SSW 2010 Abstracts

Full Papers
Full Papers
Paper Nr: 2
Title:

Development of Architecture and Caching System for Improving the Performance of Fuel Management System
Authors:

Mahmoud Ahmed and Mustafa Ali Taha
Abstract: Fuel Management System (FMS) is about managing and accounting for fuel. While implementing FMS in Sudan, some problems are noted, like system delay, inaccuracy and unavailability of the system. These problems and others make fueling companies and customers unsatisfied with the FMS. This paper aims to solve the noted problems by introducing enhanced system architecture and integrating a Caching System in the FMS architecture to enhance the performance, reduce system delay and increase the availability of the system. After architecture was developed, simulation programs were implemented to simulate the interactions required to re-fuel and to provide statistics results that help in evaluating the proposed FMS. The results of simulation programs were presented as the average service time, number of customers in system, number of customers in queue, idle probability and other results. The average service time was reduced and all results obtained emphasize the effectiveness of the proposed solution.
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Paper Nr: 3
Title:

Building Semantic Sensor Web: Knowledge and Interoperability

Authors:

Salvatore F. Pileggi, Carlos E. Palau and Manuel Esteve
Abstract: Semantic Sensor Web would be an evolving extension of Sensor Web that introduces a semantic layer in which semantics or meanings of information are formally defined according to well-defined semantic schemas (Ontology). Semantics should improve the capabilities of collecting, retrieving, sharing, manipulating and analyzing sensor data (or associate phenomena) providing a new interoperability model: semantic interoperability introduces the interpretation of means of data allowing the engineering of novel architectures based on standard reasoners.
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Paper Nr: 4
Title:

Modeling Sensor Knowledge of a National Hydrologic Information System
Authors:

Martin Molina and Javier Sanchez-Soriano
Abstract: In this paper we describe our experience in modeling and using sensor knowledge of a national hydrologic information system in Spain. We developed a web application called VSAIH supported by a knowledge-based system to analyze sensor data and to generate explanations that help users to make decisions based on hydrologic behavior. In the paper, we describe the characteristics of the infrastructure of hydrologic sensors and the representation we used to model sensor knowledge to provide support to the VSAIH application. We also describe semi-automatic procedures that we applied to construct the final model.
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Paper Nr: 5
Title:

Semantic Process Choreography for Distributed Sensor Management
Authors:

Carlos Fernandez-Llatas, Juan B. Mocholi, Agustin Moyano and Teresa Meneu
Abstract: The Factory of Future (FoF) concept demands a new framework were the health surveillance of workers needs to become more and more important. The continuous monitoring of workers in highly dynamic environments like factories require new advances on self-configurable and fault-tolerant systems in order to allow the distribution and scalability of sensors and services. In this framework, the use of Process Choreography and Semantic reasoning techniques could have a great impact in the creation of these highly configurable systems to be used in those areas. This paper proposes a semantically tagged architecture based on process choreography for distributed management of sensors.
Paper Nr: 6
Title:

Archiving pushed Inferences from Sensor Data Streams
Authors:

Jörg Brunsmann
Abstract: Although pervasively deployed, sensors are currently neither highly interconnected nor very intelligent, since they do not know each other and pro-duce only raw data streams. This lack of interoperability and high-level reasoning capabilities are major obstacles for exploiting the full potential of sensor data streams. Since interoperability and reasoning processes require a common understanding, RDF based linked sensor data is used in the semantic sensor web to articulate the meaning of sensor data. This paper shows how to derive higher levels of streamed sensor data understanding by constructing reasoning know-ledge with SPARQL. In addition, it is demonstrated how to push these inferences to interested clients in different application domains like social media streaming, weather observation and intelligent product lifecycle maintenance. Finally, the paper describes how real-time pushing of inferences enables provenance tracking and how archiving of inferred events could support further decision making processes.
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Paper Nr: 7
Title:

Using SCXML to Integrate Semantic Sensor Information into Context-aware User Interfaces
Authors:

Alvaro Sigüenza, José Luis Blanco, Jesús Bernat and Luis A. Hernández
Abstract: This paper describes a novel architecture to introduce automatic annotation and processing of semantic sensor data within context-aware applications. Based on the well-known state-charts technologies, and represented using W3C SCXML language combined with Semantic Web technologies, our architecture is able to provide enriched higher-level semantic representations of user’s context. This capability to detect and model relevant user situations allows a seamless modeling of the actual interaction situation, which can be integrated during the design of multimodal user interfaces (also based on SCXML) for them to be adequately adapted. Therefore, the final result of this contribution can be described as a flexible context-aware SCXML-based architecture, suitable for both designing a wide range of multimodal context-aware user interfaces, and implementing the automatic enrichment of sensor data, making it available to the entire Semantic Sensor Web.
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Paper Nr: 8
Title:

Wireless Sensor Network for Remote Detection of Explosives
Authors:

Simi S. and Maneesha V. Ramesh
Abstract: In recent years, due to the increase in bomb blasts worldwide, it is required to continuously monitor the presence of explosives in public places. The objective of this research work is to reduce, control, and warn about the forthcoming terrorist activity by precise and quick detection of explosives. This paper proposes a wide area monitoring system using a multi phase wireless sensor network design with minimum false alarms. W-ReMADE uses multiple wireless sensor nodes integrated with different types of sensors to identify the chemical composition and magnetic signature of explosives. Based on diverse orthogonal techniques, the system collects data from the sensing nodes, dynamically aggregates the data and forward to the sink node for further analysis. A mobile node is used for the confirmation of suspected objects and offers an enhanced target tracking mechanism. W-ReMADE provides an effective warning mechanism for security threats in public places such as airports so that the authorized persons can take immediate actions.
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Paper Nr: 9
Title:

Semantic High Level Querying in Sensor Networks
Authors:

Ilaria Giordani, Daniele Toscani, Francesco Archetti and Mauro Cislaghi
Abstract: The quick development and deployment of sensor technology within the general frame of the Internet of Things poses relevant opportunity and challenges. The sensor is not a pure data source, but an entity (Semantic Sensor Web) with associated metadata and it is a building block of a “worldwide distributed” real time database, to be processed through real-time queries. Important challenges are to achieve interoperability in connectivity and processing capabilities (queries) and to apply “intelligence” and processing capabilities as close as possible to the source of data. This paper presents the extension of a general architecture for data integration in which we add capabilities for processing of complex queries and discuss how they can be adapted to, and used by, an application in the Semantic Sensor Web, presenting a pilot study in environment and health domains.
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Paper Nr: 11
Title:

A Cognitive Approach to Modelling Semantic Sensor Web Solutions
Authors:

Agnes Korotij and Judit Kiss-Gulyas
Abstract: Semantic sensor solutions are characterized by a lack of consensus on what features make sensor networks semantic, and what services a semantic layer should provide. Although authors emphasize the fact that humans outperform software in managing inconsistent knowledge and unreliable sensor data, no attempt has been made so far to construct a model of semantic sensor networks inspired by human cognition. The aim of the present paper is to investigate whether the structure and organisation of concepts and meaning in the human mind (as proposed by cognitive linguists and psycholinguists) can serve as a model for constructing ontologies and knowledge representations for the semantic sensor web (hereafter SSW). We also aim to show how multimodal sensory data can be integrated with these representations based on contemporary findings in human perception. We suggest that SSW solutions based on cognitive mechanisms and psychologically plausible knowledge representations overcome the challenges that handling of fuzzy data and inconsistent information generates at present.
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Paper Nr: 13
Title:

Semantic Sensor Networks for Personalized Health Systems for Risk Prevention
Authors:

Teresa Meneu, Antonio Martínez, Carlos Fernández, Ainara Gonzalez and Vicente Traver
Abstract: Monitoring of health related parameters, behaviours, signs and symptoms in patients with diagnosed conditions is still a challenging issue. This is evident, if not because the need of more advanced sensing technologies, also due to the intrusiveness and the excessive technological component of the more trivial solutions proposed. Personal Health Systems (PHS) normally share a common architecture based in a closed-loop approach, combining monitoring and feedback to different levels of care. This model can be easily exported as the base for more open scenarios. More extensively developed semantic sensor networks need to be developed to face the challenges and requirements of more open scenarios for health related monitoring in personalized systems.
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Paper Nr: 17
Title:

Semantic Sensor Network Architecture for Pro-active Risk Management in the Factories of the Future
Authors:

Agustin Moyano, Oscar Lazaro and Carlos Fernandez-Llatas
Abstract: In recent years we have observe the increasing interest and a prevailing role of ICT in the context of factory environment. In parallel with increased sensing and actuating capabilities, the improvement in backhaul communications present a new factory scenario where more autonomous intelligent reasoning mechanisms could be envisaged. The Internet of Things (IoT) scenario that needs to be handle is characterized by highly variable spatial and temporal contexts that should be effectively managed. This paper presents and discusses the semantic management approach to complex system operation proposed by the FASyS project (Absolutely safe and Healthy Factory). Moreover, a distributed reasoning concept regarded as reasoning contexts proposed by the project is also proposed and the benefits discussed.
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Paper Nr: 18
Title:

Automatic Feature Selection for Operational Scenarios of Satellite Image Understanding using Measures of Mutual Information
Authors:

Dragos Bratasanu, Ion Nedelcu and Mihai Datcu
Abstract: The Earth Observation processing tools operating in the recent scenario need to be tailored to the new products offered by the sub-meter spatial resolution imaging sensors. The new methods should provide the image analysts the essential automatic support to discover relevant information and identify significant elements in the image. We advocate an automatic technique to select the optimum number features used in classification, object detection and analysis of optical satellite images. Using measures of mutual information between the target classes and the available features, we investigate the criterions of maximum-relevance and maximum-relevance-minimumredundancy for automatic feature selection at very-low cost. Following a comprehensive set of experiments on multiple sensors, applications and classifiers, the results demonstrate the possible operational use of the method in future scenarios of human-machine interactions in support of Earth Observation technologies.
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