48 research outputs found
An Architectural Approach for Enabling and Developing Cooperative Behaviour in Diverse Autonomous Robots
The paper introduces an architecture for robot-to-robot cooperation which takes into consideration how situational context augmented with peer modeling fosters cooperation opportunity identification and cooperation planning. The presented architecture allows developing, training, testing, and deploying dynamic cooperation solutions for diverse autonomous robots using ontology-based reasoning. The architecture operates in three different worlds: in the Real World with real robots, in a 3D Virtual World by emulating the real environments and robots, and in an abstract Block World that enables developing and studying large-scale cooperation scenarios. We describe an assessment practice for our architecture and cooperation procedures, which is based on scenarios implemented in all three worlds, and provide initial results of stress testing the cooperation procedures in the Block World. Moreover, as the core part of our architecture can operate in all the three worlds, development of the robot cooperation with the architecture can regularly accommodate insights gained from experimenting and testing in one world as improvements in another. We report our insights from developing the architecture and cooperation procedures as additional research outcomes.Peer reviewe
Survey of context provisioning middleware
In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles. © 2009-2012 IEEE
Cloud service discovery and analysis: a unified framework
Over the past few years, cloud computing has been more and more attractive as a new
computing paradigm due to high flexibility for provisioning on-demand computing
resources that are used as services through the Internet. The issues around cloud service
discovery have considered by many researchers in the recent years. However,
in cloud computing, with the highly dynamic, distributed, the lack of standardized
description languages, diverse services offered at different levels and non-transparent
nature of cloud services, this research area has gained a significant attention. Robust
cloud service discovery approaches will assist the promotion and growth of cloud
service customers and providers, but will also provide a meaningful contribution to
the acceptance and development of cloud computing. In this dissertation, we have
proposed an automated cloud service discovery approach of cloud services. We have
also conducted extensive experiments to validate our proposed approach. The results
demonstrate the applicability of our approach and its capability of effectively identifying
and categorizing cloud services on the Internet. Firstly, we develop a novel
approach to build cloud service ontology. Cloud service ontology initially is built
based on the National Institute of Standards and Technology (NIST) cloud computing
standard. Then, we add new concepts to ontology by automatically analyzing real
cloud services based on cloud service ontology Algorithm. We also propose cloud
service categorization that use Term Frequency to weigh cloud service ontology concepts
and calculate cosine similarity to measure the similarity between cloud services.
The cloud service categorization algorithm is able to categorize cloud services to clusters for effective categorization of cloud services. In addition, we use Machine
Learning techniques to identify cloud service in real environment. Our cloud service
identifier is built by utilizing cloud service features extracted from the real cloud service
providers. We determine several features such as similarity function, semantic
ontology, cloud service description and cloud services components, to be used effectively
in identifying cloud service on the Web. Also, we build a unified model to
expose the cloud service’s features to a cloud service search user to ease the process of
searching and comparison among a large amount of cloud services by building cloud
service’s profile. Furthermore, we particularly develop a cloud service discovery Engine
that has capability to crawl the Web automatically and collect cloud services.
The collected datasets include meta-data of nearly 7,500 real-world cloud services
providers and nearly 15,000 services (2.45GB). The experimental results show that
our approach i) is able to effectively build automatic cloud service ontology, ii) is
robust in identifying cloud service in real environment and iii) is more scalable in
providing more details about cloud services.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 201
e-Commerce Ontology Web (e-COW)
The objective of "e-Commerce Ontology Web" (e-COW) is to implement the
ontology concept and semantic web in knowledge management to improve business
operation in organization. Generally, current problem of e-commerce system is
searching information is very difficult and sometimes may miss relevant information
especially details for certain products. Furthermore, human browsing and reading
required to extract relevant information from information sources. The semantic web
deals with important application areas such as knowledge management and
electronic commerce (both B2C and B2B). It may help to overcome many of the
current bottlenecks in these areas. In feasibility study, it helps author in identifying
the framework of semantic web and ontology development process. The important
feature ofthe e-COW is retrieving information based on the class and attributes of
data intree views, and advance search using ontology agents. Inaddition the system
will display products details in meaningful and organized which can help users to
understand easily. With development of many knowledge management systems
today, it shows that the knowledge management is very important especially to
organization. As a result, we know ontology has become important concept in
knowledge management especially for managing and organizing information and
data
SeMoM: a semantic middleware for IoT healthcare applications
De nos jours, l'internet des objets (IoT) connaît un intérêt considérable tant de la part du milieu universitaire que de l'industrie. Il a contribué à améliorer la qualité de
vie, la croissance des entreprises et l'efficacité dans de multiples domaines. Cependant, l'hétérogénéité des objets qui peuvent être connectés dans de tels environnements, rend
difficile leur interopérabilité. En outre, les observations produites par ces objets sont générées avec différents vocabulaires et formats de données. Cette hétérogénéité de
technologies dans le monde IoT rend nécessaire l'adoption de solutions génériques à l'échelle mondiale. De plus, elle rend difficile le partage et la réutilisation des données
dans d'autres buts que ceux pour lesquels elles ont été initialement mises en place. Dans cette thèse, nous abordons ces défis dans le contexte des applications de santé. Pour
cela, nous proposons de transformer les données brutes issues de capteurs en connaissances et en informations en s'appuyant sur les ontologies. Ces connaissances vont être
partagées entre les différents composants du système IoT.
En ce qui concerne les défis d'hétérogénéité et d'interopérabilité, notre contribution principale est une architecture IoT utilisant des ontologies pour permettre le déploiement
d'applications IoT sémantiques. Cette approche permet de partager les observations des capteurs, la contextualisation des données et la réutilisation des connaissances et des
informations traitées. Les contributions spécifiques comprennent :
* Conception d'une ontologie " Cognitive Semantic Sensor Network ontology (CoSSN) " : Cette ontologie vise à surmonter les défis d'interopérabilité sémantiques introduits par la
variété des capteurs potentiellement utilisés. CoSSN permet aussi de modéliser la représentation des connaissances des experts.
* Conception et mise en œuvre de SeMoM: SeMoM est une architecture flexible pour l'IoT intégrant l'ontologie CoSSN. Elle s'appuie sur un middleware orienté message (MoM) pour
offrir une solution à couplage faible entre les composants du système. Ceux-ci peuvent échanger des données d'observation sémantiques de manière flexible à l'aide du paradigme
producteur/consommateur.
Du point de vue applicatif, nous sommes intéressés aux applications de santé. Dans ce domaine, les approches spécifiques et les prototypes individuels sont des solutions
prédominantes ce qui rend difficile la collaboration entre différentes applications, en particulier dans un cas de patients multi-pathologies. En ce qui concerne ces défis, nous
nous sommes intéressés à deux études de cas: 1) la détection du risque de développement des escarres chez les personnes âgées et 2) la détection des activités de la vie
quotidienne (ADL) de personnes pour le suivi et l'assistance Ă domicile :
* Nous avons développé des extensions de CoSSN pour décrire chaque concept en lien avec les deux cas d'utilisation. Nous avons également développé des applications spécifiques
grâce à SeMoM qui mettent en œuvre des règles de connaissances expertes permettant d'évaluer et de détecter les escarres et les activités.
* Nous avons mis en œuvre et évaluer le framework SeMoM en se basant sur deux expérimentations. La première basée sur le déploiement d'un système ciblant la détection des
activités ADL dans un laboratoire d'expérimentation pour la santé (le Connected Health Lab). La seconde est basée sur le simulateur d'activités ADLSim développé par l'Université
d'Oslo. Ce simulateur a Ă©tĂ© utilisĂ© pour effectuer des tests de performances de notre solution en gĂ©nĂ©rant une quantitĂ© massive de donnĂ©es sur les activitĂ©s d'une personne Ă
domicile.Nowadays, the adoption of the Internet of Things (IoT) has received a considerable interest from both academia and industry. It provides enhancements in quality of life,
business growth and efficiency in multiple domains. However, the heterogeneity of the "Things" that can be connected in such environments makes interoperability among them a
challenging problem. Moreover, the observations produced by these "Things" are made available with heterogeneous vocabularies and data formats. This heterogeneity prevents
generic solutions from being adopted on a global scale and makes difficult to share and reuse data for other purposes than those for which they were originally set up. In this
thesis, we address these challenges in the context of healthcare applications considering how we transform raw data to cognitive knowledge and ontology-based information shared
between IoT system components.
With respect to heterogeneity and integration challenges, our main contribution is an ontology-based IoT architecture allowing the deployment of semantic IoT applications. This
approach allows sharing of sensors observations, contextualization of data and reusability of knowledge and processed information. Specific contributions include:
* Design of the Cognitive Semantic Sensor Network ontology (CoSSN) ontology: CoSSN aims at overcoming the semantic interoperability challenges introduced by the variety of
sensors potentially used. It also aims at describing expert knowledge related to a specific domain.
* Design and implementation of SeMoM: SeMoM is a flexible IoT architecture built on top of CoSSN ontology. It relies on a message oriented middleware (MoM) following the
publish/subscribe paradigm for a loosely coupled communication between system components that can exchange semantic observation data in a flexible way.
From the applicative perspective, we focus on healthcare applications. Indeed, specific approaches and individual prototypes are preeminent solutions in healthcare which
straighten the need of an interoperable solution especially for patients with multiple affections. With respect to these challenges, we elaborated two case studies 1) bedsore
risk detection and 2) Activities of Daily Living (ADL) detection as follows:
* We developed extensions of CoSSN to describe each domain concepts and we developed specific applications through SeMoM implementing expert knowledge rules and assessments of
bedsore and human activities.
* We implemented and evaluated the SeMoM framework in order to provide a proof of concept of our approach. Two experimentations have been realized for that target. The first is
based on a deployment of a system targeting the detection of ADL activities in a real smart platform. The other one is based on ADLSim, a simulator of activities for ambient
assisted living that can generate a massive amount of data related to the activities of a monitored person
Development of a Framework for Ontology Population Using Web Scraping in Mechatronics
One of the major challenges in engineering contexts is the efficient collection, management, and sharing of data. To address this problem, semantic technologies and ontologies are potent assets, although some tasks, such as ontology population, usually demand high maintenance effort. This thesis proposes a framework to automate data collection from sparse web resources and insert it into an ontology. In the first place, a product ontology is created based on the combination of several reference vocabularies, namely GoodRelations, the Basic Formal Ontology, ECLASS stan- dard, and an information model. Then, this study introduces a general procedure for developing a web scraping agent to collect data from the web. Subsequently, an algorithm based on lexical similarity measures is presented to map the collected data to the concepts of the ontology. Lastly, the collected data is inserted into the ontology. To validate the proposed solution, this thesis implements the previous steps to collect information about microcontrollers from three differ- ent websites. Finally, the thesis evaluates the use case results, draws conclusions, and suggests promising directions for future research
Information and Communication Technologies for Integrated Operations of Ships
Over the past three decades, information and communication technologies have
filled our daily life with great comfort and convenience. As the technology keeps
evolving, user expectations for more challenging cases that can benefit from advanced
information and communication technologies are increasing, e.g., the scenario
of Integrated Operations (IO) for ships in the maritime domain.
However, to realize integrated operations for ships is a complex task that involves
addressing problems such as interoperability among heterogeneous operation
applications and connectivity within harsh maritime communication environments.
The common approach was to tackle these challenges separately by service
integration and communication integration, respectively: each utilizes optimized
and independent implementations. Separate solutions work fine within their own
contexts, whereas conflicts and inconsistencies can be identified by integrating them
together for specific maritime scenarios. Therefore, connection between separate
solutions needs to be studied.
In this dissertation, we first take a look at complex systems to obtain useful
methodologies applied to integrated operations for ships. Then we study IO of
ships from different perspectives and divide the complex task into sub-tasks. We
explore separate approaches to these sub-tasks, examine the connection in between,
resolve inconsistencies if there are any, and continue the exploration process till a
compatible and integrated solution can be accomplished. In general, this journey
represents our argument for an integration-oriented complex system development
approach. In concrete, it shows the way on how to achieve IO of ships by both
providing connectivity in harsh communication environments and allowing interoperability
among heterogeneous operation applications, and most importantly by
ensuring the synergy in between. This synergy also gives hints on the evolution
towards a next generation network architecture for the future Internet