Press Releases

Federal Railroad Administration Awards IEM Contract to Develop Smart Grade Crossing Monitor,   
Thursday, Feb 25, 2016

International Electronic Machines Corporation (IEM) announces the award of a two-year contract for continued development of a video-based Smart Grade Crossing Monitor. IEM will advance technology originally developed under a proof of concept contract from FRA that was completed in the fall of 2010.

Grade crossing safety continues to be a significant challenge for railroads and local and state law enforcement agencies and departments of transportation. IEM’s video based approach can provide all-weather, day-night monitoring of grade crossing that will automatically identify and track vehicles (including bicycles and motorcycles) and pedestrians as they pass through a highway rail grade crossing. In the event that a vehicle or person stops on the track for an extended period of time, IEM’s Smart Grade Crossing Monitor will automatically notify proper authorities.

In addition to serving to improve grade crossing safety, the technology behind this system has direct applicability to improved security monitoring as well and can be used for trespass detection.

Under the current contract, IEM will build and deploy multiple prototypes of the Smart Grade Crossing Monitor first at a site near Albany, NY and later as part of an ongoing FRA-sponsored trespass detection program in West Palm Beach, FL.

About IEM

IEM develops, produces, and markets innovative imaging, optical, and other sensor based systems for safety and security applications in the intelligent transportation system industry. By combining innovative sensor systems with advanced software, IEM creates intelligent solutions for use in vehicle inspection, security monitoring, maintenance activities, and more. IEM hold multiple patents covering a wide range of technologies including advanced machine vision, non-destructive evaluation, thermal infrared inspection, innovative cameras, security monitoring, and wireless sensors and sensor networks.