37,805 research outputs found
A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things
The Internet of Things (IoT) is envisioned as a global network of connected
things enabling ubiquitous machine-to-machine (M2M) communication. With
estimations of billions of sensors and devices to be connected in the coming
years, the IoT has been advocated as having a great potential to impact the way
we live, but also how we work. However, the connectivity aspect in itself only
accounts for the underlying M2M infrastructure. In order to properly support
engineering IoT systems and applications, it is key to orchestrate
heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that
the system can exhibit a goal-directed behaviour and take appropriate actions.
Yet, this form of interaction between things needs to take a user-centric
approach and by no means elude the users' requirements. To this end,
contextualisation is an important feature of the system, allowing it to infer
user activities and prompt the user with relevant information and interactions
even in the absence of intentional commands. In this work we propose a
role-based model for emergent configurations of connected systems as a means to
model, manage, and reason about IoT systems including the user's interaction
with them. We put a special focus on integrating the user perspective in order
to guide the emergent configurations such that systems goals are aligned with
the users' intentions. We discuss related scientific and technical challenges
and provide several uses cases outlining the concept of emergent
configurations.Comment: In Proceedings of the Second International Workshop on the Internet
of Agents @AAMAS201
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
Middleware platform for distributed applications incorporating robots, sensors and the cloud
Cyber-physical systems in the factory of the future
will consist of cloud-hosted software governing an agile
production process executed by autonomous mobile robots
and controlled by analyzing the data from a vast number of
sensors. CPSs thus operate on a distributed production floor
infrastructure and the set-up continuously changes with each
new manufacturing task. In this paper, we present our OSGibased
middleware that abstracts the deployment of servicebased
CPS software components on the underlying distributed
platform comprising robots, actuators, sensors and the cloud.
Moreover, our middleware provides specific support to develop
components based on artificial neural networks, a technique that
recently became very popular for sensor data analytics and robot
actuation. We demonstrate a system where a robot takes actions
based on the input from sensors in its vicinity
City Data Fusion: Sensor Data Fusion in the Internet of Things
Internet of Things (IoT) has gained substantial attention recently and play a
significant role in smart city application deployments. A number of such smart
city applications depend on sensor fusion capabilities in the cloud from
diverse data sources. We introduce the concept of IoT and present in detail ten
different parameters that govern our sensor data fusion evaluation framework.
We then evaluate the current state-of-the art in sensor data fusion against our
sensor data fusion framework. Our main goal is to examine and survey different
sensor data fusion research efforts based on our evaluation framework. The
major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed
Systems and Technologies (IJDST), 201
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