Mathematics for Detecting, Locating and Characterising Metal Objects

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Mathematics for Detecting, Locating and Characterising Metal Objects

 01 Jun 2021

Online

  • Paul Ledger, Keele University
  • Bill Lionheart, University of Manchester

About:

Sponsored by EPSRC and the Royal Society research on  the mathematical theory underpinning new  developments in detecting, locating and characterising metal objects has progressed in recent years. Read more here

Application areas for this technology are widespread. Areas of interest include, but are not limited to, early detection of threat objects (eg knives and guns) for security screening at transport hubs and public events, Identification of hidden anti-personal mines and unexploded ordnance in areas of former conflict, Identification of metallic objects of value in treasure hunts and in archaeological searches, non-destructive testing and determining integrity of reinforcement in concrete structures, ensuring food safety by identification of unwanted metallic contamination, scrap sorting to identify precious metals, finding hidden cables in walls and underground, discriminating between different coins in vending machines and automated checkouts.

We are looking to build a research/end-user community for metal detection. 

This afternoon event was the initial community builiding activity and included: 

  • a series of short presentations overviewing the research in this area

  • short metal detection challenges 'pitches' - followed by breakout sessions linking these challenges and the research

  • discussion forum - how to support the activity going forward

 

Programme:

Bill Lionheart, The University of Manchester Welcome
Paul Ledger, Keele University Object characterisation with MPT spectral signature
Michael O'Toole, The University of Manchester Metal detection and metal characterisation research at Manchester: New innovations on an established technology
Break
Sadia Rowshan, Department for Transport Overview of different transport security challenges relating to metal detection
Christos Ktistis, Mettler Toledo Safeline Metal detection challenges in the food industry: noise robust classification, and coil geometry optimization
Group discussion
Break
Smaller group discussions to discuss research priorities and suggested next steps
Wrap up and summary
Close

Sponsors and Funders:

This event is supported as part of the ICMS Knowledge Exhange Support for Academia-Industry Meetings.