The Internet-of-Things (IoT) domain area is expanding rapidly and the fast immersion in our daily activities is changing the perception of people’s life, not only from a technological perspective else in the way how we do personal activities, professional career and also in the way we establish social interactions. IoT is already considered as crucial in the process for designing the Future of the Digitised Society. It is expected IoT also will revolution our perception of the world enabling more smartness to the different external aspects of the human being activities and economic activity (cities, industries, agriculture, clothing, fashion, etc.), At the IoT unit we investigate the convergence of software systems, the semantic web and the Internet, heavily focused on the evolution of sensor technologies and the semantic technologies to unify the real and the virtual worlds.

Core Research, The UIoT’s unit Core Research, focuses on investigating algorithms, methods and new scientific paradigms for the efficient use of Semantic Data Models (i.e. Taxonomies, Vocabularies, Ontologies, etc.) and Dynamic Data Streams Processing (i.e. ) with the aim for enabling semantic interoperability and enable the semantic unification of multiple application domains. We work in computer science areas towards Global sensor modelling for open space smart services (Data Modelling and Ontology Engineering), building the basis for using Continuous Queries for Linked Data Streams using SPARQL Query optimisation (Data Bases & Information Management) and using Machine Learning Algorithms for query optimisation. We have extended the RDF for its use in different application domains by using Stream transformations and data Federation (Data Transformation and processing), implementing RDF engines in mobile and edge devices.

We have described the IoT stack and fog Computing Models and contributed on describing data federation model for IoT edge nodes, we have extended the use of Semantic Web Models & Linked data for IoT and worked towards supporting Flash-friendly databases and Graph-based models for heterogeneous personal data integration using Spatial-temporal Data Management. We have created the Semantic Interoperability framework (SEG 3.0) for Distributed Systems and the Data Interplay in Edge Computing using the Linked Data paradigm, in both works we have got awards for these Scientific Contributions/Publications. At UIoT we have advanced the state of the art on Pervasive Computing using Semantic data Modelling and Context Awareness methods to extend the “Autonomics” parading for networking systems.

Applied Research, at the UIoT Applied Research projects we focus on deploying living labs and demonstrators for real-life use cases in industrial, social and academic environments using Semantic Web and its techniques (i.e. Linked-Data, Data Stream Processing, Data Access Optimisation, etc.) to demonstrate the value of Processing Data and Semantic Analytics Tools. Our Living labs and demonstrators provides realisation to use cases for Smart Building, Smart Environmental Monitoring, Smart Traffic Management, Smart Campus, Wellbeing and Healthcare, etc.

The UIoT in-home developed technologies are state of the art proof-of-concept and reference implementation tools such as: The Linking Sensor Middleware (LSM), the multi-processing of data streams with different data formats (Super Stream Collider), the continue access and Continuous Query Evaluation over Linked Data such as the graph of things(CQELS) and the reference Implementation for Openly connect Sensor Data to the Cloud using Semantic annotation (OpenIoT), the Interoperability of Data Services using Virtualisation and Multi-Layer Accessibility (VITAL-OS), the Federation of geographically distributed Data Services and Systems (FIESTA-IoT) and the Data marketplace for offering and unifying technology (BIG IoT), among others.

Industrial Projects, The UIoT has worked in partnership with industry partners for the development of flexible IoT middleware technology focuses on abstracting data from heterogeneous sensor networks and bring this to a higher application-level(s) for enabling extended systems’ functionalities and also enable interconnected sensor networks and sensor web data interoperability by using the Internet.

We extensively work with industries for piloting solutions and execute large-scale deployments, mainly in sensor data collection, annotation and data transformation and processing by means of using advance stream processing techniques. We also work on the design principles for device and infrastructure-related architectures, technologies and protocol frameworks for Internet connected heterogeneous devices. Our Industrial partners have described our collaborative works as putting “semantics in the box and at the edge” and “as pioneer approaches for using semantic web technologies in IoT”.