2,766 research outputs found
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
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
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
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
Semantic Gateway as a Service architecture for IoT Interoperability
The Internet of Things (IoT) is set to occupy a substantial component of
future Internet. The IoT connects sensors and devices that record physical
observations to applications and services of the Internet. As a successor to
technologies such as RFID and Wireless Sensor Networks (WSN), the IoT has
stumbled into vertical silos of proprietary systems, providing little or no
interoperability with similar systems. As the IoT represents future state of
the Internet, an intelligent and scalable architecture is required to provide
connectivity between these silos, enabling discovery of physical sensors and
interpretation of messages between things. This paper proposes a gateway and
Semantic Web enabled IoT architecture to provide interoperability between
systems using established communication and data standards. The Semantic
Gateway as Service (SGS) allows translation between messaging protocols such as
XMPP, CoAP and MQTT via a multi-protocol proxy architecture. Utilization of
broadly accepted specifications such as W3C's Semantic Sensor Network (SSN)
ontology for semantic annotations of sensor data provide semantic
interoperability between messages and support semantic reasoning to obtain
higher-level actionable knowledge from low-level sensor data.Comment: 16 page
Security Management Framework for the Internet of Things
The increase in the design and development of wireless communication technologies
offers multiple opportunities for the management and control of cyber-physical systems
with connections between smart and autonomous devices, which provide the delivery
of simplified data through the use of cloud computing. Given this relationship with the
Internet of Things (IoT), it established the concept of pervasive computing that allows
any object to communicate with services, sensors, people, and objects without human
intervention. However, the rapid growth of connectivity with smart applications through
autonomous systems connected to the internet has allowed the exposure of numerous
vulnerabilities in IoT systems by malicious users.
This dissertation developed a novel ontology-based cybersecurity framework to
improve security in IoT systems using an ontological analysis to adapt appropriate
security services addressed to threats. The composition of this proposal explores
two approaches: (1) design time, which offers a dynamic method to build security
services through the application of a methodology directed to models considering
existing business processes; and (2) execution time, which involves monitoring the IoT
environment, classifying vulnerabilities and threats, and acting in the environment,
ensuring the correct adaptation of existing services.
The validation approach was used to demonstrate the feasibility of implementing the
proposed cybersecurity framework. It implies the evaluation of the ontology to offer
a qualitative evaluation based on the analysis of several criteria and also a proof of
concept implemented and tested using specific industrial scenarios. This dissertation
has been verified by adopting a methodology that follows the acceptance in the research
community through technical validation in the application of the concept in an industrial
setting.O aumento no projeto e desenvolvimento de tecnologias de comunicação sem fio oferece
mĂşltiplas oportunidades para a gestĂŁo e controle de sistemas ciber-fĂsicos com conexões
entre dispositivos inteligentes e autĂ´nomos, os quais proporcionam a entrega de dados
simplificados através do uso da computação em nuvem. Diante dessa relação com
a Internet das Coisas (IoT) estabeleceu-se o conceito de computação pervasiva que
permite que qualquer objeto possa comunicar com os serviços, sensores, pessoas e objetos
sem intervenção humana. Entretanto, o rápido crescimento da conectividade com as
aplicações inteligentes através de sistemas autônomos conectados com a internet permitiu
a exposição de inúmeras vulnerabilidades dos sistemas IoT para usuários maliciosos.
Esta dissertação desenvolveu um novo framework de cibersegurança baseada em
ontologia para melhorar a segurança em sistemas IoT usando uma análise ontológica
para a adaptação de serviços de segurança apropriados endereçados para as ameaças. A
composição dessa proposta explora duas abordagens: (1) tempo de projeto, o qual oferece
um método dinâmico para construir serviços de segurança através da aplicação de uma
metodologia dirigida a modelos, considerando processos empresariais existentes; e (2)
tempo de execução, o qual envolve o monitoramento do ambiente IoT, a classificação de
vulnerabilidades e ameaças, e a atuação no ambiente garantindo a correta adaptação dos
serviços existentes.
Duas abordagens de validação foram utilizadas para demonstrar a viabilidade da
implementação do framework de cibersegurança proposto. Isto implica na avaliação da
ontologia para oferecer uma avaliação qualitativa baseada na análise de diversos critérios
e tambĂ©m uma prova de conceito implementada e testada usando cenários especĂficos.
Esta dissertação foi validada adotando uma metodologia que segue a validação na
comunidade cientĂfica atravĂ©s da validação tĂ©cnica na aplicação do nosso conceito em
um cenário industrial
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Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
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