140,401 research outputs found
Software Defined Media: Virtualization of Audio-Visual Services
Internet-native audio-visual services are witnessing rapid development. Among
these services, object-based audio-visual services are gaining importance. In
2014, we established the Software Defined Media (SDM) consortium to target new
research areas and markets involving object-based digital media and
Internet-by-design audio-visual environments. In this paper, we introduce the
SDM architecture that virtualizes networked audio-visual services along with
the development of smart buildings and smart cities using Internet of Things
(IoT) devices and smart building facilities. Moreover, we design the SDM
architecture as a layered architecture to promote the development of innovative
applications on the basis of rapid advancements in software-defined networking
(SDN). Then, we implement a prototype system based on the architecture, present
the system at an exhibition, and provide it as an SDM API to application
developers at hackathons. Various types of applications are developed using the
API at these events. An evaluation of SDM API access shows that the prototype
SDM platform effectively provides 3D audio reproducibility and interactiveness
for SDM applications.Comment: IEEE International Conference on Communications (ICC2017), Paris,
France, 21-25 May 201
Connecting the Physical World with Arduino in SECE
The Internet of Things (IoT) enables the physical world to be connected and controlled over the Internet. This paper presents a smart gateway platform that connects everyday objects such as lights, thermometers, and TVs over the Internet. The proposed hardware architecture is implemented on an Arduino platform with a variety of off the shelf home automation technologies such as Zigbee and X10. Using the microcontroller-based platform, the SECE (Sense Everything, Control Everything) system allows users to create various IoT services such as monitoring sensors, controlling actuators, triggering action events, and periodic sensor reporting. We give an overview of the Arduino-based smart gateway architecture and its integration into SECE
Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration
There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems ‘expose’ relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT)
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
Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making
The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study
MONICA in Hamburg: Towards Large-Scale IoT Deployments in a Smart City
Modern cities and metropolitan areas all over the world face new management
challenges in the 21st century primarily due to increasing demands on living
standards by the urban population. These challenges range from climate change,
pollution, transportation, and citizen engagement, to urban planning, and
security threats. The primary goal of a Smart City is to counteract these
problems and mitigate their effects by means of modern ICT to improve urban
administration and infrastructure. Key ideas are to utilise network
communication to inter-connect public authorities; but also to deploy and
integrate numerous sensors and actuators throughout the city infrastructure -
which is also widely known as the Internet of Things (IoT). Thus, IoT
technologies will be an integral part and key enabler to achieve many
objectives of the Smart City vision.
The contributions of this paper are as follows. We first examine a number of
IoT platforms, technologies and network standards that can help to foster a
Smart City environment. Second, we introduce the EU project MONICA which aims
for demonstration of large-scale IoT deployments at public, inner-city events
and give an overview on its IoT platform architecture. And third, we provide a
case-study report on SmartCity activities by the City of Hamburg and provide
insights on recent (on-going) field tests of a vertically integrated,
end-to-end IoT sensor application.Comment: 6 page
Modeling the Internet of Things: a simulation perspective
This paper deals with the problem of properly simulating the Internet of
Things (IoT). Simulating an IoT allows evaluating strategies that can be
employed to deploy smart services over different kinds of territories. However,
the heterogeneity of scenarios seriously complicates this task. This imposes
the use of sophisticated modeling and simulation techniques. We discuss novel
approaches for the provision of scalable simulation scenarios, that enable the
real-time execution of massively populated IoT environments. Attention is given
to novel hybrid and multi-level simulation techniques that, when combined with
agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches,
can provide means to perform highly detailed simulations on demand. To support
this claim, we detail a use case concerned with the simulation of vehicular
transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High
Performance Computing and Simulation (HPCS 2017
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
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
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