IoT systems are now being deployed worldwide to sense phenomena of interest. The existing IoT systems are often independent which limits the use of sensor data to only one application. Semantic solutions have been proposed to support reuse of sensor data across IoT systems and applications. This allows integration of IoT systems for increased productivity by solving challenges associated with their interoperability and heterogeneity. Several ontologies have been proposed to handle different aspects of sensor data collection in IoT systems, ranging from sensor discovery to applying reasoning on collected sensor data for drawing inferences. In this paper, we study and categorise the existing ontologies based on the fundamental ontological concepts (e.g., sensors, context, location, and more) required for annotating different aspects of data collection and data access in an IoT application. We identify these fundamental concepts by answering the 4Ws (What, When, Who, Where) and 1H (How) identified using the 4W1H methodology.
The Internet of Things (IoT) concept has attracted a lot of attention from the research and innovation community for a number of years already. One of the key drivers for this hype towards the IoT is its applicability to a plethora of different application domains. However, infrastructures enabling experimental assessment of IoT solutions are scarce. Being able to test and assess the behavior and the performance of any piece of technology (i.e. protocol, algorithm, application, service, etc.) under real-world circumstances is of utmost importance to increase the acceptance and reduce the time to market of these innovative developments. This paper describes the federation of eleven IoT deployments from heterogeneous application domains (e.g. smart cities, maritime, smart building, crowd-sensing, smart grid, etc.) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day. The paper summarizes the resources that are made available through a cloud-based platform. The main contributions from this paper are twofold. In the one hand, the insightful summary of the federated data resources are relevant to the experimenters that might be seeking for an experimental infrastructure to assess their innovations. On the other hand, the identification of the challenges met during the testbed integration process, as well as the mitigation strategies that have been implemented to face them, are of interest for testbed providers that can be considering to join the federation.
Infrastructures enabling experimental assessment of Internet of Things (IoT) solutions are scarce. Moreover, such infrastructures are typically bound to a specific application domain, thus, not facilitating the testing of solutions with a horizontal approach. This paper presents a platform that supports Experimentation as s Service (EaaS) over a federation of IoT testbeds. This platform brings two major advances. Firstly, it leverages semantic web technologies to enable interoperability so that testbed agnostic access to the underlying facilities is allowed. Secondly, a set of tools ease both the experimentation workflow and the federation of other IoT deployments, independently of their domain of interest. Apart from the platform specification, the paper presents how this design has been actually instantiated into a cloud-based EaaS platform that has been used for supporting a wide variety of novel experiments targeting different research and innovation challenges. In this respect, the paper summarizes some of the experiences from these experiments and the key performance metrics that this instance of the platform has exhibited during the experimentation.
The Internet as we know it today is a critical infrastructure composed by communication services and end-user applications transforming all aspects of our lives. Recent advances in technology and the inexorable shift towards everything connected are creating a data-driven society where productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex networked systems. The challenge for the Next Generation Internet (NGI) is to design and build enabling technologies, implement and deploy systems, to create opportunities considering increasing uncertainties and emergent systemic behaviours where humans and machines seamlessly cooperate.
FIESTA-IoT project provides a blueprint experimental infrastructure, software tools, semantic techniques, certification processes and best practices enabling IoT testbed/platforms to interconnect their facility's resources in an interoperable semantic way. FIESTA-IoT project enables the integration of IoT platform's resources, testbeds infrastructure and their associated applications. FIESTA-IoT opens up new opportunities in the development and deployment of experiments using data from IoT testbeds. The FIESTA-IoT infrastructure enables experimenters to use a single EaaS API (i.e. the FIESTA-IoT EaaS API) for executing experiments over multiple IoT federated testbeds in a testbed agnostic way i.e. like accessing a single large scale virtualized testbed. The main goal of the FIESTA-IoT project is to open new horizons in the development and deployment of IoT applications and experiments at a EU (and global) scale, based on the interconnection and interoperability of diverse IoT platforms and testbeds. FIESTA-IoT project's experimental infrastructure provides to the European experimenters in the IoT domain with the unique capability for accessing and sharing IoT semantically annotated datasets in a testbed-agnostic way. FIESTA-IoT enables execution of experiments across multiple IoT testbeds, based on a single API for submitting the experiment and a single set of credentials for the researcher and the portability of IoT experiments across different testbeds and the provision of interoperable standards-based IoT/cloud interfaces over diverse IoT experimental facilities.
An important field in exploratory sensory data analysis is the segmentation of time-series data to identify activities of interest. In this work, we analyse the performance of univariate and multi-sensor Bayesian change detection algorithms in segmenting accelerometer data. In particular, we provide theoretical analysis and also performance evaluation on synthetic data and real-world data. The results illustrate the advantages of using multi-sensory variance change detection in the segmentation of dynamic data (e.g. accelerometer data).
IoT deployments and then related experiments tend to be highly heterogeneous leading to fragmented and non-interoperable silo solutions. Yet there is a growing need to interconnect such experiments to create rich infrastructures that will underpin the next generation of cross sector IoT applications in particular as using massive number of data. While research have been carried out for IoT test beds and interoperability for some infrastructures less has been done on the data. In this paper, we present the first step of the FIESTA certification method for federated semantic IoT test bed, which provides stakeholders with the means of assessing the interoperability of a given IoT testbed and how it can be federated with other ones to create large facility for experimenter. Focus is given on data and semantic context of the test beds and how they can interoperate together for larger experiments with data.
Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.
The Internet-of-Things (IoT)  has been identified as one of the main pillars of the world’s economies and the technology enabler for the evolution of the societies and for the future developments and improvement of the Internet . A large number of research activities in Europe have been working in this direction i.e. FP7 projects in the context of Future Internet Research and Experimentation (FIRE) initiative. FIRE projects have already demonstrated the potential of IoT technologies and deployments in a number of different application areas including transport, energy, safety and healthcare. FIRE deployments and project results have also demonstrated the advantages of implementing Smart Cities testbeds (national and EU scale) both have been extensively reported in . Smart City testbeds are the key places for large demonstration of IoT concepts and technology. Smart cities testbeds are prone to be large scale, highly heterogeneous and target a diverse set of application domains.
The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming vertical silos. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potential of smart applications in terms of size, scope and targeted business context. This paper describes the system architecture for the FIESTA-IoT platform, whose main aim is to federate a large number of testbeds across the planet, in order to offer experimenters the unique experience of dealing with a large number of semantically interoperable data sources. This system architecture was developed by following the Architectural Reference Model (ARM) methodology promoted by the IoT-A project (FP7 “light house” project on Architecture for the Internet of Things). Through this process, the FIESTAIoT architecture is composed of a set of Views that deals with a “logical” functional decomposition (Functional View, FV) and data structuring and annotation, data flows and inter-functional component interactions (Information View, IV).<br/
This deliverable analyzes the main testbeds and platforms participating in the FIESTA-IoT project. The testbeds and platforms that will be interconnected are: SmartSantander, University of Surrey, Com4Innov and KETI. This interconnection will enable the deployment of IoT experiments and allow services within federated utility-based cloud computing environments. In particular, this deliverable consists of an analysis and description of the resources that each of the aforementioned testbeds includes i.e. the IoT devices and sensors, gateways, APIs. It is of importance to have an exact knowledge of all the resources that could be part of the interconnection of the different testbeds around Europe and the entire world. Except the material resources written above, there are recorded as well communication protocols, applications as well as security and authentication mechanisms that are used. Moreover, at the later chapters in this deliverable, there is an introduction on the IoT ARM. This model will be used in order to translate the available resources of each testbed into a common language. There will be a mapping of the gateways, the IoT devices, the APIs etc in a common model, so that the interconnection of the testbeds and platforms becomes easier. Finally, there is the translation of the resources into the IoT ARM naming, e.g. the last chapter provides detailed analysis and description of the services of each Testbed and Platform based on both the Functional Model and Functional View approach from IoT ARM. In the end of the document a State-of-the-Art on Experimentation Tools is present, in order to present a set of already existing experimentation tools - collected from the in-house testbeds and from external projects, which can provide an idea of the kind of functionalities that are normally present in this kind of tools.
This deliverable describes the System Architecture for the FIESTA-IoT platform aiming at federating a large number of test-bed across the planet in order to offer experimenters with a unique experience of dealing and experimenting with a large number of semantically interoperable data sources. The architecting process leading to this document followed the Architectural reference Model methodology promoted by the IoT-A project (FP7 “light house” project on Architecture for the Internet of Things). It therefore consists of a set of Views that are in tern dealing with “logical” functional decomposition (Functional View - FV), data structuring and annotation, data flows and inter-functional Component interactions (Information View - IV) and ultimately the deployment of those logical components onto concrete software components (Deployment View). Design Choices pertaining to Non-Functional requirements will be covered in the up-coming WP deliverables providing detailed interfaces description that will guide he implemented work on each WP. The architecture describe din this document is inclusive in the sense it can accommodate under its federation a large number of test-beds with various capabilities (some being semantic-enabled already, some not). It offers full semantic interoperability: all assets of the test-bed (resources, IoT Services, Virtual Entities) are semantically annotated and described; they are searchable using either powerful data query languages or simpler APIs. FIESTA-IoT is therefore able to offer the greatest test-bed agnostic experience to both expert users (semantically skilled) and more basic experimenters as well.
Over the past few years, the semantics community has developed several ontologies to describe concepts and relationships for internet of things (IoT) applications. A key problem is that most of the IoT-related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time, and therefore, they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis and assess IoT-Lite against another solution in terms of round trip time performance for query-response times. We have linked IoT-Lite with stream annotation ontology, to allow queries over stream data annotations, and we have also added dynamic semantics in the form of MathML annotations to IoT-Lite. Dynamic semantics allows the annotation of spatio-temporal values, reducing storage requirements and therefore the response time for queries. Dynamic semantics stores mathematical formulas to recover estimated values when actual values are missing.
This document describes the dissemination and communication activities for the FIESTA-IoT project for the period M1 (February 2015) to M12 (January 2015). The dissemination plan is also presented, first describing how promotional material, FIESTA-IoT results, and FIESTA-IoT activities will be used to promote and engage with target communities in order to increase awareness of FIESTA-IoT results, and the FIESTA experimental facility. This document cover the started in M1 dissemination activities but will intensify from M12 onwards in preparation for open calls and engagement with IoT Communities of experimenters and testbeds. The dissemination activities carried out in the first year are described and material generated during the first year is included; these already cover a broad range of activities and communities: • Scientific publications. • Participation (and presentation) at relevant (IoT) events, conferences, summer schools, workshops, meetings. • Demos and exhibitions. • Standards community events. An initial plan for the second year of the project (February 2016 to January 2017) is presented to conclude the report. This outlines potential joint publications for research results, and target events where the FIESTA-IoT facility can be demonstrated, and the upcoming Open Calls can be advertised. Finally, a mapping of the dissemination activities against the objective goals of the project is presented that also serves as self-evaluation for the progress in achievements of the FIESTA-IoT project.
IoT-Lite ontology is a lightweight ontology to represent Internet of Things (IoT) resources, entities and services. IoT-Lite is an instantiation of the SSN ontology. The lightweight allow the representation and use of IoT platforms without consuming excessive processing time when querying the ontology. However it is also a meta ontology that can be extended in order to represent IoT concepts in a more detailed way in different domains. It also can be combined with ontologies representing IoT data streams such as SAO ontology. Following best practices in ontology engineering iot-lite is meant to be used with a quantity taxonomy, such as qu-taxo, that allows the discovery and interoperability of IoT resources in heterogeneous platforms using a common vocabulary. http://www.w3.org/Submission/iot-lite/
Over the past few years the semantics community has developed ontologies to describe concepts and relationships between different entities in various application domains, including Internet of Things (IoT) applications. A key problem is that most of the IoT related semantic descriptions are not as widely adopted as expected. One of the main concerns of users and developers is that semantic techniques increase the complexity and processing time and therefore they are unsuitable for dynamic and responsive environments such as the IoT. To address this concern, we propose IoT-Lite, an instantiation of the semantic sensor network (SSN) ontology to describe key IoT concepts allowing interoperability and discovery of sensory data in heterogeneous IoT platforms by a lightweight semantics. We propose 10 rules for good and scalable semantic model design and follow them to create IoT-Lite. We also demonstrate the scalability of IoT-Lite by providing some experimental analysis, and assess IoT-Lite against another solution in terms of round time trip (RTT) performance for query-response times.
The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming application silos. A lightweight data centric integration and combination of these silos presents several challenges that still need to be addressed. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potentiality of smart applications in terms of size, scope and targeted business context. In this article, a proof-of-concept implementation that federates two different IoT experimentation facilities by means of semantic-based technologies will be described. The specification and design of the implemented system and information models will be described together with the practical details of the developments carried out and its integration with the existing IoT platforms supporting the aforementioned testbeds. Overall, the system described in this paper demonstrates that it is possible to open new horizons in the development of IoT applications and experiments at a global scale, that transcend the (silo) boundaries of individual deployments, based on the semantic interconnection and interoperability of diverse IoT platforms and testbeds.