Prikaz znanja u internetu stvari: semantičko modeliranje i njegove primjene

Semantic modelling provides a potential basis for interoperating among different systems and applications in the Internet of Things (IoT). However, current work has mostly focused on IoT resource management while not on the access and utilisation of information generated by the “Things”. We present the design of a comprehensive and lightweight semantic description model for knowledge representation in the IoT domain. The design follows the widely recognised best practices in knowledge engineering and ontology modelling. Users are allowed to extend the model by linking to external ontologies, knowledge bases or existing linked data. Scalable access to IoT services and resources is achieved through a distributed, semantic storage design. The usefulness of the model is also illustrated through an IoT service discovery method.Semantičko modeliranje pruža potencijalnu osnovu za me.udjelovanje različitih sustava i aplikacija unutar interneta stvari (IoT). Međutim, postojeći radovi uglavnom su fokusirani na upravljanje IoT resursima, ali ne i pristupu i korištenju informacija koje generira “stvar”. Predstavljamo projektiranje sveobuhvatnog i laganog semantičkog opisnog modela za prikaz znanja u IoT domeni. Projektiranje slijedi široko-priznate najbolje običaje u inženjerstvu znanja i ontološkom modeliranju. Korisnicima se dopušta proširenje modela povezivanjem na eksterne ontologije, baze znanja ili postoje će povezane podatke. Skalabilni pristup IoT uslugama i resursima postiže se kroz distribuirano, semantičko projektiranje pohrane. Upotrebljivost modela tako.er je ilustrirana kroz metodu pronalaska IoT usluga

A Geospatial Service Model and Catalog for Discovery and Orchestration

The goal of this research is to provide a supporting Web services architecture, consisting of a service model and catalog, to allow discovery and automatic orchestration of geospatial Web services. First, a methodology for supporting geospatial Web services with existing orchestration tools is presented. Geospatial services are automatically translated into SOAP/WSDL services by a portable service wrapper. Their data layers are exposed as atomic functions while WSDL extensions provide syntactic metadata. Compliant services are modeled using the descriptive logic capabilities of the Ontology Language for the Web (OWL). The resulting geospatial service model has a number of functions. It provides a basic taxonomy of geospatial Web services that is useful for templating service compositions. It also contains the necessary annotations to allow discovery of services. Importantly, the model defines a number of logical relationships between its internal concepts which allow inconsistency detection for the model as a whole and for individual service instances as they are added to the catalog. These logical relationships have the additional benefit of supporting automatic classification of geospatial services individuals when they are added to the service catalog. The geospatial service catalog is backed by the descriptive logic model. It supports queries which are more complex that those available using standard relational data models, such as the capability to query using concept hierarchies. An example orchestration system demonstrates the use of the geospatial service catalog for query evaluation in an automatic orchestration system (both fully and semi-automatic orchestration). Computational complexity analysis and experimental performance analysis identify potential performance problems in the geospatial service catalog. Solutions to these performance issues are presented in the form of partitioning service instance realization, low cost pre-filtering of service instances, and pre-processing realization. The resulting model and catalog provide an architecture to support automatic orchestration capable of complementing the multiple service composition algorithms that currently exist. Importantly, the geospatial service model and catalog go beyond simply supporting orchestration systems. By providing a general solution to the modeling and discovery of geospatial Web services they are useful in any geospastial Web service enterprise

The SSN ontology of the W3C semantic sensor network incubator group

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations ? the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects

Service-oriented design of environmental information systems

Service-orientation has an increasing impact upon the design process and the architecture of environmental information systems. This thesis specifies the SERVUS design methodology for geospatial applications based upon standards of the Open Geospatial Consortium. SERVUS guides the system architect to rephrase use case requirements as a network of semantically-annotated requested resources and to iteratively match them with offered resources that mirror the capabilities of existing services

An extensible semantic catalogue for geospatial web services

Searching for web services is a challenging task due to the diversity of existing discovery tools. Varying standards for service descriptions require different tools to query their content. These standards exist for good reasons. Web services are used in different application environments and special solutions are required for their integration. We suggest an architecture for web service catalogues, which takes this diversity of standards into account. Its extensibility allows for a complete separation between service discovery and service description. Using ontologies for the storage of service descriptions enables the support of different description standards without loosing their specific advantages. The discussion and implementation focuses on geospatial web services. Due to the heterogeneity of spatially referenced data, different specifications exist for them, making the problem of different standards for service discovery and service description most evident here

Semantically-Enabled Sensor Plug & Play for the Sensor Web

Environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent over the past years. As consequence of these technological advancements, sensors are increasingly deployed to monitor our environment. The large variety of available sensor types with often incompatible protocols complicates the integration of sensors into observing systems. The standardized Web service interfaces and data encodings defined within OGC’s Sensor Web Enablement (SWE) framework make sensors available over the Web and hide the heterogeneous sensor protocols from applications. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The driver software which enables access to sensors has to be implemented and the measured sensor data has to be manually mapped to the SWE models. In this article we introduce a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) semantic matchmaking functionality, (2) a publish/subscribe mechanism underlying the SensorWeb, as well as (3) a model for the declarative description of sensor interfaces which serves as a generic driver mechanism. We implement and evaluate our approach by applying it to an oil spill scenario. The matchmaking is realized using existing ontologies and reasoning engines and provides a strong case for the semantic integration capabilities provided by Semantic Web research

Geospatial data integration with Semantic Web services: the eMerges approach

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies

A Semantic IoT Early Warning System for Natural Environment Crisis Management

This work was supported in part by the European FP7 Funded Project TRIDEC under Grant 258723, the other project partners in helping to deliver the complete project Syste, in particular, GFZ, and the German Research Centre for Geosciences, Potsdam, Germany. The work of R. Tao was supported by the Queen Mary University of London for a Ph.D. studentship

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure