32,146 research outputs found
Performance testing of a low power consumption wireless sensor communication system integrated with an energy harvesting power source
This paper presents the performance testing results of a wireless sensor communication system with low power consumption integrated with a vibration energy harvesting power source. The experiments focus on the systemâs capability to perform continuous monitoring and to wirelessly transmit the data acquired from the sensors to a user base station, completely battery-free. Energy harvesting technologies together with system design optimisation for power consumption minimisation ensure the systemâs energy autonomous capability demonstrated in this paper by presenting the promising testing results achieved following its integration with Structural Health Monitoring (SHM) and Body Area Network (BAN) applications
The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey
The Internet of Things (IoT) is a dynamic global information network
consisting of internet-connected objects, such as Radio-frequency
identification (RFIDs), sensors, actuators, as well as other instruments and
smart appliances that are becoming an integral component of the future
internet. Over the last decade, we have seen a large number of the IoT
solutions developed by start-ups, small and medium enterprises, large
corporations, academic research institutes (such as universities), and private
and public research organisations making their way into the market. In this
paper, we survey over one hundred IoT smart solutions in the marketplace and
examine them closely in order to identify the technologies used,
functionalities, and applications. More importantly, we identify the trends,
opportunities and open challenges in the industry-based the IoT solutions.
Based on the application domain, we classify and discuss these solutions under
five different categories: smart wearable, smart home, smart, city, smart
environment, and smart enterprise. This survey is intended to serve as a
guideline and conceptual framework for future research in the IoT and to
motivate and inspire further developments. It also provides a systematic
exploration of existing research and suggests a number of potentially
significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201
Adaptive sampling in context-aware systems: a machine learning approach
As computing systems become ever more pervasive, there is an increasing need for them to understand and adapt to the state of the environment around them: that is, their context. This understanding comes with considerable reliance on a range of sensors. However, portable devices are also very constrained in terms of power, and hence the amount of sensing must be minimised. In this paper, we present a machine learning architecture for context awareness which is designed to balance the sampling rates (and hence energy consumption) of individual sensors with the significance of the input from that sensor. This significance is based on predictions of the likely next context. The architecture is implemented using a selected range of user contexts from a collected data set. Simulation results show reliable context identification results. The proposed architecture is shown to significantly reduce the energy requirements of the sensors with minimal loss of accuracy in context identification
Sensing as a Service Model for Smart Cities Supported by Internet of Things
The world population is growing at a rapid pace. Towns and cities are
accommodating half of the world's population thereby creating tremendous
pressure on every aspect of urban living. Cities are known to have large
concentration of resources and facilities. Such environments attract people
from rural areas. However, unprecedented attraction has now become an
overwhelming issue for city governance and politics. The enormous pressure
towards efficient city management has triggered various Smart City initiatives
by both government and private sector businesses to invest in ICT to find
sustainable solutions to the growing issues. The Internet of Things (IoT) has
also gained significant attention over the past decade. IoT envisions to
connect billions of sensors to the Internet and expects to use them for
efficient and effective resource management in Smart Cities. Today
infrastructure, platforms, and software applications are offered as services
using cloud technologies. In this paper, we explore the concept of sensing as a
service and how it fits with the Internet of Things. Our objective is to
investigate the concept of sensing as a service model in technological,
economical, and social perspectives and identify the major open challenges and
issues.Comment: Transactions on Emerging Telecommunications Technologies 2014
(Accepted for Publication
End-to-End Privacy for Open Big Data Markets
The idea of an open data market envisions the creation of a data trading
model to facilitate exchange of data between different parties in the Internet
of Things (IoT) domain. The data collected by IoT products and solutions are
expected to be traded in these markets. Data owners will collect data using IoT
products and solutions. Data consumers who are interested will negotiate with
the data owners to get access to such data. Data captured by IoT products will
allow data consumers to further understand the preferences and behaviours of
data owners and to generate additional business value using different
techniques ranging from waste reduction to personalized service offerings. In
open data markets, data consumers will be able to give back part of the
additional value generated to the data owners. However, privacy becomes a
significant issue when data that can be used to derive extremely personal
information is being traded. This paper discusses why privacy matters in the
IoT domain in general and especially in open data markets and surveys existing
privacy-preserving strategies and design techniques that can be used to
facilitate end to end privacy for open data markets. We also highlight some of
the major research challenges that need to be address in order to make the
vision of open data markets a reality through ensuring the privacy of
stakeholders.Comment: Accepted to be published in IEEE Cloud Computing Magazine: Special
Issue Cloud Computing and the La
- âŚ