A Crowd-Based Explosive Detection System with Two-Level Feedback Sensor Calibration

Chengmo Yang, Patrick Cronin, Agamyrat Agambayev, Sule Ozev, A. Enis Cetin, Alex Orailoglu

Research output: Contribution to journalConference articlepeer-review

Abstract

Large, open, public events, such as marathons and festivals, have always presented a unique safety challenge. These sprawling events, which can take up entire city blocks or stretch for many miles, can draw tens to hundreds of thousands of spectators and in some cases have open admission. As it is impracticable to guarantee the subjection of every event-goer to a security screening, we propose a crowd-based explosive detection system that uses a multitude of low-cost ChemFET sensors which are distributed to attendees. As the sensors offer limited accuracy, we further propose a server-based decision-making framework that utilizes a two-level feedback loop between the sensors and the server and explores spatial and temporal locality of the collected data to overcome the inherent low-accuracy of individual sensors. We thoroughly explore two distinct detection schemes, stressing their performance under a myriad of conditions, thus showing that such a crowd-based detection system comprised of low-cost and low-accuracy sensors can deliver high detection accuracy with minimal false positives.

Original languageEnglish (US)
Article number9256458
JournalIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Volume2020-November
DOIs
StatePublished - Nov 2 2020
Externally publishedYes
Event39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020 - Virtual, San Diego, United States
Duration: Nov 2 2020Nov 5 2020

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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