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학술지 Multimodal layer surveillance map based anomaly detection using multi-agents for smart city security
Cited 18 time in scopus Download 163 time Share share facebook twitter linkedin kakaostory
저자
신호철, 나기인, 장지호, 엄태영
발행일
202204
출처
ETRI Journal, v.44 no.2, pp.183-193
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.2021-0395
협약과제
21HS4200, 실외 무인 경비 로봇을 위한 멀티모달 지능형 정보분석 기술 개발, 신호철
초록
Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multi-layered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4혻months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.
KSP 제안 키워드
Abnormal situation, Anomaly detection algorithm, Data collected, Data framework, Data representation, Integrated processing, Security Robots, Smart city, Temperature change, Two-Stage, behavior pattern
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