“Crowdsourced” data from a Smartphone can help in maintaining road quality


Smartphones are proving to be useful for more than just surfing the internet, using mobile applications, or simply just for making calls. The data sourced from the use of modern phones are being used in various ways that we might have not imagined. Recently, researchers from the University of Birmingham have established that GPS and motion sensors in smartphones could be used for crowdsourcing information on road quality. This information can make road maintenance a lot easier by allowing the government and maintenance firms to easily identify road areas that require repair.

Road roughness is an important indicator of how efficient the road network of a city is. This indicates how smooth the ride quality is and help the roads maintenance authorities to keep a check on the condition of the roads to ensure an efficient network of commute for the general public. But in cities with large road networks, the agencies and authorities lack the resources to assess the damage of the roads and make an informed decision to devise an effective maintenance or repair plan.

This method involves using three-axis accelerometers and GPS tracking coupled up with a low-cost app to record the vertical movement of vehicles and relating that to the carriageway. It can turn up as an easy and effective measure for civil engineers. The researchers say that the phone sensors are powerful and accurate enough to register a vertical motion that the road roughness cause. When this accelerometer data is matched with the phone’s GPS information could help in better identifying the trouble spots on the road.

While identifying road roughness, the International Roughness Index (IRI) is the most commonly used measure. But even measuring this index for a wide road network can be quite expensive if traditional technological methods are used. For instance, the cost of collecting data for road roughness in the US can cost between $1.4 and $6.2/kilometer, depending on the state. Using smartphones for detecting rough roads can significantly lower this cost.


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