12,193 research outputs found
Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions
Traditional power grids are being transformed into Smart Grids (SGs) to
address the issues in existing power system due to uni-directional information
flow, energy wastage, growing energy demand, reliability and security. SGs
offer bi-directional energy flow between service providers and consumers,
involving power generation, transmission, distribution and utilization systems.
SGs employ various devices for the monitoring, analysis and control of the
grid, deployed at power plants, distribution centers and in consumers' premises
in a very large number. Hence, an SG requires connectivity, automation and the
tracking of such devices. This is achieved with the help of Internet of Things
(IoT). IoT helps SG systems to support various network functions throughout the
generation, transmission, distribution and consumption of energy by
incorporating IoT devices (such as sensors, actuators and smart meters), as
well as by providing the connectivity, automation and tracking for such
devices. In this paper, we provide a comprehensive survey on IoT-aided SG
systems, which includes the existing architectures, applications and prototypes
of IoT-aided SG systems. This survey also highlights the open issues,
challenges and future research directions for IoT-aided SG systems
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
An IoT-based solution for monitoring a fleet of educational buildings focusing on energy efficiency
Raising awareness among young people and changing their behaviour and habits concerning energy usage iskey to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examinesways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both theusers (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizenĹ› behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system's high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies andservices in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer newapp-based solutions that can be used either for educational purposes or for managing the energy efficiency ofthebuilding. The system is replicable and adaptable to settings that may be different than the scenarios envisionedhere (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity
Long-Range Communications in Unlicensed Bands: the Rising Stars in the IoT and Smart City Scenarios
Connectivity is probably the most basic building block of the Internet of
Things (IoT) paradigm. Up to know, the two main approaches to provide data
access to the \emph{things} have been based either on multi-hop mesh networks
using short-range communication technologies in the unlicensed spectrum, or on
long-range, legacy cellular technologies, mainly 2G/GSM, operating in the
corresponding licensed frequency bands. Recently, these reference models have
been challenged by a new type of wireless connectivity, characterized by
low-rate, long-range transmission technologies in the unlicensed sub-GHz
frequency bands, used to realize access networks with star topology which are
referred to a \emph{Low-Power Wide Area Networks} (LPWANs). In this paper, we
introduce this new approach to provide connectivity in the IoT scenario,
discussing its advantages over the established paradigms in terms of
efficiency, effectiveness, and architectural design, in particular for the
typical Smart Cities applications
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
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