For users to fully benefit from mobile services, technology should offer them personalised,seamless and transparent access to information focused on their needs, when they need it,taking into account their situation. Today, still some challenges have to be solved. This ismainly due to the difficulties to manage efficiently heterogeneous and unstable communicationnetworks, as well as of limited performances of personalisation solutions in this context.CLAIRVOYANT aims at contributing to the issue of context-aware mobile services throughadaptation of information transmission to the end-user and her/his context, all along thetransport chain. From a quality of service point of view, it focuses on the optimisation of a)information transmission in hybrid communication networks; b) gathering and aggregation ofinformation in these networks; and c) filtering algorithms for context-aware provision ofpersonalised information on mobile devices.Network management will be addressed using mobility management techniques with regard tothe self-organised and context-aware information transmission solution with the followingobjectives: 1) the best underlying access network for communication is selected at each giveninstant according to each context/situation and user preferences; 2) the best routing algorithmsare chosen to establish communication, taking into account network topology changes and usermobility; 3) the best instant for information transmission is decided, mainly in the case of delaytolerantservices.A multi mobile agents system will be investigated for the abstraction of the communicationnetwork, and for the aggregation of contextual information out of the network. The two followingobjectives will be targeted: 1) the abstraction layer removes any dependency due to thenetwork, providing a low coupling with the personalisation engine that facilitates the informationfiltering process; 2) the agent system is organised so as to optimise the informationmanagement and aggregation from any source including ad-hoc networks formed by terminaldevices, targeting near real-time processing of requests.On the filtering side, semantic web technologies coupled with fuzzy theory will be investigated.The first provides efficient means to formalise knowledge, defining its semantics, and toconduct reasoning on it. The second offers a framework to represent partial truth and imprecisevaluations such as those represented with linguistic variables, and allows for approximatereasoning. It offers a natural way to deal with imprecise preferences in the user profile, as wellas confident values of contextual information. The addressed question is the suitability ofontological knowledge processing, helped by fuzzy logic, to deal with complex contextual oruser-related data, and to provide an efficient mean for personalisation in hybrid networksenvironment. This means in particular dealing with network availability, mobile environments’technical constraints, user’s situation gathered from multiple heterogeneous sources, etc. allleading to imprecise, partial or missing data.The three identified axes will be investigated within the framework of a global system to be built.While algorithms for each will be elaborated and tested independently, they will be adjusted inthe integrated system targeting the best average global performances. The tuned system will beassessed on an experimental use case of multimodal transport.