Unexploded landmines have severe post-conflict humanitarian repercussions: landmines cost lives, limbs and land. For deminers engaged in humanitarian landmine clearance, metal detectors remain the primary detection tool as more sophisticated technologies fail to get adopted due to restrictive cost, low reliability, and limited robustness. Metal detectors are, however, of limited effectiveness, as modern landmines contain only minimal amounts of metal, making them difficult to distinguish from the ubiquitous but harmless metallic clutter littering post-combat areas. We seek to improve the safety and efficiency of the demining process without introducing an inviable replacement for the metal detectors. Instead, we propose and evaluate a novel, pattern-based visual support approach inspired by the documented strategies employed by expert deminers. In our laboratory study, participants provided with a prototype of our support tool were 80% less likely to mistake a mine for harmless clutter. A follow-up study demonstrates the potential of our pattern-based approach to enable peer decision-making support during landmine clearance. Lastly, we identify several design opportunities for further improving deminers' decision making capabilities.
Lahiru G. Jayatilaka, Luca F. Bertuccelli, James Staszewski, and Krzysztof Z. Gajos. Evaluating a pattern-based visual support approach for humanitarian landmine clearance. In CHI '11: Proceeding of the annual SIGCHI conference on Human factors in computing systems, New York, NY, USA, 2011. ACM.