IRD announces strong third quarter, launches new products

Intelligent transportation systems provider International Road Dynamics (IRD) has announced solid financial results for the third quarter of 2016, with revenues up 16.0 per cent to US$36.6 million (CA$48.4 million) on growth in key North American markets and an increase in gross margin to 32.5 per cent. Nett earnings increased 27.5 per cent to US$1.6 million (CA$2.2 million). The company says it is in a strong financial position with working capital of US$10 million ($13.3 million). According to Terry Be
Classification & Data Collection / October 14, 2016
Intelligent transportation systems provider 69 International Road Dynamics (IRD) has announced solid financial results for the third quarter of 2016, with revenues up 16.0 per cent to US$36.6 million (CA$48.4 million) on growth in key North American markets and an increase in gross margin to 32.5 per cent. Nett earnings increased 27.5 per cent to US$1.6 million (CA$2.2 million). The company says it is in a strong financial position with working capital of US$10 million ($13.3 million).

According to Terry Bergin, IRD president and CEO, the company’s strong operating performance continued in the third quarter, underpinned by a significant increase in gross margin and further growth in our solid base of recurring service and maintenance revenues.

"Looking ahead, we continue to believe fiscal 2016 will be another year of record revenues and net earnings as we continue to leverage our strong presence in the growing global ITS market," he said.
 
IRD also recently launched VectorSense and VI2M (Vehicle Information-In-Motion), which were developed to meet the needs of highway and roadway authorities to provide previously unavailable traffic and vehicle data.  This includes tire width and axle configuration including identification of single, dual and new super-single tires being used on large trucks, enhanced vehicle and truck identification, bicycle lane traffic, vehicle lane position and safety information such as under-inflated tires.  This data is collected while vehicles travel at highway speeds.

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