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China's first three-dimension ground penetrating radar with AI technology launched

Updated: 2018-12-06

Eagle eye-A, China’s first ground penetrating radar using artificial intelligence (AI) is able to realize three-dimensional ground testing.jpg

Eagle Eye-A, China's first ground penetrating radar using artificial intelligence (AI) is able to realize three-dimensional ground testing. [Photo/sasac.gov.cn]

China Aerospace Science and Industry Cooperation (CASIC) launched Eagle Eye-A, China's first ground penetrating radar that uses artificial intelligence (AI) and is able to realize three-dimension ground testing, on Nov 27.

Eagle Eye-A can collect three-dimensional ground information in real time. Traditional ground penetrating radar can only receive signals of the tracks they move on.

The launching ceremony of Eagle eye-A, China’s first ground penetrating radar using artificial intelligence (AI) technology.jpg

The launching ceremony of Eagle Eye-A, China's first ground penetrating radar using artificial intelligence (AI) technology [Photo/sasac.gov.cn]

The new ground penetration radar is effective to tackle today's increasing underground security risks, such as road surface collapse and burning line leak caused by aging roads and rapidly expanding sub-ground lines, tubes and channels.

The energy and time conserving AI radar can autonomously detect, recognize and mark underground abnormalities and generate a report. Previous radars required statistical analysis. And the machine's reports are more reliable than those humans make which can be somewhat subjective. 

Eagle eye-A operates by being pulled by a car.jpg

Eagle Eye-A operates by being pulled by a car. [Photo/sasac.gov.cn]

The accuracy rate of the Eagle Eye-A's for pipelines is over 90 percent and its false alarm rate is less than 5 percent. Comparing with traditional ground penetrating radar, the Eagle Eye-A reduces the detecting time by 50 to 80 percent.

In the future, underground information collected by the Eagle Eye-A will form a big data platform which will help cities' underground management be more targeted and effective.



(Executive editor: Li Shuling)


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