14,987 research outputs found
Semi-automatic semantic enrichment of raw sensor data
One of the more recent sources of large volumes of generated data is sensor devices, where dedicated sensing equipment is used to monitor events and happenings in a wide range of domains, including monitoring human biometrics. In recent trials to examine the effects that key moments in movies have on the human body, we fitted fitted with a number of biometric sensor devices and monitored them as they watched a range of dierent movies in groups. The purpose of these experiments was to examine the correlation between humans' highlights in movies as observed from biometric sensors, and highlights in the same movies as identified by our automatic movie analysis techniques. However,the problem with this type of experiment is that both the analysis of the video stream and the sensor data readings are not directly usable
in their raw form because of the sheer volume of low-level data values generated both from the sensors and from the movie analysis. This work describes the semi-automated enrichment of both video analysis and sensor data and the mechanism used to query the data in both centralised
environments, and in a peer-to-peer architecture when the number of sensor devices grows to large numbers. We present and validate a scalable means of semi-automating the semantic enrichment of sensor data, thereby providing a means of large-scale sensor management
A Data Annotation Architecture for Semantic Applications in Virtualized Wireless Sensor Networks
Wireless Sensor Networks (WSNs) have become very popular and are being used
in many application domains (e.g. smart cities, security, gaming and
agriculture). Virtualized WSNs allow the same WSN to be shared by multiple
applications. Semantic applications are situation-aware and can potentially
play a critical role in virtualized WSNs. However, provisioning them in such
settings remains a challenge. The key reason is that semantic applications
provisioning mandates data annotation. Unfortunately it is no easy task to
annotate data collected in virtualized WSNs. This paper proposes a data
annotation architecture for semantic applications in virtualized heterogeneous
WSNs. The architecture uses overlays as the cornerstone, and we have built a
prototype in the cloud environment using Google App Engine. The early
performance measurements are also presented.Comment: This paper has been accepted for presentation in main technical
session of 14th IFIP/IEEE Symposium on Integrated Network and Service
Management (IM 2015) to be held on 11-15 May, 2015, Ottawa, Canad
A Distributed Sensor Data Search Platform for Internet of Things Environments
Recently, the number of devices has grown increasingly and it is hoped that,
between 2015 and 2016, 20 billion devices will be connected to the Internet and
this market will move around 91.5 billion dollars. The Internet of Things (IoT)
is composed of small sensors and actuators embedded in objects with Internet
access and will play a key role in solving many challenges faced in today's
society. However, the real capacity of IoT concepts is constrained as the
current sensor networks usually do not exchange information with other sources.
In this paper, we propose the Visual Search for Internet of Things (ViSIoT)
platform to help technical and non-technical users to discover and use sensors
as a service for different application purposes. As a proof of concept, a real
case study is used to generate weather condition reports to support rheumatism
patients. This case study was executed in a working prototype and a performance
evaluation is presented.Comment: International Journal of Services Computing (ISSN 2330-4472) Vol. 4,
No.1, January - March, 201
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
From Sensor to Observation Web with Environmental Enablers in the Future Internet
This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)
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
Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters
Demands on the disaster response capacity of the European Union are likely to
increase, as the impacts of disasters continue to grow both in size and
frequency. This has resulted in intensive research on issues concerning
spatially-explicit information and modelling and their multiple sources of
uncertainty. Geospatial support is one of the forms of assistance frequently
required by emergency response centres along with hazard forecast and event
management assessment. Robust modelling of natural hazards requires dynamic
simulations under an array of multiple inputs from different sources.
Uncertainty is associated with meteorological forecast and calibration of the
model parameters. Software uncertainty also derives from the data
transformation models (D-TM) needed for predicting hazard behaviour and its
consequences. On the other hand, social contributions have recently been
recognized as valuable in raw-data collection and mapping efforts traditionally
dominated by professional organizations. Here an architecture overview is
proposed for adaptive and robust modelling of natural hazards, following the
Semantic Array Programming paradigm to also include the distributed array of
social contributors called Citizen Sensor in a semantically-enhanced strategy
for D-TM modelling. The modelling architecture proposes a multicriteria
approach for assessing the array of potential impacts with qualitative rapid
assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema
and complementing more traditional and accurate a-posteriori assessment. We
discuss the computational aspect of environmental risk modelling using
array-based parallel paradigms on High Performance Computing (HPC) platforms,
in order for the implications of urgency to be introduced into the systems
(Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of
Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua
From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web
In the process of scientific research, many information objects are
generated, all of which may remain valuable indefinitely. However, artifacts
such as instrument data and associated calibration information may have little
value in isolation; their meaning is derived from their relationships to each
other. Individual artifacts are best represented as components of a life cycle
that is specific to a scientific research domain or project. Current cataloging
practices do not describe objects at a sufficient level of granularity nor do
they offer the globally persistent identifiers necessary to discover and manage
scholarly products with World Wide Web standards. The Open Archives
Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these
requirements. We demonstrate a conceptual implementation of OAI-ORE to
represent the scientific life cycles of embedded networked sensor applications
in seismology and environmental sciences. By establishing relationships between
publications, data, and contextual research information, we illustrate how to
obtain a richer and more realistic view of scientific practices. That view can
facilitate new forms of scientific research and learning. Our analysis is
framed by studies of scientific practices in a large, multi-disciplinary,
multi-university science and engineering research center, the Center for
Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for
Information Science and Technology (JASIST
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