Firearm Detection Using Wrist Worn Tri-Axis Accelerometer Signals

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dc.contributor.authorKhan, Md Abdullah Al Hafiz
dc.contributor.authorWelsh, David
dc.contributor.authorRoy, Nirmalya
dc.date.accessioned2018-06-11T18:36:35Z
dc.date.available2018-06-11T18:36:35Z
dc.description.abstractGunshot detection traditionally has been a task performed with acoustic signal processing. While this type of detection can give cities, civil services and training institutes a method to identify specific locations of gunshots, the nature of acoustic detection may not provide the fine-grained detection accuracy and sufficient metrics for performance assessment. If however you examine a different signature of a gunshot, the recoil, detection of the same event with accelerometers can provide you with persona and firearm model level detection abilities. The functionality of accelerometer sensors in wrist worn devices have increased significantly in recent time. From fitness trackers to smart watches, accelerometers have been put to use in various activity recognition and detection applications. In this paper, we design an approach that is able to account for the variations in firearm generated recoil, as recorded by a wrist worn accelerometer, and helps categorize the impulse forces. Our experiments show that not only can wrist worn accelerometers detect the differences in handgun rifle and shotgun gunshots, but the individual models of firearms can be distinguished from each other. The application of this framework could be extended in the future to include real time detection embedded in smart devices to assist in firearms training and also help in crime detection and prosecution.en_US
dc.description.sponsorshipThis research is partially supported by the ONR under grant N00014-15-1-2229.en_US
dc.format.extent6 pagesen_US
dc.genrejournal articles preprintsen_US
dc.identifierdoi:10.13016/M2F47GX51
dc.identifier.urihttp://hdl.handle.net/11603/10912
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectgunshot detectionen_US
dc.subjectfirearm model detectionen_US
dc.subjectfirearm recoilen_US
dc.subjectwrist worn accelerometeren_US
dc.titleFirearm Detection Using Wrist Worn Tri-Axis Accelerometer Signalsen_US
dc.typeTexten_US

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