With predictions of shared bike movements, operators can easily identify how to increase yield with fewer bikes, as well as how to predict availability of the cycles at docks and so improve user satisfaction.
HAL24K’s data intelligence solution predicts the weekly number of replacement vehicles needed per hub and boosts efficiencies for roadside assistance provider.
Data from induction loops, local weather, historical ticketing and calendar data, were used to build operational traffic intensity models to predict traffic at toll plazas. Sharing forecasts with drivers allows them to make departure time changes and avoid congestion.