The design of a random number generator is a challenging task on systems in changing environment such as smartphones. Finding reliable and high-throughput sources of entropy is difficult. This paper proposes an online entropy estimation algorithm to test the quality of an entropy source when nothing is known \textit{a priori} on the source statistics. Our estimator can be executed at a low cost and is adapted for any type of sources. It extends the results of Bucci and Luzzi to non-binary sources and introduces a parameter that allows to trade time and memory for a better estimate. Our estimator is then applied to several sources available on an iPhone and compare to the state of the art.