Mobile Vehicle-Borne Environmental Monitoring Based on Environmental Multi-Sensor Integration

2014 ◽  
Vol 522-524 ◽  
pp. 38-43
Author(s):  
Nan Yang ◽  
Zhen Feng Shao ◽  
Lei Zhang
Keyword(s):  
Environmental Monitoring ◽  
Spatial Data ◽  
Disaster Response ◽  
High Efficiency ◽  
Environmental Parameters ◽  
Development Trend ◽  
Quantitative Model ◽  
Environmental Data ◽  
Multiple Sensors ◽  
Mobile Vehicle

Environmental monitoring is increasingly playing a significant role in such aspects as environment protection, emergency disaster response and rescue, and macro decision-making etc. However, the intrinsic characteristics of complexity and spatial-temporal diversity, multi-scale features and heterogeneity brought from various means of data acquisition make the integration of multi-source data with high-efficiency becomes an international challenge nowadays. In this paper, the design and implementation of a vehicle-borne platform based on Internet of Things for environmental monitoring has been achieved. And then, by merging and matching environmental data and spatial data, more intensive multi-source environmental parameters and information can be obtained to act as meaningful supplementation of fixed environmental monitoring stations. The research of this paper is conductive to the transition of environmental monitoring from static methods to dynamic methods and from a small amount of data-based empirical model to sensor network-based quantitative model. Mobile environmental monitoring platform integrating with multiple sensors that can make environmental monitoring more timely, dynamic, integrated and intelligent will be the beneficial attempt and the development trend.

Design and Implementation of Mobile Monitoring System for Environmental Monitoring

2013 ◽  
Vol 295-298 ◽  
pp. 933-939 ◽  
Author(s):  
Zhen Feng Shao ◽  
Cheng Jing ◽  
Jia Chen ◽  
Lin Ding ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Environmental Monitoring ◽  
Spatial Data ◽  
Disaster Response ◽  
High Efficiency ◽  
Environmental Parameters ◽  
Quantitative Model ◽  
Environmental Data ◽  
Environment Monitoring ◽  
Multi Scale ◽  
Design And Implementation

Environmental monitoring is increasingly playing a significant role in such aspects as environment protection, emergency disaster response and rescue, and macro decision-making etc. However, the intrinsic characteristics of complexity and spatial-temporal diversity, multi-scale features and heterogeneity brought from various means of data acquisition make the integration of multi-source data with high-efficiency becomes an international challenge nowadays. In this paper, the design and implementation of a vehicle-borne platform based on Internet of Things for environmental monitoring has been achieved. And then, by merging and matching environmental data and spatial data, more intensive multi-source environmental parameters and information can be obtained to act as meaningful supplementation of fixed environment monitoring stations. The research of this paper is conductive to the transition of environment monitoring from static methods to dynamic methods and from data-based empirical model to sensor network-based quantitative model. As a result, current environment monitoring will become more timely, dynamic, integrated and intelligent.

scholarly journals Automated environmental monitoring and database management: Fantasies and realities

1999 ◽  
Vol 75 (3) ◽  
pp. 483-486
Author(s):  
R. A. Benton ◽  
K. M. Pettersen
Keyword(s):  
Environmental Monitoring ◽  
System Design ◽  
Monitoring System ◽  
Database Management ◽  
Environmental Parameters ◽  
Lessons Learned ◽  
Environmental Data ◽  
Monitoring Networks ◽  
Environmental Monitoring System ◽  
Wide Range

Modern dataloggers and the ever-increasing number of sensors can measure a wide range of environmental parameters, from air temperature and relative humidity through energy flux density, in minute detail and summarize the data for you at any interval your research requires. The cost of collecting environmental data using automated data recorders and their associated sensors continues to drop with advancements in microprocessor development. The value of the data collected by these systems is largely determined by decisions regarding overall project and individual study component design. The utility and versatility of the information collected is a function of the planning performed at the beginning of the research program. The initial design of the monitoring system and the database produced by the system will determine whether or not the data may be useful for other work being conducted on site or nearby. The expected and actual functionality of the database produced can be quite different depending on the resources applied to the monitoring system during initial setup and with ongoing maintenance. This paper incorporates the experiences gained from three long-term research programs involving extensive automated environmental monitoring networks, the problems encountered, the success stories, and the lessons learned. Suggestions and considerations for system design and database management are proposed. Key words: environmental monitoring, system design, database management

scholarly journals Supervised Machine Learning for Regionalization of Environmental Data: Distribution of Uranium in Groundwater in Ukraine

2018 ◽  
Vol 1 ◽  
pp. 1-4
Author(s):  
Michael Govorov ◽  
Gennady Gienko ◽  
Viktor Putrenko
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Learning Algorithms ◽  
Environmental Parameters ◽  
Unsupervised Classification ◽  
Machine Learning Algorithms ◽  
Environmental Data ◽  
Supervised Machine Learning ◽  
Ann Models ◽  
Homogeneous Regions

In this paper, several supervised machine learning algorithms were explored to define homogeneous regions of con-centration of uranium in surface waters in Ukraine using multiple environmental parameters. The previous study was focused on finding the primary environmental parameters related to uranium in ground waters using several methods of spatial statistics and unsupervised classification. At this step, we refined the regionalization using Artifi-cial Neural Networks (ANN) techniques including Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Convolutional Neural Network (CNN). The study is focused on building local ANN models which may significantly improve the prediction results of machine learning algorithms by taking into considerations non-stationarity and autocorrelation in spatial data.

Giscience in the Mountain Geography

2010 ◽  
Vol 27 (1-2) ◽  
pp. 81-90
Author(s):  
Krishna Poudel
Keyword(s):  
Spatial Data ◽  
Environmental Data ◽  
Temporal Data ◽  
Observation Systems ◽  
Research Findings ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics ◽  
Mountain Geography ◽  
Different Sources

Mountains have distinct geography and are dynamic in nature compared to the plains. 'Verticality' and 'variation' are two fundamental specificities of the mountain geography. They possess distinct temporal and spatial characteristics in a unique socio-cultural setting. There is an ever increasing need for spatial and temporal data for planning and management activities; and Geo Information (GI) Science (including Geographic Information and Earth Observation Systems). This is being recognized more and more as a common platform for integrating spatial data with social, economic and environmental data and information from different sources. This paper investigates the applicability and challenges of GISscience in the context of mountain geography with ample evidences and observations from the mountain specific publications, empirical research findings and reports. The contextual explanation of mountain geography, mountain specific problems, scientific concerns about the mountain geography, advances in GIScience, the role of GIScience for sustainable development, challenges on application of GIScience in the contexts of mountains are the points of discussion. Finally, conclusion has been made with some specific action oriented recommendations.

To the 70th anniversary of World Meteorological Organization. Scientific and technical cooperation of Hydrometeorological Center of the USSR/Russia in the Programs of World Meteorological Organization

2020 ◽  
pp. 117-138
Author(s):  
S.V. Borshch ◽  
◽  
R.M. Vil’fand ◽  
D.B. Kiktev ◽  
V.M. Khan ◽  
...  
Keyword(s):  
Environmental Monitoring ◽  
High Efficiency ◽  
World Meteorological Organization ◽  
70Th Anniversary ◽  
Technical Level ◽  
Technical Cooperation ◽  
Wide Range

The paper presents the summary and results of long-term and multi-faceted experience of international scientific and technical cooperation of Hydrometeorological Center of Russia in the field of hydrometeorology and environmental monitoring within the framework of WMO programs, which indicates its high efficiency in performing a wide range of works at a high scientific and technical level. Keywords: World Meteorological Organization, major WMO programs, representatives of Hydrometeorological Center of Russia in WMO

scholarly journals The YadA Protein of Yersinia pseudotuberculosis Mediates High-Efficiency Uptake into Human Cells under Environmental Conditions in Which Invasin Is Repressed

2002 ◽  
Vol 70 (9) ◽  
pp. 4880-4891 ◽  
Author(s):  
Julia Eitel ◽  
Petra Dersch
Keyword(s):  
Extracellular Matrix ◽  
Mammalian Cells ◽  
Yersinia Pseudotuberculosis ◽  
High Efficiency ◽  
Environmental Parameters ◽  
Infection Process ◽  
Nutrient Concentrations ◽  
Integrin Receptors ◽  
Uptake Process ◽  
High Level

ABSTRACT The YadA protein is a major adhesin of Yersinia pseudotuberculosis that promotes tight adhesion to mammalian cells by binding to extracellular matrix proteins. In this study, we first addressed the possibility of competitive interference of YadA and the major invasive factor invasin and found that expression of YadA in the presence of invasin affected neither the export nor the function of invasin in the outer membrane. Furthermore, expression of YadA promoted both bacterial adhesion and high-efficiency invasion entirely independently of invasin. Antibodies against fibronectin and β1 integrins blocked invasion, indicating that invasion occurs via extracellular-matrix-dependent bridging between YadA and the host cell β1 integrin receptors. Inhibitor studies also demonstrated that tyrosine and Ser/Thr kinases, as well as phosphatidylinositol 3-kinase, are involved in the uptake process. Further expression studies revealed that yadA is regulated in response to several environmental parameters, including temperature, ion and nutrient concentrations, and the bacterial growth phase. In complex medium, YadA production was generally repressed but could be induced by addition of Mg2+. Maximal expression of yadA was obtained in exponential-phase cells grown in minimal medium at 37°C, conditions under which the invasin gene is repressed. These results suggest that YadA of Y. pseudotuberculosis constitutes another independent high-level uptake pathway that might complement other cell entry mechanisms (e.g., invasin) at certain sites or stages during the infection process.

scholarly journals The impact of environmental variables on the spread of COVID-19 in the Republic of Korea

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Kwan Lim ◽  
Oh Joo Kweon ◽  
Hye Ryoun Kim ◽  
Tae-Hyoung Kim ◽  
Mi-Kyung Lee
Keyword(s):  
Environmental Factors ◽  
Virus Disease ◽  
Environmental Parameters ◽  
Environmental Data ◽  
Republic Of Korea ◽  
Metropolitan Region ◽  
Health Concern ◽  
Ozone Level ◽  
The Republic ◽  
The Impact

AbstractCorona virus disease 2019 (COVID-19) has been declared a global pandemic and is a major public health concern worldwide. In this study, we aimed to determine the role of environmental factors, such as climate and air pollutants, in the transmission of COVID-19 in the Republic of Korea. We collected epidemiological and environmental data from two regions of the Republic of Korea, namely Seoul metropolitan region (SMR) and Daegu-Gyeongbuk region (DGR) from February 2020 to July 2020. The data was then analyzed to identify correlations between each environmental factor with confirmed daily COVID-19 cases. Among the various environmental parameters, the duration of sunshine and ozone level were found to positively correlate with COVID-19 cases in both regions. However, the association of temperature variables with COVID-19 transmission revealed contradictory results when comparing the data from SMR and DGR. Moreover, statistical bias may have arisen due to an extensive epidemiological investigation and altered socio-behaviors that occurred in response to a COVID-19 outbreak. Nevertheless, our results suggest that various environmental factors may play a role in COVID-19 transmission.

scholarly journals An Empirical Mode-Spatial Model for Environmental Data Imputation

Hydrology ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 63 ◽  
Author(s):  
Benjamin Nelsen ◽  
D. Williams ◽  
Gustavious Williams ◽  
Candace Berrett
Keyword(s):  
Time Series ◽  
Spatial Data ◽  
Missing Values ◽  
Time Series Data ◽  
Environmental Data ◽  
Series Data ◽  
Data Imputation ◽  
Accurate Data ◽  
Target Station ◽  
Periodic Components

Complete and accurate data are necessary for analyzing and understanding trends in time-series datasets; however, many of the available time-series datasets have gaps that affect the analysis, especially in the earth sciences. As most available data have missing values, researchers use various interpolation methods or ad hoc approaches to data imputation. Since the analysis based on inaccurate data can lead to inaccurate conclusions, more accurate data imputation methods can provide accurate analysis. We present a spatial-temporal data imputation method using Empirical Mode Decomposition (EMD) based on spatial correlations. We call this method EMD-spatial data imputation or EMD-SDI. Though this method is applicable to other time-series data sets, here we demonstrate the method using temperature data. The EMD algorithm decomposes data into periodic components called intrinsic mode functions (IMF) and exactly reconstructs the original signal by summing these IMFs. EMD-SDI initially decomposes the data from the target station and other stations in the region into IMFs. EMD-SDI evaluates each IMF from the target station in turn and selects the IMF from other stations in the region with periodic behavior most correlated to target IMF. EMD-SDI then replaces a section of missing data in the target station IMF with the section from the most closely correlated IMF from the regional stations. We found that EMD-SDI selects the IMFs used for reconstruction from different stations throughout the region, not necessarily the station closest in the geographic sense. EMD-SDI accurately filled data gaps from 3 months to 5 years in length in our tests and favorably compares to a simple temporal method. EMD-SDI leverages regional correlation and the fact that different stations can be subject to different periodic behaviors. In addition to data imputation, the EMD-SDI method provides IMFs that can be used to better understand regional correlations and processes.

Intelligent Environmental Monitoring System Based on Multi-Sensor Data Technology

2020 ◽  
Vol 11 (4) ◽  
pp. 57-71
Author(s):  
Qiuxia Liu
Keyword(s):  
Data Fusion ◽  
Environmental Monitoring ◽  
Real Time ◽  
Monitoring System ◽  
Intelligent System ◽  
Evidence Synthesis ◽  
Environmental Parameters ◽  
Monitoring Data ◽  
Sensor Data ◽  
Environmental Monitoring System

Using multi-sensor data fusion technology, ARM technology, ZigBee technology, GPRS, and other technologies, an intelligent environmental monitoring system is studied and developed. The SCM STC12C5A60S2 is used to collect the main environmental parameters in real time intelligently. The collected data is transmitted to the central controller LPC2138 through the ZigBee module ATZGB-780S5, and then the collected data is transmitted to the management computer through the GPRS communication module SIM300; thus, the real-time processing and intelligent monitoring of the environmental parameters are realized. The structure of the system is optimized; the suitable fusion model of environmental monitoring parameters is established; the hardware and the software of the intelligent system are completed. Each sensor is set up synchronously at the end of environmental parameter acquisition. The method of different value detection is used to filter out different values. The authors obtain the reliability of the sensor through the application of the analytic hierarchy process. In the analysis and processing of parameters, they proposed a new data fusion algorithm by using the reliability, probability association algorithm, and evidence synthesis algorithm. Through this algorithm, the accuracy of environmental monitoring data and the accuracy of judging monitoring data are greatly improved.

scholarly journals Street Network: Physical and Cultural Transformations on the Morphology of Historical City of Malacca

2021 ◽  
pp. 1-13
Author(s):  
Marina Mohd Nor ◽  
Norzailawati Mohd Noor ◽  
Sadayuki Shimoda
Keyword(s):  
Cultural Influences ◽  
Development Trend ◽  
Street Network ◽  
Cultural Impact ◽  
Multiple Sensors ◽  
Street Networks ◽  
Cultural Transformations ◽  
Physical Transformation ◽  
Spot 5 ◽  
The Development Trend

The deterioration of streets in the historical city of Malacca in Malaysia due to modernization contributes to the streets’ vulnerabilities. This paper purposely analyses the physical transformation of the street networks for the years of 1993-2015, and the cultural influences and impact throughout the establishment of multi-racial cultural society. The methodology for the study is through mapping the street networks of Malacca city by using SPOT satellite imageries of three different years; 1993, 2005, and 2015, and through the street semi-automatic extraction technique to monitor the street pattern of Malacca city. Multiple sensors of SPOT were used, consisting of SPOT-2XS, SPOT 5, and SPOT 6 with 20 m, 5 m, and 1.5 m resolutions in extracting the street objects, while using the IMAGINE OBJECTIVE tools from ERDAS. The finding shows that the street network trend varied from 1993, 2005, and 2015 where the streets achieved 23.8% street expansions in the year 1993 compared to 10.49% in the year 2005. However, the development trend of streets increased to 14.68% in the year 2015. The connection of the physical transformations of the streets with the cultural impact contributed to the sense of place and divided the streets based on socio-economic, cultural and ethnic lines. Finally, it shows that the trend and pattern of street networks were essential in understanding a city’s morphology that has a significant impact on cultural evolution since the establishment of the Chinese community in Malacca.

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