Funder: This internal project is funded by De Montfort University (DMU), Leicester, UK (23.5K GBP) ;
Programme: DMU Global Challenges Research Fund;
Principal Investigator: Dr Fabio Caraffini (DMU);
Co-investigator: Dr Mario Gongora (DMU);
Internation partner : Prof. Carlos Parra, Ponteficia Univerisdad Javeriana (PUJ), Bogota, Colombia;
Research Assistants: Ms Johana Maria Florez Lozano (PUJ)
The new peace process in Colombia is providing a new lease of life to rural communities but raising many issues and challenges, both social and operational. Lands that were in no-go zones are now available for use but have many issues from direct effect from war such as land mines, to indirect such as debris, pollution and exhaustion. On the other hand technologisation in agriculture is very limited in those regions.
The PUJ has a very strong social engagement and impact in all faculties and is working in both social and operational aspects to support the sustainable development of these communities; one of the projects involves the use of multiple sensors to measure the land and help optimise its use.
Sensing land characteristic and detecting buried objects is very complex and no one sensor or method can achieve this optimally. With multiple sensors, computational intelligence based data fusion, analysis and decision making techniques we can optimise the performance of various systems.
We are currently collaborating with PUJ in optimising a land scanning platform that uses an array of sensors and other data sources. We are using improvised land mine detection as a case study but this will be expanded to other applications for the optimal use of land.
Our collaboration will put together PUJ’s links with key rural communities and their sensing robotic platforms, with our CI, optimisation and decision making expertise to enable scaling their capabilities to many applications and large data sets and large expanses of land.
On the UN International Awareness Day we are kick-starting our GCRF funded project at our Colombian partner's robotics lab with the mine detection sensor array.
Data, source code, preprints and dissemination material is available at our Figshare project page!