12,189 research outputs found
EC-IoT : an easy configuration framework for constrained IoT devices
Connected devices offer tremendous opportunities. However, their configuration and control remains a major challenge in order to reach widespread adoption by less technically skilled people. Over the past few years, a lot of attention has been given to improve the configuration process of constrained devices with limited resources, such as available memory and absence of a user interface. Still, a major deficiency is the lack of a streamlined, standardized configuration process. In this paper we propose EC-IoT, a novel configuration framework for constrained IoT devices. The proposed framework makes use of open standards, leveraging upon the Constrained Application Protocol (CoAP), an application protocol that enables HTTP-like RESTful interactions with constrained devices. To validate the proposed approach, we present a prototype implementation of the EC-IoT framework and assess its scalability.The research from DEWI project (www.dewi-project.eu)
leading to these results has received funding from the
ARTEMIS Joint Undertaking under grant agreement n
621353 and from the agency for Flanders Innovation &
Entrepreneurship (VLAIO). The research from the ITEA2
FUSE-IT project (13023) leading to these results has re-
ceived funding from the agency for Flanders Innovation &
Entrepreneurship (VLAIO)
Context-aware Dynamic Discovery and Configuration of 'Things' in Smart Environments
The Internet of Things (IoT) is a dynamic global information network
consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as
well as other instruments and smart appliances that are becoming an integral
component of the future Internet. Currently, such Internet-connected objects or
`things' outnumber both people and computers connected to the Internet and
their population is expected to grow to 50 billion in the next 5 to 10 years.
To be able to develop IoT applications, such `things' must become dynamically
integrated into emerging information networks supported by architecturally
scalable and economically feasible Internet service delivery models, such as
cloud computing. Achieving such integration through discovery and configuration
of `things' is a challenging task. Towards this end, we propose a Context-Aware
Dynamic Discovery of {Things} (CADDOT) model. We have developed a tool
SmartLink, that is capable of discovering sensors deployed in a particular
location despite their heterogeneity. SmartLink helps to establish the direct
communication between sensor hardware and cloud-based IoT middleware platforms.
We address the challenge of heterogeneity using a plug in architecture. Our
prototype tool is developed on an Android platform. Further, we employ the
Global Sensor Network (GSN) as the IoT middleware for the proof of concept
validation. The significance of the proposed solution is validated using a
test-bed that comprises 52 Arduino-based Libelium sensors.Comment: Big Data and Internet of Things: A Roadmap for Smart Environments,
Studies in Computational Intelligence book series, Springer Berlin
Heidelberg, 201
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
Semantic-driven Configuration of Internet of Things Middleware
We are currently observing emerging solutions to enable the Internet of
Things (IoT). Efficient and feature rich IoT middeware platforms are key
enablers for IoT. However, due to complexity, most of these middleware
platforms are designed to be used by IT experts. In this paper, we propose a
semantics-driven model that allows non-IT experts (e.g. plant scientist, city
planner) to configure IoT middleware components easier and faster. Such tools
allow them to retrieve the data they want without knowing the underlying
technical details of the sensors and the data processing components. We propose
a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of
automated context-aware configuration of filtering, fusion, and reasoning
mechanisms in IoT middleware according to the problems at hand. We incorporate
semantic technologies in solving the above challenges. We demonstrate the
feasibility and the scalability of our approach through a prototype
implementation based on an IoT middleware called Global Sensor Networks (GSN),
though our model can be generalized into any other middleware platform. We
evaluate CASCoM in agriculture domain and measure both performance in terms of
usability and computational complexity.Comment: 9th International Conference on Semantics, Knowledge & Grids (SKG),
Beijing, China, October, 201
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices
The Internet of Things (IoT) is part of Future Internet and will comprise
many billions of Internet Connected Objects (ICO) or `things' where things can
sense, communicate, compute and potentially actuate as well as have
intelligence, multi-modal interfaces, physical/ virtual identities and
attributes. Collecting data from these objects is an important task as it
allows software systems to understand the environment better. Many different
hardware devices may involve in the process of collecting and uploading sensor
data to the cloud where complex processing can occur. Further, we cannot expect
all these objects to be connected to the computers due to technical and
economical reasons. Therefore, we should be able to utilize resource
constrained devices to collect data from these ICOs. On the other hand, it is
critical to process the collected sensor data before sending them to the cloud
to make sure the sustainability of the infrastructure due to energy
constraints. This requires to move the sensor data processing tasks towards the
resource constrained computational devices (e.g. mobile phones). In this paper,
we propose Mobile Sensor Data Processing Engine (MOSDEN), an plug-in-based IoT
middleware for mobile devices, that allows to collect and process sensor data
without programming efforts. Our architecture also supports sensing as a
service model. We present the results of the evaluations that demonstrate its
suitability towards real world deployments. Our proposed middleware is built on
Android platform
- …