37,697 research outputs found
The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks
The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management
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
Embedded Sensor System for Early Pathology Detection in Building Construction
Structure pathology detection is an important security task in building construction, which is performed by an operator by looking manually for damages on the materials. This activity could be dangerous if the structure is hidden or difficult to reach. On the other hand, embedded devices and wireless sensor networks (WSN) are becoming popular and cheap, enabling the design of an alternative pathology detection system to monitor structures based on these technologies. This article introduces a ZigBee WSN system, intending to be autonomous, easy to use and with low power consumption. Its functional parts are fully discussed with diagrams, as well as the protocol used to collect samples from sensor nodes. Finally, several tests focused on range and power consumption of our prototype are shown, analysing whether the results obtained were as expected or not
Review of sensors for remote patient monitoring
Remote patient monitoring (RPM) of physiological
measurements can provide an efficient method and high
quality care to patients. The physiological signals
measurement is the initial and the most important factor
in RPM. This paper discusses the characteristics of the
most popular sensors, which are used to obtain vital
clinical signals in prevalent RPM systems.
The sensors discussed in this paper are used to measure
ECG, heart sound, pulse rate, oxygen saturation, blood
pressure and respiration rate, which are treated as the
most important vital data in patient monitoring and
medical examination
A Review of the Enviro-Net Project
Ecosystems monitoring is essential to properly understand their development
and the effects of events, both climatological and anthropological in nature.
The amount of data used in these assessments is increasing at very high rates.
This is due to increasing availability of sensing systems and the development
of new techniques to analyze sensor data. The Enviro-Net Project encompasses
several of such sensor system deployments across five countries in the
Americas. These deployments use a few different ground-based sensor systems,
installed at different heights monitoring the conditions in tropical dry
forests over long periods of time. This paper presents our experience in
deploying and maintaining these systems, retrieving and pre-processing the
data, and describes the Web portal developed to help with data management,
visualization and analysis.Comment: v2: 29 pages, 5 figures, reflects changes addressing reviewers'
comments v1: 38 pages, 8 figure
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