Identifying road defect information from smartphones

Defect repair, for example potholes, is one of the most common and expensive tasks of road maintenance. One of the difficulties of this form of asset management is in identifying these defects early. Although a defect may take many years to initiate, once begun they can propagate rapidly with further deterioration increasing the cost and subsequent repair time. This paper introduces a methodology to collect real time acceleration data from smartphones operated by the road going public. Smartphones are rapidly becoming cheaper, more reliable, more utilised and importantly, more powerful. This paper describes an analysis technique which takes smartphone accelerations to create profiles and identify likely defects and their corresponding severity. A trial test section was compared between visual survey and the defect detection algorithm in this paper with good correlation to the position and severity of identified defects. The detection algorithm clustered likely defects from a series of repeated runs at various speeds. The precision and accuracy in this test trial show that a full network application is possible from the current smartphone technology