Aguilera, AnaAnaAguileraDominique GarridoIrvin DongoMaria Cornejo-Lupa2025-12-082025-12-082024-01-0110.1109/clei64178.2024.107003982-s2.0-85207856052https://cris-uv-2.scimago.es/handle/123456789/7875WOS:001337958300060The rapid adoption of Internet of Things (IoT) technology has allowed the development of applications where devices such as sensors generate data periodically. These devices are integrated into IoT systems where large volumes of data are managed and whose processing and handling for the proper operation of the IoT system is necessary. One of the main challenges in IoT is the effective data management and real-time communication between heterogeneous devices. Ontologies, which are semantic representations of knowledge, are built to provide semantic interoperability. However, the diversity of applications and the scope of new technologies makes current ontology's proposals incomplete in modeling privacy and security, energy awareness, and ethics at the same time. In this context, we propose an enhanced Ontology, called IoTO++, for improving semantic interoperability in IoT environments. We validated the proposal considering lexical, structural and domain knowledge levels. Results show that even though lite ontologies are more maintainable, compatible and transferable, ontologies with more annotations are better in terms of functional adequacy. This includes but is not limited to characteristics like, knowledge reuse, acquisition and representation. Furthermore, IoTO++ demonstrates superior performance in the domain knowledge level, proving to be a more effective solution for modeling the variety of IoT applications.enacceso restringidoComputer Science ApplicationsHardware And ArchitectureComputer Networks And CommunicationsArtificial Intelligenceproceedings paper