Feasibility of Using Intelligent Video for Machine Safety Applications
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Feasibility of Using Intelligent Video for Machine Safety Applications

  • 10/01/2008

  • Source: IAS '08: Conference Record of the 2008 IEEE Industry Applications Conference: Forty-third IAS Annual Meeting, October 5-9, 2008, Edmonton, Alberta, Canada. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2008 Oct; :1-5
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      Researchers at the National Institute for Occupational Safety and Health (NIOSH) are studying methods to prevent workers from being entangled in machinery used at mining operations. An analysis of mining accidents in the United States that resulted in a fatality or permanent disability from 2000 through 2005 showed 438 severe incidents that involved contact with machinery or equipment, an average of 73 per year. Researchers determined that the most common machinery involved in these severe accidents was conveyors. Also, a significant portion of the accidents occurred during machine maintenance and repair. Researchers are focusing on improved methods to prevent unintentional machine startup during maintenance activity and methods to detect workers near moving machine components. One new technology that shows promise for this application is intelligent video. Popular in the surveillance and security industries, these systems use cameras and computerized video analysis techniques to automatically detect the presence of people in preset zones within the camera’s field of view. A preliminary study has been initiated to determine if this technology could reliably detect the presence of workers in hazardous locations near machinery. Possible advantages of the use of this technology include improved detection zone demarcation and improved ability to distinguish between hazardous and non-hazardous proximity, compared to conventional proximity sensor techniques. Initial tests to detect a person near a conveyor system in daylight conditions showed promising results. A description of the technology, test procedures and results, implementation challenges, and future research needs are discussed.
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