Detection and aggregation of anomalies in data from sensors placed in smartphones.

Summary Wireless and mobile networks have developed enormously in recent years. Far from being reserved for industrialized countries, these networks requiring a limited fixed infrastructure have also imposed themselves in emerging and developing countries. Indeed, with a relatively low structural investment compared to the one necessary for the implementation of a wireline network, these networks allow operators to offer a very wide coverage of the territory, with a cost of access to the network (price of the telephone and the communications) completely acceptable for the users. Therefore, it is not surprising that today, in most countries, the number of wireless phones is much higher than the number of fixed phones. This large number of terminals spread all over the world is an invaluable reservoir of information, of which only a tiny part is currently exploited. Indeed, by combining the position of a cell phone and its speed of movement, it becomes possible to deduce the quality of roads or road traffic. On another note, by integrating a thermometer and/or a hygrometer in each terminal, which on a large scale would imply a derisory unit cost, these terminals could serve as a relay for a more reliable local weather forecast. In this context, the objective of this thesis is to study and analyze the opportunities offered by the use of data from mobile terminals, to propose original solutions for the processing of these large masses of data, insisting on the optimizations (fusion, aggregation, etc.) that can be realized in an intermediate way in the context of their transport to the storage and processing center(s), and eventually to identify the data not available today on these terminals but that could have a strong impact in the years to come. A prototype presenting a typical example of use will allow to validate the different approaches.