21,157 research outputs found
Application of ERTS-1 data to integrated state planning in the state of Maryland
There are no author-identified significant results in this report
Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review
Animals play a profoundly important and intricate role in our lives today.
Dogs have been human companions for thousands of years, but they now work
closely with us to assist the disabled, and in combat and search and rescue
situations. Farm animals are a critical part of the global food supply chain,
and there is increasing consumer interest in organically fed and humanely
raised livestock, and how it impacts our health and environmental footprint.
Wild animals are threatened with extinction by human induced factors, and
shrinking and compromised habitat. This review sets the goal to systematically
survey the existing literature in smart computing and sensing technologies for
domestic, farm and wild animal welfare. We use the notion of \emph{animal
welfare} in broad terms, to review the technologies for assessing whether
animals are healthy, free of pain and suffering, and also positively stimulated
in their environment. Also the notion of \emph{smart computing and sensing} is
used in broad terms, to refer to computing and sensing systems that are not
isolated but interconnected with communication networks, and capable of remote
data collection, processing, exchange and analysis. We review smart
technologies for domestic animals, indoor and outdoor animal farming, as well
as animals in the wild and zoos. The findings of this review are expected to
motivate future research and contribute to data, information and communication
management as well as policy for animal welfare
Wireless Health Monitoring using Passive WiFi Sensing
This paper presents a two-dimensional phase extraction system using passive
WiFi sensing to monitor three basic elderly care activities including breathing
rate, essential tremor and falls. Specifically, a WiFi signal is acquired
through two channels where the first channel is the reference one, whereas the
other signal is acquired by a passive receiver after reflection from the human
target. Using signal processing of cross-ambiguity function, various features
in the signal are extracted. The entire implementations are performed using
software defined radios having directional antennas. We report the accuracy of
our system in different conditions and environments and show that breathing
rate can be measured with an accuracy of 87% when there are no obstacles. We
also show a 98% accuracy in detecting falls and 93% accuracy in classifying
tremor. The results indicate that passive WiFi systems show great promise in
replacing typical invasive health devices as standard tools for health care.Comment: 6 pages, 8 figures, conference pape
MOSDEN: A Scalable Mobile Collaborative Platform for Opportunistic Sensing Applications
Mobile smartphones along with embedded sensors have become an efficient
enabler for various mobile applications including opportunistic sensing. The
hi-tech advances in smartphones are opening up a world of possibilities. This
paper proposes a mobile collaborative platform called MOSDEN that enables and
supports opportunistic sensing at run time. MOSDEN captures and shares sensor
data across multiple apps, smartphones and users. MOSDEN supports the emerging
trend of separating sensors from application-specific processing, storing and
sharing. MOSDEN promotes reuse and re-purposing of sensor data hence reducing
the efforts in developing novel opportunistic sensing applications. MOSDEN has
been implemented on Android-based smartphones and tablets. Experimental
evaluations validate the scalability and energy efficiency of MOSDEN and its
suitability towards real world applications. The results of evaluation and
lessons learned are presented and discussed in this paper.Comment: Accepted to be published in Transactions on Collaborative Computing,
2014. arXiv admin note: substantial text overlap with arXiv:1310.405
Gait Analysis of Horses for Lameness Detection with Radar Sensors
This paper presents the preliminary investigation of the use of
radar signatures to detect and assess lameness of horses and its
severity. Radar sensors in this context can provide attractive
contactless sensing capabilities, as a complementary or
alternative technology to the current techniques for lameness
assessment using video-graphics and inertial sensors attached to the horses' body. The paper presents several examples of experimental data collected at the Weipers Centre Equine
Hospital at the University of Glasgow, showing the micro-
Doppler signatures of horses and preliminary results of their
analysis
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