Infrared Drones Could Detect Dangerous ‘Butterfly’ Landmines in Post-Conflict Regions
Researchers from Binghamton University (BU) report that drones with infrared cameras can be utilized to detect remnant minefields in post- conflict countries.
According to The U.S. Department of the Interior’s Bureau of Land Management and U.S. Fish and Wildlife Service around 100 million military munitions and explosives of concern devices are deposited unclaimed in the world. Majority of these munitions are surface plastic landmines with low-pressure triggers, such as the mass-produced Soviet PFM-1 “butterfly” landmine. The name is credited by the small size and butterfly-like shape of these mines that are difficult to locate and clear. These mines possess a low trigger mass and do not include any metal component, practically making them invisible to metal detectors. These mines earned the notorious name of ‘toy mines’ due to high casualty rate among children who find them playful in post- conflict nations such as Afghanistan.
To tackle the issue, researchers at Binghamton University devised a new method to accurately detect these mini landmines using low-cost drones. Alex Nikulin, assistant Professor of Energy Geophysics at BU equipped the drones with infrared cameras that can remotely map the dynamic thermal conditions of the surface and recorded distinct heat signatures associated with the plastic casings of the mines. In several experiments the study revealed that the mines heated up at a much-greater rate than surrounding rocks. The drones were able to recognize the mines by their shape and apparent heat signatures. Moreover, the experiments conducted in early hours of the day gave prominent results as the heat signatures were more transparent. These results are promising in rapid identification of surface plastic MECs. The report was published in the journal The Leading Edge on June 19, 2018. These low cost infrared drones possess great potential for a wide spread use in post- conflict countries as it increases detection accuracy along with minimal labor cost.
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