920 resultados para Environment monitoring


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IEEE 802.15.4 standard is a relatively new standard designed for low power low data rate wireless sensor networks (WSN), which has a wide range of applications, e.g., environment monitoring, e-health, home and industry automation. In this paper, we investigate the problems of hidden devices in coverage overlapped IEEE 802.15.4 WSNs, which is likely to arise when multiple 802.15.4 WSNs are deployed closely and independently. We consider a typical scenario of two 802.15.4 WSNs with partial coverage overlapping and propose a Markov-chain based analytical model to reveal the performance degradation due to the hidden devices from the coverage overlapping. Impacts of the hidden devices and network sleeping modes on saturated throughput and energy consumption are modeled. The analytic model is verified by simulations, which can provide the insights to network design and planning when multiple 802.15.4 WSNs are deployed closely. © 2013 IEEE.

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IEEE 802.15.4 standard is a relatively new standard designed for low power low data rate wireless sensor networks (WSN), which has a wide range of applications, e.g., environment monitoring, e-health, home and industry automation. In this paper, we investigate the problems of hidden devices in coverage overlapped IEEE 802.15.4 WSNs, which is likely to arise when multiple 802.15.4 WSNs are deployed closely and independently. We consider a typical scenario of two 802.15.4 WSNs with partial coverage overlapping and propose a Markov-chain based analytical model to reveal the performance degradation due to the hidden devices from the coverage overlapping. Impacts of the hidden devices and network sleeping modes on saturated throughput and energy consumption are modeled. The analytic model is verified by simulations, which can provide the insights to network design and planning when multiple 802.15.4 WSNs are deployed closely. © 2013 IEEE.

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Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

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Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

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This document is the Copernicus Marine Environment Monitoring Service for In Situ observations System Requirements Document (CMES-INS-SRD). It specifies the capabilities of the CMEMS-INS system as a response to the CMEMS-INS system requirements. The Copernicus In Situ Thematic Assembly Centre (In Situ TAC) provides a research and operational framework to develop and deliver In Situ observations and derived products based on such observations, to address progressively global but also regional needs either for monitoring, modelling or downstream service development.

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By employing interpretive policy analysis this thesis aims to assess, measure, and explain policy capacity for government and non-government organizations involved in reclaiming Alberta's oil sands. Using this type of analysis to assess policy capacity is a novel approach for understanding reclamation policy; and therefore, this research will provide a unique contribution to the literature surrounding reclamation policy. The oil sands region in northeast Alberta, Canada is an area of interest for a few reasons; primarily because of the vast reserves of bitumen and the environmental cost associated with developing this resource. An increase in global oil demand has established incentive for industry to seek out and develop new reserves. Alberta's oil sands are one of the largest remaining reserves in the world, and there is significant interest in increasing production in this region. Furthermore, tensions in several oil exporting nations in the Middle East remain unresolved, and this has garnered additional support for a supply side solution to North American oil demands. This solution relies upon the development of reserves in both the United States and Canada. These compounding factors have contributed to the increased development in the oil sands of northeastern Alberta. Essentially, a rapid expansion of oil sands operations is ongoing, and is the source of significant disturbance across the region. This disturbance, and the promises of reclamation, is a source of contentious debates amongst stakeholders and continues to be highly visible in the media. If oil sands operations are to retain their social license to operate, it is critical that reclamation efforts be effective. One concern non-governmental organizations (NGOs) expressed criticizes the current monitoring and enforcement of regulatory programs in the oil sands. Alberta's NGOs have suggested the data made available to them originates from industrial sources, and is generally unchecked by government. In an effort to discern the overall status of reclamation in the oil sands this study explores several factors essential to policy capacity: work environment, training, employee attitudes, perceived capacity, policy tools, evidence based work, and networking. Data was collected through key informant interviews with senior policy professionals in government and non-government agencies in Alberta. The following are agencies of interest in this research: Canadian Association of Petroleum Producers (CAPP); Alberta Environment and Sustainable Resource Development (AESRD); Alberta Energy Regulator (AER); Cumulative Environmental Management Association (CEMA); Alberta Environment Monitoring, Evaluation, and Reporting Agency (AEMERA); Wood Buffalo Environmental Association (WBEA). The aim of this research is to explain how and why reclamation policy is conducted in Alberta's oil sands. This will illuminate government capacity, NGO capacity, and the interaction of these two agency typologies. In addition to answering research questions, another goal of this project is to show interpretive analysis of policy capacity can be used to measure and predict policy effectiveness. The oil sands of Alberta will be the focus of this project, however, future projects could focus on any government policy scenario utilizing evidence-based approaches.

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The requirement to monitor the rapid pace of environmental change due to global warming and to human development is producing large volumes of data but placing much stress on the capacity of ecologists to store, analyse and visualise that data. To date, much of the data has been provided by low level sensors monitoring soil moisture, dissolved nutrients, light intensity, gas composition and the like. However, a significant part of an ecologist’s work is to obtain information about species diversity, distributions and relationships. This task typically requires the physical presence of an ecologist in the field, listening and watching for species of interest. It is an extremely difficult task to automate because of the higher order difficulties in bandwidth, data management and intelligent analysis if one wishes to emulate the highly trained eyes and ears of an ecologist. This paper is concerned with just one part of the bigger challenge of environmental monitoring – the acquisition and analysis of acoustic recordings of the environment. Our intention is to provide helpful tools to ecologists – tools that apply information technologies and computational technologies to all aspects of the acoustic environment. The on-line system which we are building in conjunction with ecologists offers an integrated approach to recording, data management and analysis. The ecologists we work with have different requirements and therefore we have adopted the toolbox approach, that is, we offer a number of different web services that can be concatenated according to need. In particular, one group of ecologists is concerned with identifying the presence or absence of species and their distributions in time and space. Another group, motivated by legislative requirements for measuring habitat condition, are interested in summary indices of environmental health. In both case, the key issues are scalability and automation.

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Knowledge of cable parameters has been well established but a better knowledge of the environment in which the cables are buried lags behind. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Results based on long term continuous field data are given. A probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. This data from field studies can reduce the risk in cable rating decisions and provide a basis for reliable prediction of “hot spot” of an existing cable circuit

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Government action is essential to increase the healthiness of food environments and reduce obesity, diet-related non-communicable diseases (NCDs), and their related inequalities. This paper proposes a monitoring framework to assess government policies and actions for creating healthy food environments. Recommendations from relevant authoritative organizations and expert advisory groups for reducing obesity and NCDs were examined, and pertinent components were incorporated into a comprehensive framework for monitoring government policies and actions. A Government Healthy Food Environment Policy Index (Food-EPI) was developed, which comprises a ‘policy’ component with seven domains on specific aspects of food environments, and an ‘infrastructure support’ component with seven domains to strengthen systems to prevent obesity and NCDs. These were revised through a week-long consultation process with international experts. Examples of good practice statements are proposed within each domain, and these will evolve into benchmarks established by governments at the forefront of creating and implementing food policies for good health. A rating process is proposed to assess a government's level of policy implementation towards good practice. The Food-EPI will be pre-tested and piloted in countries of varying size and income levels. The benchmarking of government policy implementation has the potential to catalyse greater action to reduce obesity and NCDs.

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This report describes results and conclusions from the monitoring component of the Douglas Shire Council (DSC) water quality project. The components of this project that this report addresses are: • Site selection and installation of in-stream and off-paddock automatic water quality monitoring equipment in the Douglas Shire. • Design of appropriate sampling strategies for automatic stations. • Estimation of loads of suspended sediment, total nitrogen and total phosphorus in rivers and also estimation of the changes in nutrient loads from sugar cane under different fertilizer application rates. • Development of a community-based water quality sampling program to complement the automatic sampling efforts. • Design of an optimised, long-term water quality monitoring strategy.

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As there are a myriad of micro organic pollutants that can affect the well-being of human and other organisms in the environment the need for an effective monitoring tool is eminent. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing time-integrated load as well as representative average of concentrations of pollutants in the environment. Those techniques have been applied to monitor many pollutants caused by agricultural activities, i.e. residues of pesticides, veterinary drugs and so on. Several types of passive samplers are commercially available and their uses are widely accepted. However, not many applications of those techniques have been found in Japan, especially in the field of agricultural environment. This paper aims to introduce the field of passive sampling and then to describe some applications of passive sampling techniques in environmental monitoring studies related to the agriculture industry.

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The micro paddy lysimeter (MPL) was developed and evaluated for its performance to simulate solute transport in paddy environment under laboratory conditions. MPLs were constructed using soil collected from Field Museum Honmachi of Tokyo University of Agriculture and Technology, Japan. For the physical characteristics of the hardpan layer, parameters such as thickness, and soil aggregate size, affecting the percolation rate were studied. For the plow layer, two types of plow soils, sieved and un-sieved soils were compared. The sieved soil plow layer was produced by mixing air-dried soils of different aggregate sizes of D > 9.50, 9.50 ≥ D > 4.75, 4.75 ≥ D > 2.0 mm and D ≤ 2.0 mm at 47.1, 19.5, 20.6, and 12.8%, respectively. The un-sieved plow layer soil was directly used after collecting from the field. Inert tracer was applied to ponding water with controlled boundary conditions to evaluate the reproducibility of the soil hydraulic characteristics. HYDRUS-1D was used to evaluate the movement of bromide tracer in the MPL. The proposed conditions of the MPL were that the hardpan layer can be made from soil aggregates smaller than 0.425 mm with 2 cm thickness and that the plow layer can be prepared with sieved or un-sieved soils. With these conditions, the obtained results proved that MPLs can be a useful tool to simulate solute transport in paddy environment.

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The Alliance for Coastal Technologies (ACT) convened a workshop on Evaluating Approaches and Technologies for Monitoring Organic Contaminants in the Aquatic Environment in Ann Arbor, MI on July 21-23, 2006. The primary objectives of this workshop were to: 1) identify the priority management information needs relative to organic contaminant loading; 2) explore the most appropriate approaches to estimating mass loading; and 3) evaluate the current status of the sensor technology. To meet these objectives, a mixture of leading research scientists, resource managers, and industry representatives were brought together for a focused two-day workshop. The workshop featured four plenary talks followed by breakout sessions in which arranged groups of participants where charged to respond to a series of focused discussion questions. At present, there are major concerns about the inadequacies in approaches and technologies for quantifying mass emissions and detection of organic contaminants for protecting municipal water supplies and receiving waters. Managers use estimates of land-based contaminant loadings to rivers, lakes, and oceans to assess relative risk among various contaminant sources, determine compliance with regulatory standards, and define progress in source reduction. However, accurately quantifying contaminant loading remains a major challenge. Loading occurs over a range of hydrologic conditions, requiring measurement technologies that can accommodate a broad range of ambient conditions. In addition, in situ chemical sensors that provide a means for acquiring continuous concentration measurements are still under development, particularly for organic contaminants that typically occur at low concentrations. Better approaches and strategies for estimating contaminant loading, including evaluations of both sampling design and sensor technologies, need to be identified. The following general recommendations were made in an effort to advance future organic contaminant monitoring: 1. Improve the understanding of material balance in aquatic systems and the relationship between potential surrogate measures (e.g., DOC, chlorophyll, particle size distribution) and target constituents. 2. Develop continuous real-time sensors to be used by managers as screening measures and triggers for more intensive monitoring. 3. Pursue surrogate measures and indicators of organic pollutant contamination, such as CDOM, turbidity, or non-equilibrium partitioning. 4. Develop continuous field-deployable sensors for PCBs, PAHs, pyrethroids, and emerging contaminants of concern and develop strategies that couple sampling approaches with tools that incorporate sensor synergy (i.e., measure appropriate surrogates along with the dissolved organics to allow full mass emission estimation).[PDF contains 20 pages]