3,186 research outputs found
Pedestrian Counting Based on Piezoelectric Vibration Sensor
Pedestrian counting has attracted much interest of the academic and industry communities for its widespread application in many real-world scenarios. While many recent studies have focused on computer vision-based solutions for the problem, the deployment of cameras brings up concerns about privacy invasion. This paper proposes a novel indoor pedestrian counting approach, based on footstep-induced structural vibration signals with piezoelectric sensors. The approach is privacy-protecting because no audio or video data is acquired. Our approach analyzes the space-differential features from the vibration signals caused by pedestrian footsteps and outputs the number of pedestrians. The proposed approach supports multiple pedestrians walking together with signal mixture. Moreover, it makes no requirement about the number of groups of walking people in the detection area. The experimental results show that the averaged F1-score of our approach is over 0.98, which is better than the vibration signal-based state-of-the-art methods.Peer reviewe
Development and evaluation of a prototype global volcano surveillance system utilizing the ERTS-1 satellite data collection system
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
Intelligent Traffic Monitoring Systems for Vehicle Classification: A Survey
A traffic monitoring system is an integral part of Intelligent Transportation
Systems (ITS). It is one of the critical transportation infrastructures that
transportation agencies invest a huge amount of money to collect and analyze
the traffic data to better utilize the roadway systems, improve the safety of
transportation, and establish future transportation plans. With recent advances
in MEMS, machine learning, and wireless communication technologies, numerous
innovative traffic monitoring systems have been developed. In this article, we
present a review of state-of-the-art traffic monitoring systems focusing on the
major functionality--vehicle classification. We organize various vehicle
classification systems, examine research issues and technical challenges, and
discuss hardware/software design, deployment experience, and system performance
of vehicle classification systems. Finally, we discuss a number of critical
open problems and future research directions in an aim to provide valuable
resources to academia, industry, and government agencies for selecting
appropriate technologies for their traffic monitoring applications.Comment: Published in IEEE Acces
Trailgazers: A Scoping Study of Footfall Sensors to Aid Tourist Trail Management in Ireland and Other Atlantic Areas of Europe
This paper examines the current state of the art of commercially available outdoor footfall sensor technologies and defines individually tailored solutions for the walking trails involved in an ongoing research project. Effective implementation of footfall sensors can facilitate quantitative analysis of user patterns, inform maintenance schedules and assist in achieving management objectives, such as identifying future user trends like cyclo-tourism. This paper is informed by primary research conducted for the EU funded project TrailGazersBid (hereafter referred to as TrailGazers), led by Donegal County Council, and has Sligo County Council and Causeway Coast and Glens Council (NI) among the 10 project partners. The project involves three trails in Ireland and five other trails from Europe for comparison. It incorporates the footfall capture and management experiences of trail management within the EU Atlantic area and desk-based research on current footfall technologies and data capture strategies. We have examined 6 individual types of sensor and discuss the advantages and disadvantages of each. We provide key learnings and insights that can help to inform trail managers on sensor options, along with a decision-making tool based on the key factors of the power source and mounting method. The research findings can also be applied to other outdoor footfall monitoring scenarios
A survey: localization and tracking mobile targets through wireless sensors network
Wireless sensor network applications have been
deployed widely. Sensor networks involve sensor nodes which are
very small in size. They are low in cost, and have a low battery
life. Sensor nodes are capable of solving a variety of collaborative
problems, such as, monitoring and surveillance. One of the
critical components in wireless sensor networks is the localizing
tracking sensor or mobile node. In this paper we will discuss the
various location system techniques and categorize these
techniques based on the communication between nodes into
centralized and decentralized localization techniques. The
tracking techniques are categorized into four main types. Each
type will be compared and discussed in detail. We will suggest
ways of implementing the techniques and finally carry out an
evaluation
Wi-Fi For Indoor Device Free Passive Localization (DfPL): An Overview
The world is moving towards an interconnected and intercommunicable network of animate and inanimate objects with the emergence of Internet of Things (IoT) concept which is expected to have 50 billion connected devices by 2020. The wireless communication enabled devices play a major role in the realization of IoT. In Malaysia, home and business Internet Service Providers (ISP) bundle Wi-Fi modems working in 2.4 GHz Industrial, Scientific and Medical (ISM) radio band with their internet services. This makes Wi-Fi the most eligible protocol to serve as a local as well as internet data link for the IoT devices. Besides serving as a data link, human entity presence and location information in a multipath rich indoor environment can be harvested by monitoring and processing the changes in the Wi-Fi Radio Frequency (RF) signals. This paper comprehensively discusses the initiation and evolution of Wi-Fi based Indoor Device free Passive Localization (DfPL) since the concept was first introduced by Youssef et al. in 2007. Alongside the overview, future directions of DfPL in line with ongoing evolution of Wi-Fi based IoT devices are briefly discussed in this paper
JUNO Conceptual Design Report
The Jiangmen Underground Neutrino Observatory (JUNO) is proposed to determine
the neutrino mass hierarchy using an underground liquid scintillator detector.
It is located 53 km away from both Yangjiang and Taishan Nuclear Power Plants
in Guangdong, China. The experimental hall, spanning more than 50 meters, is
under a granite mountain of over 700 m overburden. Within six years of running,
the detection of reactor antineutrinos can resolve the neutrino mass hierarchy
at a confidence level of 3-4, and determine neutrino oscillation
parameters , , and to
an accuracy of better than 1%. The JUNO detector can be also used to study
terrestrial and extra-terrestrial neutrinos and new physics beyond the Standard
Model. The central detector contains 20,000 tons liquid scintillator with an
acrylic sphere of 35 m in diameter. 17,000 508-mm diameter PMTs with high
quantum efficiency provide 75% optical coverage. The current choice of
the liquid scintillator is: linear alkyl benzene (LAB) as the solvent, plus PPO
as the scintillation fluor and a wavelength-shifter (Bis-MSB). The number of
detected photoelectrons per MeV is larger than 1,100 and the energy resolution
is expected to be 3% at 1 MeV. The calibration system is designed to deploy
multiple sources to cover the entire energy range of reactor antineutrinos, and
to achieve a full-volume position coverage inside the detector. The veto system
is used for muon detection, muon induced background study and reduction. It
consists of a Water Cherenkov detector and a Top Tracker system. The readout
system, the detector control system and the offline system insure efficient and
stable data acquisition and processing.Comment: 328 pages, 211 figure
Latitude, longitude, and beyond:mining mobile objects' behavior
Rapid advancements in Micro-Electro-Mechanical Systems (MEMS), and wireless communications, have resulted in a surge in data generation. Mobility data is one of the various forms of data, which are ubiquitously collected by different location sensing devices. Extensive knowledge about the behavior of humans and wildlife is buried in raw mobility data. This knowledge can be used for realizing numerous viable applications ranging from wildlife movement analysis, to various location-based recommendation systems, urban planning, and disaster relief. With respect to what mentioned above, in this thesis, we mainly focus on providing data analytics for understanding the behavior and interaction of mobile entities (humans and animals). To this end, the main research question to be addressed is: How can behaviors and interactions of mobile entities be determined from mobility data acquired by (mobile) wireless sensor nodes in an accurate and efficient manner? To answer the above-mentioned question, both application requirements and technological constraints are considered in this thesis. On the one hand, applications requirements call for accurate data analytics to uncover hidden information about individual behavior and social interaction of mobile entities, and to deal with the uncertainties in mobility data. Technological constraints, on the other hand, require these data analytics to be efficient in terms of their energy consumption and to have low memory footprint, and processing complexity
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