To successfully monitor and actively control hydrodynamic and aerodynamic systems (e.g., wind turbine blade, wind farm, hydrofoil, aircraft wings), it can be critical to estimate and predict the unsteady flow around them in real-time. We propose to introduce a new algorithm to couple onboard measurements with fluid dynamics simulations and data in real-time without the need to rely on an extensive computational infrastructure. This coupling is achieved by combining a Proper Orthogonal Decomposition Galerkin method, a model under location uncertainty stochastic closure, and a particle filtering scheme. We focus our numerical tests on a two-and a three-dimensional wake flows at low and moderate Reynolds numbers, respectively. Using a single measurement point, we obtain almost optimal flow estimations for up to 14 vortex shedding cycles after the learning time window.