23,750 research outputs found
Km4City Ontology Building vs Data Harvesting and Cleaning for Smart-city Services
Presently, a very large number of public and private data sets are available
from local governments. In most cases, they are not semantically interoperable
and a huge human effort would be needed to create integrated ontologies and
knowledge base for smart city. Smart City ontology is not yet standardized, and
a lot of research work is needed to identify models that can easily support the
data reconciliation, the management of the complexity, to allow the data
reasoning. In this paper, a system for data ingestion and reconciliation of
smart cities related aspects as road graph, services available on the roads,
traffic sensors etc., is proposed. The system allows managing a big data volume
of data coming from a variety of sources considering both static and dynamic
data. These data are mapped to a smart-city ontology, called KM4City (Knowledge
Model for City), and stored into an RDF-Store where they are available for
applications via SPARQL queries to provide new services to the users via
specific applications of public administration and enterprises. The paper
presents the process adopted to produce the ontology and the big data
architecture for the knowledge base feeding on the basis of open and private
data, and the mechanisms adopted for the data verification, reconciliation and
validation. Some examples about the possible usage of the coherent big data
knowledge base produced are also offered and are accessible from the RDF-Store
and related services. The article also presented the work performed about
reconciliation algorithms and their comparative assessment and selection
An ontology-based approach to relax traffic regulation for autonomous vehicle assistance
Traffic regulation must be respected by all vehicles, either human- or
computer- driven. However, extreme traffic situations might exhibit practical
cases in which a vehicle should safely and reasonably relax traffic regulation,
e.g., in order not to be indefinitely blocked and to keep circulating. In this
paper, we propose a high-level representation of an automated vehicle, other
vehicles and their environment, which can assist drivers in taking such
"illegal" but practical relaxation decisions. This high-level representation
(an ontology) includes topological knowledge and inference rules, in order to
compute the next high-level motion an automated vehicle should take, as
assistance to a driver. Results on practical cases are presented
Ontology based Scene Creation for the Development of Automated Vehicles
The introduction of automated vehicles without permanent human supervision
demands a functional system description, including functional system boundaries
and a comprehensive safety analysis. These inputs to the technical development
can be identified and analyzed by a scenario-based approach. Furthermore, to
establish an economical test and release process, a large number of scenarios
must be identified to obtain meaningful test results. Experts are doing well to
identify scenarios that are difficult to handle or unlikely to happen. However,
experts are unlikely to identify all scenarios possible based on the knowledge
they have on hand. Expert knowledge modeled for computer aided processing may
help for the purpose of providing a wide range of scenarios. This contribution
reviews ontologies as knowledge-based systems in the field of automated
vehicles, and proposes a generation of traffic scenes in natural language as a
basis for a scenario creation.Comment: Accepted at the 2018 IEEE Intelligent Vehicles Symposium, 8 pages, 10
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Improving sustainability through intelligent cargo and adaptive decision making
In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange.In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange.In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange
Multi-Paradigm Reasoning for Access to Heterogeneous GIS
Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn
the web into a geospatial web services enabled place. Mediation
architectures like VirGIS overcome syntactical and semantical heterogeneity
between several distributed sources. On mobile devices,
however, this kind of solution is not suitable, due to limitations,
mostly regarding bandwidth, computation power, and available storage
space. The aim of this paper is to present a solution for providing
powerful reasoning mechanisms accessible from mobile applications
and involving data from several heterogeneous sources.
By adapting contents to time and location, mobile web information
systems can not only increase the value and suitability of the
service itself, but can substantially reduce the amount of data delivered
to users. Because many problems pertain to infrastructures
and transportation in general and to way finding in particular, one
cornerstone of the architecture is higher level reasoning on graph
networks with the Multi-Paradigm Location Language MPLL. A
mediation architecture is used as a âgraph providerâ in order to
transfer the load of computation to the best suited component â
graph construction and transformation for example being heavy on
resources. Reasoning in general can be conducted either near the
âsourceâ or near the end user, depending on the specific use case.
The concepts underlying the proposal described in this paper are
illustrated by a typical and concrete scenario for web applications
Moving Object Trajectories Meta-Model And Spatio-Temporal Queries
In this paper, a general moving object trajectories framework is put forward
to allow independent applications processing trajectories data benefit from a
high level of interoperability, information sharing as well as an efficient
answer for a wide range of complex trajectory queries. Our proposed meta-model
is based on ontology and event approach, incorporates existing presentations of
trajectory and integrates new patterns like space-time path to describe
activities in geographical space-time. We introduce recursive Region of
Interest concepts and deal mobile objects trajectories with diverse
spatio-temporal sampling protocols and different sensors available that
traditional data model alone are incapable for this purpose.Comment: International Journal of Database Management Systems (IJDMS) Vol.4,
No.2, April 201
Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web
Current âInternet of Thingsâ concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3Câs Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where driversâ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun
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