds in costs in addition to time savings of six months on a major housing or road development of 100 hectares.
"That's just one use for our technology and the Enterprise Fellowship programme will accelerate ArchAI towards addressing wide-ranging environmental challenges globally."
Space archaeology uses satellites or high-flying aircraft to take pictures of the Earth's surface to find hints of ancient features buried under the ground. Things may show up visually or near infrared may show small differences in vegetation, with growth on top of buried stone likely to be less healthy.
Dr Fraser Sturt, a Professor of Archaeology at the University of Southampton, says: "Aerial photography transformed archaeology in the early 20th century, revealing sites in a way that few people could have conceived of in the past. Advances in Earth Observation and Machine learning offer another leap forward, helping us to identify and monitor sites across of space and time. This information is critical not only for our understanding of the past, but how we manage the built environment and its development in the future."
Iris' PhD research is the first in the world to apply deep learning to the detection of archaeological sites from Earth Observation data. The project has trialled the deep learning techniques with Historic Environment Scotland to automatically identify hundreds of archaeological sites.
Last year, she became one of just six participants to be selected for the Ordnance Survey and HM Land Registry Geovation Accelerator Programme.
In October, she pitched for ArchAI in a Dragons' Den-style event hosted by the University's Future Worlds start-up accelerator. The business impressed the dragon investors and she received a ÃÂ£70,000 offer of investment at the highest ever valuation in the event's history.