With the release of Android 7 (Nougat)1, Google provided Android developers with access to the GNSS raw data from the smartphones’ chipset. Since then, several research activities have been conducted by the GNSS community to analyse the quality of the raw measurements provided by different Android devices. In this context, the proposed paper will analyse the benefits of applying EDAS corrections to raw measurements from different Android devices in comparison with the position provided by the smartphone chipset. EDAS (EGNOS Data Access Service) is the EGNOS internet broadcast service, which provides free of charge access to the data generated and collected by the EGNOS infrastructure. EDAS gathers all the raw data coming from the GPS, GLONASS and EGNOS GEO satellites collected by all the receivers located at the EGNOS reference stations, which are mainly distributed over Europe and North Africa. Once the data are received, EDAS disseminates them over the Internet in real time and also through an FTP archive. The EDAS services portfolio is the result of the various protocols and formats supported, along with several types of GNSS data made available to users by each service. EDAS, through its SISNeT and Ntrip services, provides, respectively, EGNOS wide area corrections to GPS signals in RTCA format  and differential corrections to the GPS and GLONASS in RTCM format. These EDAS products will be the key enablers for the proposed study. To assess EDAS potential in this context, the GNSS raw measurements collected by different Android devices (Huawei P30, Xiaomi M8) have been tested in open sky and rural, as well as in static and dynamic (i.e. pedestrian) scenarios. Data recorded during the tests using Google’s GNSSLogger application has been analysed in detail as part of this paper, looking at the key performance indicators that characterize the GNSS navigation solution (i.e. accuracy, availability) and how they are reflected in the different indicators made available by the Android API. The Android API provides several quality indicators which have proven to be useful to identify and filter potentially misleading data as part of the measurement reconstruction and smoothing process. Since the smoothing of the code is a must in order to inject sufficiently clean measurements to the position engine, the understanding of these indicators and their link to the received code or phase measurements is essential. The position provided by the device (internal chipset) has been compared with respect to the GPS L1 Single Point Positioning (SPP) solution obtained by post-processing the reconstructed and smoothed pseudo-ranges obtained from the Android API. These results have also been compared with the position obtained when applying the differential (RTCM format) and EGNOS (RTCA format) corrections, provided by EDAS, to the same measurements. An independent solution from a survey grade receiver has been used as reference. Therefore, to sum up, the performance obtained with the following position solutions has been analysed in detail for each device: • Device computed solution (internal chipset). • GPS L1 SPP solution. • EDAS based Differential position. • EGNOS based position (using the EGNOS message in RTCA format provided by EDAS). Globally, the objective of this paper is twofold; as a first step, the adequacy of the GNSS raw data provided by the Android API to apply code differential position techniques has been assessed, looking at critical aspects for differential code positioning such as the noise level and multipath induced errors (local errors) and the way to handle them as part of the measurements’ smoothing process. After that, the corrections provided by EDAS have been applied to the available set of Android raw measurements in order to present the performance benefits associated to the use of EDAS, a free of charge service, as an external corrections source.