Browse > Article
http://dx.doi.org/10.15683/kosd.2014.10.1.105

Experimental and Analytical Study on the Water Level Detection and Early Warning System with Intelligent CCTV  

Hong, Sangwan (Strategic Planning Team, UDP Technology Ltd.)
Park, Youngjin (Disaster Information Research Division, National Disaster Management Institute)
Lee, Hacheol (Dept. of Information and Communication Eng., Yuhan University)
Publication Information
Journal of the Society of Disaster Information / v.10, no.1, 2014 , pp. 105-115 More about this Journal
Abstract
In this research, we developed video analytic algorithms to detect water-level automatically and a system for proactive alarming using intelligent CCTV cameras. We applied these algorithms and a system to test-beds and verified for practical use. We made camera-selection policies and operation plans to keep the detection accuracy high and to optimize the suitability for the ever-changing weather condition, while the environmental factors such as camera shaking and weather condition can affect to detection accuracy. The estimation result of algorithms showed 90% detection accuracy for all CCTV camera types. For water level detection, NIR camera performed great. NIR camera performed over 95% accuracy in day or night, suitable in natural weather condition such as shaking condition, fog, and low light, needs similar installment skills with common cameras, and spends only 15% high cost. As a result, we practically tested water level detection algorithms and operation system based on intelligent CCTV camera. Furthermore, we expect the positive evidences when it is applied for public use.
Keywords
Intelligent CCTV camera; Automatic water level detection; Accuracy deduction prevention; Proactive alarm system; NIR camera;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Bilateral Filtering for Gray and Color Images, http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/MANDUCHI1/Bilateral_Filtering.html.
2 Jeong Taeseong, Jin Gyeonghyeok, Choi Seonhwa, Ku Sinhoe, Kwuan Dohyeon, National Disaster Management Institute (2008). Development of decision support system for mitigation of flood related damage. National Disaster Management Institute, Seoul.
3 Minister of Land, Infrastructure, Park Jeongrim, Dongbu Engineering (2008). Complement the Basic plan of Foold Risk Map. Minister of Land, Infrastructure, Seoul.
4 Korea Water Resources Corporation (2008), Flood disaster management Geographic Information System in Pyeongtaek, Korea Water Resources Corporation, KIWE-HRC-08-14.
5 John Honovich (2012). Selection Standard of Video Analytics : How to Select Video Analytics. IPVM, http://ipvm.com/report/how_to_select_video_analytics.
6 Natinal Disaster Management Institute (2013). A study on Mid-Long term planning for CCTV based Smart Disaster Management. Natinal Disaster Management Institute, Seoul.
7 A Study of Quality Evaluation Model for Intelligent Video Surveillance Solution(2010)
8 Korea Information Security Center (2010). Final Report : A Study on Construction DB and Certification Test Plans for Intelligent CCTV based on Behavior. Korea Information Security Center, KISA-WP-2012-0060.
9 Digital Image Processing 2nd, Rafael C. Conzalez, Richard E. Woods. A probabilistic model for flood detection in video sequences, Paulo Vinicius Koerich Borges, Joceli Mayer, Ebroul Izquierdo OpenCV, http://opencv.willowgarage.com/wiki/