Abstract. This paper presents an IoT architecture for the semantic interoperability of diverse IoT systems and applications in smart cities. The architecture virtualizes diverse IoT systems and ensures their modelling and representation according to common standards-based IoT ontologies. Furthermore, based on this architecture, the paper introduces a first-of-a-kind visual development environment which eases the development of semantically interoperable applications in smart citites. The development environment comes with a range of visual tools, which enable the assembly of non-trivial datadriven applications in smart cities, including applications that leverage data streams from diverse IoT systems. Moreover, these tools allow developers to leverage the functionalities and building blocks of the presented architecture. Overall, the introduced visual environment advances the state of the art in IoT developments for smart cities towards the direction of semantic interoperability for data driven applications.
One of the main challenges in modern Internet of Things (IoT) systems is the efficient collection, routing and management of data streams from heterogeneous sources, including sources with high ingestion rates. Despite the existence of various IoT data streaming frameworks, there is still no easy way for collecting and routing IoT streams in efficient and configurable ways that are easy to be implemented and deployed in realistic environments. In this paper, we introduce a programmable engine for Distributed Data Analytics (DDA), which eases the task of collecting IoT streams from different sources and accordingly, routing them to appropriate consumers. The engine provides also the means for preprocessing and analysis of data streams, which are two of the most important tasks in Big Data analytics applications. At the heart of the engine lies a Domain Specific Language (DSL) that enables the zero-programming definition of data routing and preprocessing tasks. This DSL is outlined in the paper, along with the middleware that supports its runtime execution. As part of the paper, we present the architecture of the engine, as well as the digital models that it uses for modelling data streams in the digital world. We also discuss the validation of the DDA in several data intensive IoT use cases in industrial environments, including use cases in pilot productions lines and in several real-life manufacturing environments. The latter manifest the configurability, programmability and flexibility of the DDA engine, as well as its ability to support practical applications.
A Smart City can be seen as a system in which different Internet of Things (IoT) solutions coexist and cooperate. According with this vision, the number of IoT deployments is, nowadays, in continuous expansion and it involves disparate scenarios, from street lighting, waste management, etc. However those initiatives are standalone, based on different protocols and standards, while the Smart City concept requires, on the other hand, integration and interoperability among all its stakeholders. To face this problem, in this paper we introduce the VITAL-OS architecture, that can monitor, visualize, and control all the operations of a city. Then, we present a practical use case of connecting a Sensor Network to this OS and we describe eCACHACA, a ranking mechanism that facilitates the discovery of services provided by each sensor. Performance has been evaluated via experimentation on the FIT IoT-LAB, and results demonstrate the effectiveness in the discovery of resources.
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