With data coming from many sources, we believe in strengthening the existing silos of understanding roads. This will help to improve maintenance cost, efficient decision making on road access and over all transport for districts and ultimately the city.
Implementing maintenance procedures at right timing – will prove less disruptive – and more savings for district offices. Together with Machine Learning, the better the predictive capabilities of the transport system, ultimately will improve traffic flow, efficiency and real time challenges.
Reducing congestion, ultimately will result in improve quality of life.