The New Role of Machine Learning in Road Infrastructure

When people think of road infrastructure, they normally think about potholes and construction work, but when you take a step back to think about the enormity of the road infrastructure it starts to dawn on people just how massive that system really is. In the United States alone, there are over 4.5 Million miles of roads most of which are managed at a local level.

Now imagine you are responsible for the monitoring, management, maintenance, and condition of some portion of those roads – what would you do? With previous technologies and the complexity of monitoring, the only viable solution was to manually inspect every road in order to compile the master plan of which roads need what repairs. At such a massive scale this is a considerable undertaking. Emerging technologies, however, are starting to change all of that.

“Machine learning” is at the forefront of technological innovation in many industries. Recently it has started making inroads into road management in the form of advanced road inspection technologies. These technologies allow a simple video data collection from the windshield of a vehicle and transforms it into the front-line solution for understanding the exact condition of millions-of-miles of roadway–simple and effective.

As these technologies continue to emerge and improve, newer and more advanced solutions will become more frequent. For instance, new research is starting to show the viability of dash mounted cameras for automated signage and other roadway feature inventories, and one day, assessments.

RoadBotics is at the forefront of this technological revolution by providing an effective solution for road managers to obtain a comprehensive road inventory and assessment. The RoadBotics team deploys professional drivers to collect video data that is then processed and analyzed using the RoadBotics proprietary machine learning cloud. Road managers now have the latest and greatest machine learning technology at their disposal.

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