Human and Object Detection in Smoke-Filled Space Using Millimeter-Wave Radar Based Measurement | Zendy

Yoshimitsu Aoki | Zendy; Masaki Sakai | Zendy

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Human and Object Detection in Smoke-Filled Space Using Millimeter-Wave Radar Based Measurement

Author(s) -

Yoshimitsu Aoki,

Masaki Sakai

Publication year - 2006

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2006.p0760

Subject(s) - extremely high frequency , smoke , radar , computer science , reflection (computer programming) , task (project management) , blocking (statistics) , object (grammar) , object detection , space (punctuation) , computer vision , millimeter , artificial intelligence , remote sensing , real time computing , engineering , geology , geography , pattern recognition (psychology) , telecommunications , physics , optics , systems engineering , meteorology , computer network , programming language , operating system

One of the greatest problems in rescue operations during fire disasters is the blocking of firefighters’ view by dense smoke. Assuming that a firefighter’s most important task is to understand the situation within a smoke-filled space. We developed a way to do so, starting by scanning space using millimeter-wave radar combined with a gyrosensor. To detect persons and objects, we constructed a 3D map from signal reflection datasets using 3D image processing. We detail our proposal and report results of measurement experiment in actual smoke-filled areas.

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