997 resultados para Persistent Monitoring


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Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

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Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

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Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

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Persistent monitoring of the ocean is not optimally accomplished by repeatedly executing a fixed path in a fixed location. The ocean is dynamic, and so should the executed paths to monitor and observe it. An open question merging autonomy and optimal sampling is how and when to alter a path/decision, yet achieve desired science objectives. Additionally, many marine robotic deployments can last multiple weeks to months; making it very difficult for individuals to continuously monitor and retask them as needed. This problem becomes increasingly more complex when multiple platforms are operating simultaneously. There is a need for monitoring and adaptation of the robotic fleet via teams of scientists working in shifts; crowds are ideal for this task. In this paper, we present a novel application of crowd-sourcing to extend the autonomy of persistent-monitoring vehicles to enable nonrepetitious sampling over long periods of time. We present a framework that enables the control of a marine robot by anybody with an internet-enabled device. Voters are provided current vehicle location, gathered science data and predicted ocean features through the associated decision support system. Results are included from a simulated implementation of our system on a Wave Glider operating in Monterey Bay with the science objective to maximize the sum of observed nitrate values collected.

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Water to air methane emissions from freshwater reservoirs can be dominated by sediment bubbling (ebullitive) events. Previous work to quantify methane bubbling from a number of Australian sub-tropical reservoirs has shown that this can contribute as much as 95% of total emissions. These bubbling events are controlled by a variety of different factors including water depth, surface and internal waves, wind seiching, atmospheric pressure changes and water levels changes. Key to quantifying the magnitude of this emission pathway is estimating both the bubbling rate as well as the areal extent of bubbling. Both bubbling rate and areal extent are seldom constant and require persistent monitoring over extended time periods before true estimates can be generated. In this paper we present a novel system for persistent monitoring of both bubbling rate and areal extent using multiple robotic surface chambers and adaptive sampling (grazing) algorithms to automate the quantification process. Individual chambers are self-propelled and guided and communicate between each other without the need for supervised control. They can maintain station at a sampling site for a desired incubation period and continuously monitor, record and report fluxes during the incubation. To exploit the methane sensor detection capabilities, the chamber can be automatically lowered to decrease the head-space and increase concentration. The grazing algorithms assign a hierarchical order to chambers within a preselected zone. Chambers then converge on the individual recording the highest 15 minute bubbling rate. Individuals maintain a specified distance apart from each other during each sampling period before all individuals are then required to move to different locations based on a sampling algorithm (systematic or adaptive) exploiting prior measurements. This system has been field tested on a large-scale subtropical reservoir, Little Nerang Dam, and over monthly timescales. Using this technique, localised bubbling zones on the water storage were found to produce over 50,000 mg m-2 d-1 and the areal extent ranged from 1.8 to 7% of the total reservoir area. The drivers behind these changes as well as lessons learnt from the system implementation are presented. This system exploits relatively cheap materials, sensing and computing and can be applied to a wide variety of aquatic and terrestrial systems.

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This paper documents the design, implementation and characterisation of a wireless sensor node (GENESI Node v1.0), applicable to long-term structural health monitoring. Presented is a three layer abstraction of the hardware platform; consisting of a Sensor Layer, a Main Layer and a Power Layer. Extended operational lifetime is one of the primary design goals, necessitating the inclusion of supplemental energy sources, energy awareness, and the implementation of optimal components (microcontroller(s), RF transceiver, etc.) to achieve lowest-possible power consumption, whilst ensuring that the functional requirements of the intended application area are satisfied. A novel Smart Power Unit has been developed; including intelligence, ambient available energy harvesting (EH), storage, electrochemical fuel cell integration, and recharging capability, which acts as the Power Layer for the node. The functional node has been prototyped, demonstrated and characterised in a variety of operational modes. It is demonstrable via simulation that, under normal operating conditions within a structural health monitoring application, the node may operate perpetually.

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Most persistent organic pollutants (POPs) like polychlorinated biphenyls (PCBs), a range of polybrominated diphenyl ethers (PBDEs) and organochlorine pesticides (OCPs) are readily absorbed (via the ingestion and inhalation) and accumulate in fatty tissue, including adipose tissue and human milk [1]. Health effects related to exposure to these chemicals may include neurological effects, altered functioning of the nervous system and/or endocrine disruption [2-4]. The burden of environmental disease is recognized as much higher for children than adults, especially in young children under 5 years of age worldwide [5]. There is increased concern regarding the environmental impact on the health of children who have been disproportionately affected by environmental problems. For example they may be subjected to relatively higher exposure, have greater physiological susceptibility and/or suffer more extreme consequences due to growth [6-9]. It is therefore worthwhile to assess the correlation between burden of disease and exposure to xenobiotic chemical pollutants like POPs. Such assessment may provide guidance for legislative changes regarding chemical bans and give reliable advice to parents including lactating mothers.

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Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

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Persistent organic pollutants (POPs) including polybrominated diphenyl ethers (PBDEs); organochlorine pesticides (OCPs); and polychlorinated biphenyls (PCBs) persist in the environment, bioaccumulate, and pose a risk of causing adverse human health effects. Typically, exposure assessments undertaken by modeling existing intake data underestimate the concentrations of these chemicals in infants. This study aimed to determine concentrations of POPs in infant foods, assess exposure via dietary intake and compare this to historical exposure. Fruit purees, meat and vegetables, dairy desserts, cereals and jelly foods (n = 33) purchased in 2013 in Brisbane, Australia were analyzed. For OCPs and PCBs, concentrations ranged up to 95 pg/g fw and for PBDEs up to 32 pg/g fw with most analytes below the limit of detection. Daily intake is dependent on type and quantity of foods consumed. Consumption of a 140 g meal would result in intake ranging from 0 to 4.2 ng/day, 4.4 ng/day and 13.3 ng/day, for OCPs, PBDEs and PCBs, respectively. PBDEs were detected in 3/33 samples, OCPs in 9/33 samples and PCBs in 13/33 samples. Results from this study indicate exposure for infants via dietary (in contrast to dust and breast milk) intake in Australia contribute only a minor component to total exposure.

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Assessing blood concentration of persistent organic pollutants (POPs) in infants is difficult due to the ethical and practical difficulties in obtaining sufficient quantities of blood. To determine whether measuring POPs in faeces might reflect blood concentration during infancy, we measured the concentrations of a range of POPs (i.e. polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and organochlorine pesticides (OCPs)) in a pilot study using matched breast milk and infant faecal samples obtained from ten mother-child pairs. All infants were breast fed, with 8 of them also receiving solid food at the time of faecal sampling. In this small dataset faecal concentrations (range 0.01-41ngg-1 lipid) are strongly associated with milk concentrations (range 0.02-230ngg-1 lipid). Associations with other factors generally could not be detected in this dataset, with the exception of a small effect of age or growth. Different sources (external or internal) of exposure appeared to directly influence faecal concentrations of different chemicals based on different inter-individual variability in the faeces-to-milk concentration ratio Rfm. Overall, the matrix of faeces as an external measure of internal exposure in infants looks promising for some chemicals and is worth assessing further in larger datasets.

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This is the Water Quality Monitoring in the Mersey Estuary report produced by the Environment Agency in 2001. This report focuses on the Water Quality Monitoring Programme held in the Mersey Estuary. Since the mid-1960s water samples have been collected at approximately monthly intervals along the length of the estuary between Warrington and New Brighton and in later years further off-shore. This data-set provides an invaluable resource to determine how the very large capital spending of recent years has resulted in the dramatic improvements in water quality that we are now able to record. Initially, the interest was focused on parameters such as dissolved oxygen, BOD, nutrients and suspended solids. Over the last decades, as analytical methods have improved, toxic metals and persistent organic compounds have been included in the routine monitoring programme at a limited number of sites. Moreover, with the introduction of the European Water Framework Directive monitoring programmes it was an opportune time to review the Mersey monitoring strategy. This revised monitoring programme required data from several other components (water, sediments, flora, fauna, fish and birds. This report also contains information about Routine monthly surveys, Special surveys, Chloralkali Directive, UKNMP, British Geological Survey, EDMAR and NERC Environmental Diagnostics Thematic Programme.

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The National Status and Trends (NS&T) Program has conducted studies to determine the spatial extent and severity of chemical contamination and associated adverse biological effects in coastal bays and estuaries of the United States since 1991. Sediment contamination in U.S. coastal areas is a major environmental issue because of its potential toxic effects on biological resources and often, indirectly, on human health. Thus, characterizing and delineating areas of sediment contamination and toxicity and demonstrating their effect(s) on benthic living resources are therefore important goals of coastal resource management at NOAA. The National Centers for Coastal Ocean Science, and the Office of National Marine Sanctuaries, in cooperation with the U.S. Geological Survey (USGS), University of California Moss Landing Marine Lab (MLML), and the Monterey Bay Aquarium Research Institute (MBARI), conducted ecosystem monitoring and characterization studies within and between marine sanctuaries along the California coast in 2002 and 2004 on the NOAA RV McArthur. One of the objectives was to perform a systematic assessment of the chemical and physical habitats and associated biological communities in soft bottom habitats on the continental shelf and slope in the central California region. This report addresses the magnitude and extent of chemical contamination, and contaminant transport patterns in the region. Ongoing studies of the benthic community are in progress and will be reported in an integrated assessment of habitat quality and the parameters that govern natural resource distributions on the continental margin and in canyons in the region.

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Persistent bioaccumulative toxins (PBTs) are organic substances that are persistent, bioaccumulative and can cause severe toxic effects (e.g. potential oncogens, mutagenic, endocrine disrupters) to human health or environment which are the ones that need special attention. PBT chemicals could be released to the environment from several types of sources and are ubiquitous in environment. However, fast and efficiency monitoring and assessment methods to investigate PBTs in environment are still lacking. In this study, a cleaning-up procedure of analyzing PBTs in fuels combustion soot was developed and its performance was assessed through comparing the chromatograms of crude extracts with their cleaned extracts after the cleaning-up procedure. The results showed that polycyclic aromatic compounds (PACs) were the main components in fuel combustion soot and the clean-up procedure developed in this paper can be well used as the method of analyzing PBTs in fuels combustion soot.

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We used polyurethane foam units (PFUs) to collect persistent organic pollutants (POPs) from four sites in Baiyangdian Lake in July 2003. Following extraction from the PFUs, relative concentrations of seven organochlorine pesticides (OCPs) and ten polychlorinated biphenyls (PCBs) were determined by gas chromatography. OCPs and PCBs were detected in the microbial communities from all the four sampling stations. In terms of the total concentration of POPs (OCPs+ PCBs), two river estuary stations had more POP (18.45 mu g/L and 9.77 mu g/L) than the two mid-lake stations (4.75 mu g/L and 5.21 mu g/L), indicating that Baiyangdian Lake was significantly impacted by inflow from the Fu River and Baigou River.

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The number of variables involved in the monitoring of an ecosystem can be high and often one of the first stages in the analysis is to reduce the number of variables. We describe a method developed for geological purposes, using the information theory, that enables selection of the most relevant variables. This technique also allows the examination of the asymmetrical relationships between variables. Applied to a set of physical and biological variables (plankton assemblages in four areas of the North Sea), the method shows that biological variables are more informative than physical variables although the controlling factors are mainly physical (sea surface temperature in winter and spring). Among biological variables, diversity measures and warm-water species assemblages are informative for the state of the North Sea pelagic ecosystems while among physical variables sea surface temperature in late winter and early spring are highly informative. Although often used in bioclimatology, the utilisation of the North Atlantic Oscillation (NAO) index does not seem to provide a lot of information. The method reveals that only the extreme states of this index has an influence on North Sea pelagic ecosystems. The substantial and persistent changes that were detected in the dynamic regime of the North Sea ecosystems and called regime shift are detected by the method and corresponds to the timing of other shifts described in the literature for some European Systems such as the Baltic and the Mediterranean Sea when both physical and biological variables are considered.