4 resultados para Internet monitoring

em Universidad de Alicante


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In order to evaluate the influence of particle transport episodes on particle number concentration temporal trends at both urban and high-altitude (Aitana peak-1558 m a.s.l.) stations, a simultaneous sampling campaign from October 2011 to September 2012 was performed. The monitoring stations are located in southeastern Spain, close to the Mediterranean coast. The annual average value of particle concentration obtained in the larger accumulation mode (size range 0.25–1 μm) at the mountain site, 55.0 ± 3.0 cm− 3, was practically half that of the value obtained at the urban station (112.0 ± 4.0 cm− 3). The largest difference between both stations was recorded during December 2011 and January 2012, when particles at the mountain station registered the lowest values. It was observed that during urban stagnant episodes, particle transport from urban sites to the mountain station could take place under specific atmospheric conditions. During these transports, the major particle transfer is produced in the 0.5–2 μm size range. The minimum difference between stations was recorded in summer, particularly in July 2012, which is most likely due to several particle transport events that affected only the mountain station. The particle concentration in the coarse mode was very similar at both monitoring sites, with the biggest difference being recorded during the summer months, 0.4 ± 0.1 cm− 3 at the urban site and 0.9 ± 0.1 cm− 3 at the Aitana peak in August 2012. Saharan dust outbreaks were the main factor responsible for these values during summer time. The regional station was affected more by these outbreaks, recording values of > 4.0 cm− 3, than the urban site. This long-range particle transport from the Sahara desert also had an effect upon O3 levels measured at the mountain station. During periods affected by Saharan dust outbreaks, ozone levels underwent a significant decrease (3–17%) with respect to its mean value.

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Nowadays, the intensive use of Technology Information (TI) provide solutions to problems of the high population density, energy conservation and cities management. This produces a newest concept of the city, Smart City. But the inclusion of TI in the city brings associated new problems, specifically the generation of electromagnetic fields from the available and new technological infrastructures installed in the city that did not exist before. This new scenario produces a negative effect on a particular group of the society, as are the group of persons with electromagnetic hypersensitivity pathology. In this work we propose a system that would allow you to detect and prevent the continuous exposure to such electromagnetic fields, without the need to include more devices or infrastructure which would only worsen these effects. Through the use of the architecture itself and Smart City services, it is possible to infer the necessary knowledge to know the situation of the EMF radiation and thus allow users to avoid the areas of greatest conflict. This knowledge, not only allows us to get EMF current map of the city, but also allows you to generate predictions and detect future risk situations.

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Today, faced with the constant rise of the Smart cities around the world, there is an exponential increase of the use and deployment of information technologies in the cities. The intensive use of Information Technology (IT) in these ecosystems facilitates and improves the quality of life of citizens, but in these digital communities coexist individuals whose health is affected developing or increasing diseases such as electromagnetic hypersensitivity. In this paper we present a monitoring, detection and prevention system to help this group, through which it is reported the rates of electromagnetic radiation in certain areas, based on the information that the own Smart City gives us. This work provides a perfect platform for the generation of predictive models for detection of future states of risk for humans.

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Irrigated agriculture is usually performed in semi-arid regions despite scarcity of water resources. Therefore, optimal irrigation management by monitoring the soil is essential, and assessing soil hydraulic properties and water flow dynamics is presented as a first measure. For this purpose, the control of volumetric water content, θ, and pressure head, h, is required. This study adopted two types of monitoring strategies in the same experimental plot to control θ and h in the vadose zone: i) non-automatic and more time-consuming; ii) automatic connected to a datalogger. Water flux was modelled with Hydrus-1D using the data collected from both acquisition strategies independently (3820 daily values for the automatic; less than 1000 for the non-automatic). Goodness-of-fit results reported a better adjustment in case of automatic sensors. Both model outputs adequately predicted the general trend of θ and h, but with slight differences in computed annual drainage (711 mm and 774 mm). Soil hydraulic properties were inversely estimated from both data acquisition systems. Major differences were obtained in the saturated volumetric water content, θs, and the n and α van Genuchten model shape parameters. Saturated hydraulic conductivity, Ks, shown lower variability with a coefficient of variation range from 0.13 to 0.24 for the soil layers defined. Soil hydraulic properties were better assessed through automatic data acquisition as data variability was lower and accuracy was higher.