Semantic Integration of Coastal Buoys Data using SPARQL

Currently, the data provided by the heterogeneous buoy sensors/networks (e.g. National Data Buoy center (NDBC), Gulf Of Maine Ocean Observing System (GoMoos) etc. is not amenable to the development of integrated systems due to conflicts in the data representation at syntactic and structural levels. With the rapid increase in the amount of information, the integration of heterogeneous resources is an important issue and requires integrative technologies such as semantic web. In distributed data dissemination system, normally querying on single database will not provide relevant information and requires querying across interrelated data sources to retrieve holistic information. In this thesis we develop system for integrating two different Resource Description Framework (RDF) data sources through intelligent querying using Simple Protocol and RDF Query Language (SPARQL). We use Semantic Web application framework from AllegroGraph that provides functionality for developing triple store for the ontological representations, forming federated stores and querying it through SPARQL

Architecting Social Internet of Things

In the new era of the Internet of Things (IoT), most of the devices we interact with daily are connected to the Internet. From tiny sensors, lamps, home appliances, home security systems and health-care devices, to complex heating, ventilation and air conditioning (HVAC) systems at home, myriad devices have network connectivity and provide smart applications. The Social Internet of Things (SIoT) is a new paradigm where IoT merges with social networks, allowing people and connected devices as well as the devices themselves to interact within a social network framework to support a new social navigation. Smart homes is one of the domains that can fully leverage this new paradigm, which will enable people and devices, even in different homes, to actively and mostly automatically collaborate to discover and share new information and services. Unfortunately the heterogeneous nature of the devices around the home prohibits seamless communication in the (S)IoT. Furthermore, the state-of-the-art solutions in smart homes offer little, if any, support for collaborating users and devices. This dissertation describes a new, scalable approach to connect, interact and share useful information through devices and users with common interests. The dissertation has three contributions. First, it proposes a holistic and extensible smart home gateway architecture that seamlessly integrates heterogeneous protocol-- and vendor-- specific devices and services and provides fine-grained access controls. Second, it defines an interoperable, scalable and extensible software architecture for a novel cloud-based collaboration framework for a large number of devices and users in many different smart homes. Third, it provides a reasoning framework to enable automated decisions based on the discovered information and knowledge created and shared by end users. The developed architecture and solutions are implemented in real systems, which integrate with many different devices from different manufacturers and run multiple categories of rules created by end users. The architectural evaluation results show the developed systems are interoperable, scalable and extensible

A study of existing Ontologies in the IoT-domain

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.Comment: Submitted to Elsevier JWS SI on Web semantics for the Internet/Web of Thing

Semantic Driven Approach for Rapid Application Development in Industrial Internet of Things

The evolution of IoT has revolutionized industrial automation. Industrial devices at every level such as field devices, control devices, enterprise level devices etc., are connected to the Internet, where they can be accessed easily. It has significantly changed the way applications are developed on the industrial automation systems. It led to the paradigm shift where novel IoT application development tools such as Node-RED can be used to develop complex industrial applications as IoT orchestrations. However, in the current state, these applications are bound strictly to devices from specific vendors and ecosystems. They cannot be re-used with devices from other vendors and platforms, since the applications are not semantically interoperable. For this purpose, it is desirable to use platform-independent, vendor-neutral application templates for common automation tasks. However, in the current state in Node-RED such reusable and interoperable application templates cannot be developed. The interoperability problem at the data level can be addressed in IoT, using Semantic Web (SW) technologies. However, for an industrial engineer or an IoT application developer, SW technologies are not very easy to use. In order to enable efficient use of SW technologies to create interoperable IoT applications, novel IoT tools are required. For this purpose, in this paper we propose a novel semantic extension to the widely used Node-RED tool by introducing semantic definitions such as iot.schema.org semantic models into Node-RED. The tool guides a non-expert in semantic technologies such as a device vendor, a machine builder to configure the semantics of a device consistently. Moreover, it also enables an engineer, IoT application developer to design and develop semantically interoperable IoT applications with minimal effort. Our approach accelerates the application development process by introducing novel semantic application templates called Recipes in Node-RED. Using Recipes, complex application development tasks such as skill matching between Recipes and existing things can be automated.We will present the approach to perform automated skill matching on the Cloud or on the Edge of an automation system. We performed quantitative and qualitative evaluation of our approach to test the feasibility and scalability of the approach in real world scenarios. The results of the evaluation are presented and discussed in the paper.Die Entwicklung des Internet der Dinge (IoT) hat die industrielle Automatisierung revolutioniert. Industrielle Geräte auf allen Ebenen wie Feldgeräte, Steuergeräte, Geräte auf Unternehmensebene usw. sind mit dem Internet verbunden, wodurch problemlos auf sie zugegriffen werden kann. Es hat die Art und Weise, wie Anwendungen auf industriellen Automatisierungssystemen entwickelt werden, deutlich verändert. Es führte zum Paradigmenwechsel, wo neuartige IoT Anwendungsentwicklungstools, wie Node-RED, verwendet werden können, um komplexe industrielle Anwendungen als IoT-Orchestrierungen zu entwickeln. Aktuell sind diese Anwendungen jedoch ausschließlich an Geräte bestimmter Anbieter und Ökosysteme gebunden. Sie können nicht mit Geräten anderer Anbieter und Plattformen verbunden werden, da die Anwendungen nicht semantisch interoperabel sind. Daher ist es wünschenswert, plattformunabhängige, herstellerneutrale Anwendungsvorlagen für allgemeine Automatisierungsaufgaben zu verwenden. Im aktuellen Status von Node-RED können solche wiederverwendbaren und interoperablen Anwendungsvorlagen jedoch nicht entwickelt werden. Diese Interoperabilitätsprobleme auf Datenebene können im IoT mithilfe von Semantic Web (SW) -Technologien behoben werden. Für Ingenieure oder Entwickler von IoT-Anwendungen sind SW-Technologien nicht sehr einfach zu verwenden. Zur Erstellung interoperabler IoT-Anwendungen sind daher neuartige IoT-Tools erforderlich. Zu diesem Zweck schlagen wir eine neuartige semantische Erweiterung des weit verbreiteten Node-RED-Tools vor, indem wir semantische Definitionen wie iot.schema.org in die semantischen Modelle von NODE-Red einführen. Das Tool leitet einen Gerätehersteller oder Maschinebauer, die keine Experten in semantische Technologien sind, an um die Semantik eines Geräts konsistent zu konfigurieren. Darüber hinaus ermöglicht es auch einem Ingenieur oder IoT-Anwendungsentwickler, semantische, interoperable IoT-Anwendungen mit minimalem Aufwand zu entwerfen und entwicklen Unser Ansatz beschleunigt die Anwendungsentwicklungsprozesse durch Einführung neuartiger semantischer Anwendungsvorlagen namens Rezepte für Node-RED. Durch die Verwendung von Rezepten können komplexe Anwendungsentwicklungsaufgaben wie das Abgleichen von Funktionen zwischen Rezepten und vorhandenen Strukturen automatisiert werden. Wir demonstrieren Skill-Matching in der Cloud oder am Industrial Edge eines Automatisierungssystems. Wir haben dafür quantitative und qualitative Bewertung unseres Ansatzes durchgeführt, um die Machbarkeit und Skalierbarkeit des Ansatzes in realen Szenarien zu testen. Die Ergebnisse der Bewertung werden in dieser Arbeit vorgestellt und diskutiert

Ontology-Based Data Integration in Multi-Disciplinary Engineering Environments: A Review

Today's industrial production plants are complex mechatronic systems. In the course of the production plant lifecycle, engineers from a variety of disciplines (e.g., mechanics, electronics, automation) need to collaborate in multi-disciplinary settings that are characterized by heterogeneity in terminology, methods, and tools. This collaboration yields a variety of engineering artifacts that need to be linked and integrated, which on the technical level is reflected in the need to integrate heterogeneous data. Semantic Web technologies, in particular ontologybased data integration (OBDI), are promising to tackle this challenge that has attracted strong interest from the engineering research community. This interest has resulted in a growing body of literature that is dispersed across the Semantic Web and Automation System Engineering research communities and has not been systematically reviewed so far. We address this gap with a survey reflecting on OBDI applications in the context of Multi-Disciplinary Engineering Environment (MDEE). To this end, we analyze and compare 23 OBDI applications from both the Semantic Web and the Automation System Engineering research communities. Based on this analysis, we (i) categorize OBDI variants used in MDEE, (ii) identify key problem context characteristics, (iii) compare strengths and limitations of OBDI variants as a function of problem context, and (iv) provide recommendation guidelines for the selection of OBDI variants and technologies for OBDI in MDEE

Mobile Edge Computing Empowers Internet of Things

In this paper, we propose a Mobile Edge Internet of Things (MEIoT) architecture by leveraging the fiber-wireless access technology, the cloudlet concept, and the software defined networking framework. The MEIoT architecture brings computing and storage resources close to Internet of Things (IoT) devices in order to speed up IoT data sharing and analytics. Specifically, the IoT devices (belonging to the same user) are associated to a specific proxy Virtual Machine (VM) in the nearby cloudlet. The proxy VM stores and analyzes the IoT data (generated by its IoT devices) in real-time. Moreover, we introduce the semantic and social IoT technology in the context of MEIoT to solve the interoperability and inefficient access control problem in the IoT system. In addition, we propose two dynamic proxy VM migration methods to minimize the end-to-end delay between proxy VMs and their IoT devices and to minimize the total on-grid energy consumption of the cloudlets, respectively. Performance of the proposed methods are validated via extensive simulations

SERVICE-BASED AUTOMATION OF SOFTWARE CONSTRUCTION ACTIVITIES

The reuse of software units, such as classes, components and services require professional knowledge to be performed. Today a multiplicity of different software unit technologies, supporting tools, and related activities used in reuse processes exist. Each of these relevant reuse elements may also include a high number of variations and may differ in the level and quality of necessary reuse knowledge. In such an environment of increasing variations and, therefore, an increasing need for knowledge, software engineers must obtain such knowledge to be able to perform software unit reuse activities. Today many different reuse activities exist for a software unit. Some typical knowledge intensive activities are: transformation, integration, and deployment. In addition to the problem of the amount of knowledge required for such activities, other difficulties also exist. The global industrial environment makes it challenging to identify sources of, and access to, knowledge. Typically, such sources (e.g., repositories) are made to search and retrieve information about software unitsand not about the required reuse activity knowledge for a special unit. Additionally, the knowledge has to be learned by inexperienced software engineers and, therefore, to be interpreted. This interpretation may lead to variations in the reuse result and can differ from the estimated result of the knowledge creator. This makes it difficult to exchange knowledge between software engineers or global teams. Additionally, the reuse results of reuse activities have to be repeatable and sustainable. In such a scenario, the knowledge about software reuse activities has to be exchanged without the above mentioned problems by an inexperienced software engineer. The literature shows a lack of techniques to store and subsequently distribute relevant reuse activity knowledge among software engineers. The central aim of this thesis is to enable inexperienced software engineers to use knowledge required to perform reuse activities without experiencing the aforementioned problems. The reuse activities: transformation, integration, and deployment, have been selected as the foundation for the research. Based on the construction level of handling a software unit, these activities are called Software Construction Activities (SCAcs) throughout the research. To achieve the aim, specialised software construction activity models have been created and combined with an abstract software unit model. As a result, different SCAc knowledge is described and combined with different software unit artefacts needed by the SCAcs. Additionally, the management (e.g., the execution of an SCAc) will be provided in a service-oriented environment. Because of the focus on reuse activities, an approach which avoids changing the knowledge level of software engineers and the abstraction view on software units and activities, the object of the investigation differs from other approaches which aim to solve the insufficient reuse activity knowledge problem. The research devised novel abstraction models to describe SCAcs as knowledge models related to the relevant information of software units. The models and the focused environment have been created using standard technologies. As a result, these were realised easily in a real world environment. Softwareengineers were able to perform single SCAcs without having previously acquired the necessary knowledge. The risk of failing reuse decreases because single activities can be performed. The analysis of the research results is based on a case study. An example of a reuse environmenthas been created and tested in a case study to prove the operational capability of the approach. The main result of the research is a proven concept enabling inexperienced software engineers to reuse software units by reusing SCAcs. The research shows the reduction in time for reuse and a decrease of learning effort is significant

Dynamic service orchestration in heterogeneous internet of things environments

Internet of Things (IoT) presents a dynamic global revolution in the Internet where physical and virtual “things” will communicate and share information. As the number of devices increases, there is a need for a plug-and–interoperate approach of deploying “things” to the existing network with less or no human need for configuration. The plug-and-interoperate approach allows heterogeneous “things” to seamlessly interoperate, interact and exchange information and subsequently share services. Services are represented as functionalities that are offered by the “things”. Service orchestration provides an approach to integration and interoperability that decouples applications from each other, enhancing capabilities to centrally manage and monitor components. This work investigated requirements for semantic interoperability and exposed current challenges in IoT interoperability as a means of facilitating services orchestration in IoT. The research proposes a platform that allows heterogeneous devices to collaborate thereby enabling dynamic service orchestration. The platform provides a common framework for representing semantics allowing for a consistent information exchange format. The information is stored and presented in an ontology thereby preserving semantics and making the information comprehensible to machines allowing for automated addressing, tracking and discovery as well as information representation, storage, and exchange. Process mining techniques were used to discover service orchestrations. Process mining techniques enabled the analysis of runtime behavior of service orchestrations and the semantic breakdown of the service request and creation in real time. This enabled the research to draw observations that led to conclusions presented in this work. The research noted that the use of semantic technologies facilitates interoperability in heterogeneous devices and can be implemented as a means to bypass challenges presented by differences in IoT “things”