A Knowledge Fusion Approach for Context Awareness in Vehicular Networks

Vehicular Ad-hoc Networks (VANETs) are a challenging IoT scenario. While research is proposing increasingly sophisticated hardware and software solutions for on-board context detection, probably high-level context information sharing has not been adequately addressed so far. This paper proposes a novel logic-based framework enabling a contextual data management and mining in VANETs. It grounds on a knowledge fusion algorithm based on non-standard, nonmonotonic inference services in Description Logics, adopting standard Semantic Web languages. Ontology-referred context annotations produced by individual VANET nodes are merged with automatic reconciliation of inconsistencies. An efficient information dissemination protocol complements the proposal. The approach has been implemented in a vehicular network simulator and early experimental results proved its effectiveness and feasibility.