scholarly journals Implementation of a Radon Monitoring Network in a Seismic Area

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1041
Author(s):  
Victorin-Emilian Toader ◽  
Andrei Mihai ◽  
Iren-Adelina Moldovan ◽  
Constantin Ionescu ◽  
Alexandru Marmureanu ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Sampling Rate ◽  
Region Of Interest ◽  
Monitoring Network ◽  
Geological Structure ◽  
Reference Level ◽  
Seismic Area ◽  
Radon Monitoring

Large-scale radon monitoring is carried out due to the fact that it is directly responsible for public health. European Directive 2013/59/EURATOM has been transposed into the legislation of several countries and provides for the need for long-term monitoring of radon in homes and workplaces by setting the average annual reference level at 300 Bq/m3. At the same time, radon is a precursor factor, its emission being correlated with seismic and volcanic activity. In this case, the protection of the population is ensured by a forecast similar to a meteorological one. The NIEP (National Institute for Earth Physics) is developing a multidisciplinary real-time monitoring network in the most dangerous seismic area in Romania, Vrancea. This is located at the bend of the Carpathian Mountains and is characterized by deep earthquakes (over 80 km), with destructive effects over large distances. Implementing a multidisciplinary monitoring network that includes radon, involves finding the locations and equipment that will give the best results. There is no generic solution for achieving this, because the geological structure depends on the monitoring area, and in most cases the equipment does not offer the ability to transmit data in real time. The positioning of the monitoring stations was based on fault maps of the Vrancea area. Depending on the results, some of the locations were changed in pursuit of a correlation with zonal seismicity. Through repeated tests, we established the optimal sampling rate for minimizing errors, maintaining measurement accuracy, and ensuring the detection of anomalies in real time. The radon 222Rn was determined by the number of counts and ROI1 (region of interest) values, depending on the particularities of the equipment. Finally, we managed to establish a real-time radon monitoring network which transmits data to geophysical platforms and makes correlations with the seismicity in the Vrancea area. The equipment, designed to store data for long periods of time then manually download it with manufacturers’ applications, now works in real time, after we implemented software designed specifically for this purpose.

scholarly journals InSight2: A Modular Visual Analysis Platform for Network Situational Awareness in Large-Scale Networks

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1747
Author(s):  
Hansaka Angel Dias Edirisinghe Kodituwakku ◽  
Alex Keller ◽  
Jens Gregor
Keyword(s):  
Real Time ◽  
Computer Networks ◽  
Network Flow ◽  
Large Scale ◽  
Visual Analysis ◽  
Situational Awareness ◽  
Monitoring Network ◽  
Network Activity ◽  
Flow Data ◽  
Large Scale Networks

The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection.

scholarly journals The role of technical elements of digitalization in the development of modern animal farming

2021 ◽  
Vol 7 (Special) ◽  
pp. 10-10
Author(s):  
Alexey Shemetov ◽  
◽  
Andrey Ivanov
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Large Scale ◽  
Sampling Rate ◽  
Digital Technologies ◽  
Animal Husbandry ◽  
Machine Learning Algorithms ◽  
Detection Methods ◽  
Animal Products ◽  
Technical Problems

It is estimated that farmers need to increase production by 70% over the next 50 years to meet the growing global demand for meat and animal products [1]. Since land and other natural resources are limited, more efficient ways of raising more animals per hectare of land will need to be found to meet this growing demand. Today, most animal husbandry methods require manual intervention at some level. This affects production productivity. Previously, digital technologies were expensive and could not be applied on a large scale. Today, sensors, big data, and machine learning algorithms have significant cost advantages over these older detection methods. Currently, the sensors offered by the market are significantly limited in reliable forecasting and disease management in animal husbandry due to continuous automated monitoring in real time. In addition, there are certain technical problems, such as the location of the sensors, what the sampling rate will be, and how the data will be transmitted. All of these considerations affect the accuracy of the algorithms, as well as the scalability and practicality of a solution that ultimately can be used on a livestock farm. In real-time systems, large feature sets can be problematic due to computational complexity and higher storage requirements. In light of the still existing pandemic, when restrictions prevent veterinarians and producers from visiting farms, cowsheds and feed mills (but there is a need for 24/7 information on activities, consumption and production of products in real time), then the current and practically only possible solution is the introduction of digital technologies. Keywords: LIVESTOCK, SMART FARMING, SENSORS, SENSORS, MACHINE LEARNING

scholarly journals The Italian TREETALKER NETWORK (ITT-Net): continuous large scale monitoring of tree functional traits and vulnerabilities to climate change

2020 ◽  
Author(s):  
Simona Castaldi ◽  
Serena Antonucci ◽  
Shahla Asgharina ◽  
Giovanna Battipaglia ◽  
Luca Belelli Marchesini ◽  
...  
Keyword(s):  
Climate Change ◽  
Real Time ◽  
High Frequency ◽  
Large Scale ◽  
Operation Mode ◽  
Cloud Services ◽  
Long Term Monitoring ◽  
The Impact ◽  
Term Monitoring

<p>The  <strong>Italian TREETALKER NETWORK (ITT-Net) </strong>aims to respond to one of the grand societal challenges: the impact of climate changes on forests ecosystem services and forest dieback. The comprehension of the link between these phenomena requires to complement the most classical approaches with a new monitoring paradigm based on large scale, single tree, high frequency and long-term monitoring tree physiology, which, at present, is limited by the still elevated costs of multi-sensor devices, their energy demand and maintenance not always suitable for monitoring in remote areas. The ITT-Net network will be a unique and unprecedented worldwide example of real time, large scale, high frequency and long-term monitoring of tree physiological parameters. By spring 2020, as part of a national funded project (PRIN) the network will have set 37 sites from the north-east Alps to Sicily where a new low cost, multisensor technology “the TreeTalker®” equipped to measure tree radial growth, sap flow, transmitted light spectral components related to foliage dieback and physiology and plant stability (developed by Nature 4.0), will monitor over 600 individual trees. A radio LoRa protocol for data transmission and access to cloud services will allow to transmit in real time high frequency data on the WEB cloud with a unique IoT identifier to a common database where big data analysis will be performed to explore the causal dependency of climate events and environmental disturbances with tree functionality and resilience.</p><p>With this new network, we aim to create a new knowledge, introducing a massive data observation and analysis, about the frequency, intensity and dynamical patterns of climate anomalies perturbation on plant physiological response dynamics in order to: 1) characterize the space of “normal or safe tree operation mode” during average climatic conditions; 2) identify the non-linear tree responses beyond the safe operation mode, induced by extreme events, and the tipping points; 3) test the possibility to use a high frequency continuous monitoring system to identify early warning signals of tree stress which might allow to follow tree dynamics under climate change in real time at a resolution and accuracy that cannot always be provided through forest inventories or remote sensing technologies.</p><p>To have an overview of the ITT Network you can visit www.globaltreetalker.org</p><p> </p>

scholarly journals Italian Radon mOnitoring Network (IRON): A permanent network for near real-time monitoring of soil radon emission in Italy

2018 ◽  
Vol 61 (Vol 61 (2018)) ◽  
Author(s):  
Valentina Cannelli ◽  
Antonio Piersanti ◽  
Gianfranco Galli ◽  
Daniele Melini
Keyword(s):  
Real Time ◽  
Monitoring Network ◽  
Real Time Monitoring ◽  
Soil Radon ◽  
Radon Emission ◽  
Radon Monitoring

Operational modal analysis of a multi-span skew bridge using real-time wireless sensor networks

2010 ◽  
Vol 17 (13) ◽  
pp. 1952-1963 ◽  
Author(s):  
MJ Whelan ◽  
MV Gangone ◽  
KD Janoyan ◽  
R Jha
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Sampling Rate ◽  
Sensor Data ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Radio Waves ◽  
Operational Mode ◽  
Ambient Vibration Testing ◽  
Output Only

A large-scale field deployment of high-density, real-time wireless sensors networks for the acquisition of local acceleration measurements across a medium length, multi-span highway bridge is presented. The advantages, performance characteristics, and limitations of employing this emerging technology in favor of the traditional cable-based acquisition systems are discussed in the context of the in-service instrumentation and ambient vibration testing of a multi-span bridge. Of particular highlight in this study is the deployment of a large number of stationary rather than reference-based accelerometers to uniquely permit simultaneous acquisition of vibration measurements across the structure and thereby ensure consistent temperature, ambient vibration, and traffic loading. The deployment consisted of 30 dual-axis accelerometers installed across the girders of the bridge and interfaced with 30 wireless acquisition and transceiver nodes operating in two star topology networks. Real-time wireless acquisition at a per channel sampling rate of 128 samples per second was maintained across both networks for the specified test durations of 3 min with insignificant data loss. Output-only system identification of the structure from the experimental data is presented to provide estimates of natural frequencies, damping ratios, and operational mode shapes for 19 modes. The analysis of the structure under test provides a unique case study documenting the measured response of a multiple-span skewed bridge supported by elastomeric bearings. The feasibility of embedded wireless instrumentation for structural health monitoring of large civil constructions is concluded while highlighting relevant technological shortcomings and areas of further development required. In particular, previously undocumented obstacles relating to radio transmission of the sensor data using low-power 2.4 GHz wireless instrumentation, such as the effect of solid piers within the line-of-sight and the reflection of the radio waves on the surface of the water, are discussed.

How Performance Management Must Change to Drive Organizational Agility and High Performance

2020 ◽  
pp. 211-232
Author(s):  
Elaine D. Pulakos ◽  
Tracy Kantrowitz
Keyword(s):  
Performance Management ◽  
Real Time ◽  
High Performance ◽  
Large Scale ◽  
Organizational Agility ◽  
Organizational Conditions ◽  
Performance Drivers ◽  
Definition Of ◽  
Design And Practice

This chapter focuses on implications of the changing work environment for performance management (PM) design and practice. The chapter begins by discussing how technology has created disruptive change and hypercompetition, which have left organizations searching for how to create competitive advantage, concluding that agility is essential for their long-term success. Given the limited research in this area, a large-scale research program was undertaken (as described in the first part of this chapter) to provide an evidence-based definition of agility and to understand what organizational conditions lead to it and which outcomes result from it. The research showed, remarkably, that companies with high organizational agility delivered up to five times higher financial performance than others. It was learned that six organizational conditions enabled agility, two of which were team-level factors that are particularly relevant for PM. These were interconnected performance and real-time performance drivers (i.e., agile goals, real-time feedback, and solving performance problems). In the second part of this chapter, implications of these factors for PM design and practice are discussed.

scholarly journals The challenge of sensor selection, long term-sensor operation and data evaluation in inter- -institutional long term monitoring projects (lessons learned in the MOSES project)

2020 ◽  
Author(s):  
Philipp Fischer ◽  
Madlen Friedrich ◽  
Markus Brand ◽  
Uta Koedel ◽  
Peter Dietrich ◽  
...  
Keyword(s):  
Environmental Variables ◽  
Large Scale ◽  
Low Cost ◽  
Monitoring Network ◽  
Research Field ◽  
Lessons Learned ◽  
Environmental Data ◽  
The North ◽  
Accuracy And Precision

<p>Measuring environmental variables over longer times in coastal marine environments is a challenge in regard to sensor maintenance and data processing of continuously produced comprehensive datasets. In the project “MOSES” (Modular Observation Solutions for Earth Systems), this procedure became even more complicated because seven large Helmholtz centers from the research field Earth and Environment (E&E) within the framework of the German Ministery of Educatiopn and Research (BMBF) work together to design and construct a large scale monitoring network across earth compartments to study the effects of short-term events on long term environmental trends. This requires the development of robust and standardized automated data acquisition and processing routines, to ensure reliable, accure and precise data.</p><p>Here, the results of two intercomparison workshops on senor accuracy and precicion for selected environmental variables are presented. Environmental sensors which were to be used in MOSES campaigns on hydrological extremes (floods and draughts) in the Elbe catchment and the adjacent coastal areas in the North Sea in 2019 to 2020 were compared for selected parameters (temperature, salinity, chlorophyll-A, turbidity and methane) in the same experimentally controlled water body, assuming that all sensors provide comparable data. Results were analyzed with respect to individual sensor accuracy and precision related to an “assumed” real value as well as with respect to a cost versus accuracy/precision index for measuring specific environmental data. The results show, that accuracy and precision of sensors do not necessarily correlate with the price of the sensors and that low cost sensors may provide the same or even higher accuracy and precision values as even the highest price sensor types.</p>

scholarly journals SAFE Acoustics: an open-source, real-time eco-acoustic monitoring network in the tropical rainforests of Borneo

2020 ◽  
Author(s):  
Sarab S. Sethi ◽  
Robert M. Ewers ◽  
Nick S. Jones ◽  
Aaron Signorelli ◽  
Lorenzo Picinali ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Large Scale ◽  
Monitoring Network ◽  
Ecological Monitoring ◽  
Acoustic Monitoring ◽  
Sensor Technology ◽  
Tropical Rainforests ◽  
List Type ◽  
Monitoring Networks

AbstractAutomated monitoring approaches offer an avenue to deep, large-scale insight into how ecosystems respond to human pressures. Since sensor technology and data analyses are often treated independantly, there are no open-source examples of end-to-end, real-time ecological monitoring networks.Here, we present the complete implementation of an autonomous acoustic monitoring network deployed in the tropical rainforests of Borneo. Real-time audio is uploaded remotely from the field, indexed by a central database, and delivered via an API to a public-facing website.We provide the open-source code and design of our monitoring devices, the central web2py database and the ReactJS website. Furthermore, we demonstrate an extension of this infrastructure to deliver real-time analyses of the eco-acoustic data.By detailing a fully functional, open-source, and extensively tested design, our work will accelerate the rate at which fully autonomous monitoring networks mature from technological curiosities, and towards genuinely impactful tools in ecology.

Evolution of Large-Scale Coronal Structures

1994 ◽  
Vol 144 ◽  
pp. 29-33
Author(s):  
P. Ambrož
Keyword(s):  
Magnetic Field ◽  
Field Line ◽  
Large Scale ◽  
Coronal Magnetic Field ◽  
Source Surface ◽  
Solar Cycles ◽  
Characteristic Relationship ◽  
The Magnetic Field ◽  
Coronal Structures

AbstractThe large-scale coronal structures observed during the sporadically visible solar eclipses were compared with the numerically extrapolated field-line structures of coronal magnetic field. A characteristic relationship between the observed structures of coronal plasma and the magnetic field line configurations was determined. The long-term evolution of large scale coronal structures inferred from photospheric magnetic observations in the course of 11- and 22-year solar cycles is described.Some known parameters, such as the source surface radius, or coronal rotation rate are discussed and actually interpreted. A relation between the large-scale photospheric magnetic field evolution and the coronal structure rearrangement is demonstrated.

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