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Naimuri goes undercover with 42 Engineer Regiment (GEO)

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Data intelligence specialist Naimuri has partnered with 42 Engineer Regiment (GEO), part of the National Centre for Geospatial Intelligence, for its new client-facing technology conference for Tech, Academia and Government (TAG).

42 Engineer Regiment (Geographic) is a Royal Engineers regiment of the British Army. The regiment, formed originally in 1947, provides field deployable geographic services, including geodetic survey, terrain analysis, information management and dissemination and geospatial intelligence.

The event saw over 100 people from across academia, government and technology unite at Naimuri’s Manchester HQ and listen to six academics from across the North of England share a range of data insights and solutions to explore problem solving techniques to establish ‘how to better understand the characteristics of a forest from satellite imagery, using a range of data analysis techniques.’

TAG was launched in June 2022 and was the brain-child of Dr Phininder Balaghan, Innovation and Engagement Lead at Naimuri. His vision was to build upon the foundations of Naimuri’s ‘Data Intelligence Centre of Excellence’ (DICE) and to create an event which would meet real life challenges at the heart of government, and defence, by delivering innovative ideas, showcasing ground-breaking data and state-of-the-art academic research.

Dr, Phininder Balaghan, innovation and engagement lead, who joined the company from the University of Hull, said: “When we launched TAG back in 2022, we could not have anticipated the success of the event and it was wonderful to work with the MOD and 42 Engineer Regiment (GEO) for our second event. TAG is very much part of our Data Intelligence Centre of Excellence and was created to push boundaries and explore and drive collaboration and revolutionise change. We are the first in the North West tech scene to run an in-house technology conference of this kind and feel in a fortunate position to enable our partners to come together in a supportive and secure environment and to explore the realms of what is possible. We look forward to growing the TAG brand and creating further events and collaborations.”

SSgt Warren Slade, Cap Dev Ssgt, Strategic Command, Defence Intelligence, added: “TAG was a well organised event from the onset, with clear direction on the agenda, objectives, challenges, talks and the networking in between. The talks were meticulous, insightful and informative, which provided my team and I multiple avenues to immediately explore and identify a possible solution for the problem set. All the academics were extremely engaging and really eager to tackle such a simple problem ‘on paper’, but extremely complex to accomplish in reality. TAG would have not been possible without all of the hard work and dedication from the Naimuri team, who all had such great work ethic and positivity. We hope there’ll be more opportunities to work with Naimuri in the future”.

Six universities presented research to help solve the problem, including Newcastle University, who discussed how active learning and hierarchical classification can be combined to meet the challenge; Manchester University, who gave an overview of object change detection or disaster assessments using satellite imagery; the University of Hull, who set out how we can use Astronomical Cartographic Techniques to find tree trunks; Liverpool John Moores, who showcased a number of different data science techniques, such as time series activity detection; the University of Sheffield, who showed a plan for solving the challenge, sending a satellite into space next year that can use P-waves to go through the canopy, and the University of York, who presented data science techniques in finding obscure items in satellite images.

Data intelligence company, Naimuri was founded in 2015 and taken over by global defence giant QinetiQ in 2020. At the turn of 2023 the company revealed it had doubled its headcount to 140 since the takeover, as well as registering a 25 per cent increase in turnover during the previous year.

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