scholarly journals Automatic water level control using LabVIEW

2017 ◽  
Vol 2 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Hemin Ismael Azeez ◽  
Narongrit Pimkumwong ◽  
Shih-Chung Chen
Keyword(s):  
Water Supply ◽  
Water Level ◽  
Programming Language ◽  
Water Shortage ◽  
Level Control ◽  
Graphical Programming ◽  
Dataflow Model ◽  
The World ◽  
Circuit Components ◽  
Full Day

Shortage in water supply is one of the major issues that some major cities throughout the world are facing nowadays. Due to not having full day water supply, households will have to efficiently manage the problem of water shortage and overcome the crises. This paper presents a system that indicates and controls the level of water in overhead tanks. Ultra-sonic sensors are employed to detect the level of the water between predefined minimum and maximum levels. LabVIEW which is a graphical programming language that uses a dataflow model is used to program microcontroller board Arduino UNO that is an interface between the software and the rest of the circuit components. From measured results good performance and accurate results are achieved.  

Application of Internet of Things monitoring technology to the improvement of agricultural irrigation disaster management

2020 ◽  
Author(s):  
Sheng-Hsueh Yang ◽  
Wen-Hao Leu ◽  
Meng-Chen Chen ◽  
Jiun-Hue Kuo ◽  
Keh-Chia Yeh
Keyword(s):  
Internet Of Things ◽  
Water Supply ◽  
Water Level ◽  
Early Warning ◽  
Water Shortage ◽  
The Internet ◽  
Agricultural Irrigation ◽  
Agricultural Crops ◽  
Flow Discharge ◽  
The Internet Of Things

<p>Climate change has gradually affected Taiwan's agricultural environment. The number of raining days has decreased, the rainfall intensity has increased, and the drought time has been prolonged. In addition, with the mountainous terrain of Taiwan, rainfall is not easy to be stored and used. The summer and autumn are rainy seasons, which are prone to flooding disasters, the lack of water in spring and winter causes droughts that cause insufficient agricultural water supply, and the stable supply of food is closely related to people's livelihood needs. Therefore, the research department uses UAV imaging technology to identify agricultural crops, grasp the agricultural crops and water supply needs in the spring and winter seasons, and try to estimate the water demand and distribution water volume as the management basis of agricultural irrigation and drainage. Use long-term meteorological models to estimate rainfall results in the next month, and determine whether there are water shortage characteristics in agricultural crop areas. If there is a water shortage, further use the Internet of Things monitoring technology to monitor the inflow and outflow of agricultural crops in irrigated areas, control and distribute the required water consumption, and then to reduce water supply at night or supplying irrigation water in turn in response to the water shortage during the irrigation period. In the summer and autumn rainfall periods, the Internet of Things technology is also used to observe the water level and flow discharge of the main irrigation waterways, and set the rainfall and water level early warning values to reduce the occurrence of flooding disasters in agricultural areas, and use the immediate hydrological and hydraulic models to forecast the future suggestions such as hourly water level and flow discharge and gate control provide timely information on agricultural disaster warnings. The relevant research area is in the Meinong Agricultural Area (about 4,000 ha) of Farm Irrigation Association of Kaohsiung Taiwan as an example. Through web pages hourly displays Internet of Things information, model analysis results, and disaster prevention early warning results to let the management units understand the actual status of agricultural irrigation areas.</p>

scholarly journals WATER-RESOURCES COMPLEX FOR SUSTAINABLE DEVELOPMENT: PROBLEMS OF DISTRIBUTION AND WATER SHORTAGE

2017 ◽  
pp. 61-67
Author(s):  
Vasyl Faifura
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Water Resources ◽  
Water Supply ◽  
Water Shortage ◽  
Economic Problems ◽  
Water Factor ◽  
Social And Economic Development ◽  
The World

The article deals with the current problems of providing water resources to the countries of the world and regions of Ukraine, emphasizes the role of the water factor in ensuring further social and economic development. Issues of water shortage and related political, social and economic problems are considered. The regional aspects of the world and national distribution of water resources are considered, an assessment of the water supply of the regions of the country available to the use of water resources.

Water Level Control of Small-scale Hydroelectric Power Plant

2002 ◽  
Vol 122 (6) ◽  
pp. 989-994
Author(s):  
Shinichiro Endo ◽  
Masami Konishi ◽  
Hirosuke Imabayashi ◽  
Hayami Sugiyama
Keyword(s):  
Power Plant ◽  
Water Level ◽  
Hydroelectric Power Plant ◽  
Small Scale ◽  
Hydroelectric Power ◽  
Level Control

Perspective of Water Resources in Japan and in the World

1991 ◽  
Vol 23 (1-3) ◽  
pp. 11-18
Author(s):  
Tamon Ishibashi
Keyword(s):  
Developing Countries ◽  
Water Resources ◽  
Water Shortage ◽  
Water Shortages ◽  
The World

Recently, problems of water shortage are becoming global in both developed and developing countries. This is due to tremendous population increases and also urbanization and industrialization. In this paper, countermeasures for future water shortages are described.

scholarly journals Hydrogeological and Geochemical Characteristics of the Coastal Aquifer of Stromboli Volcanic Island (Italy)

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 417
Author(s):  
Paolo Madonia ◽  
Gloria Campilongo ◽  
Marianna Cangemi ◽  
Maria Luisa Carapezza ◽  
Salvatore Inguaggiato ◽  
...  
Keyword(s):  
Water Supply ◽  
Coastal Aquifer ◽  
Volcano Monitoring ◽  
Conductivity Measurements ◽  
Thin Lens ◽  
Supply Source ◽  
The World ◽  
Volcanic Islands ◽  
Monitoring Protocols ◽  
Potential Use

Although groundwater is a strategic source in volcanic islands, most hydrogeochemical research on this topic has been focused on volcanic activity monitoring, overlooking general hydrogeological aspects. The same applies to one of the most studied volcanoes in the world, Stromboli Island (Italy). Here, we provide a hydrogeological scheme of its coastal aquifer, retrieving inferences about its potential use as a water supply source and for optimizing monitoring protocols for volcanic surveillance. Starting from the hydrogeochemical literature background, we analyzed new data, acquired both for volcano monitoring purposes and during specific surveys. Among these, there were saturated hydraulic conductivity measurements of selected rock samples and precise determinations of water table elevations based on GNSS surveys of wells. We identified a ubiquitous thin lens of brackish water floating on seawater and composed of a variable mixing of marine and meteoric components; inlets of hydrothermal fluids to the aquifer are basically gases, mainly CO2. Based on its hydrogeochemical character, the coastal aquifer of Stromboli could be used as a water supply source after desalinization by reverse osmosis, while the wells located far from the seashore are the most interesting for volcano monitoring, because they are less disturbed by the shallow geochemical noise.

scholarly journals Comparison of Night, Day and 24 h Motor Activity Data for the Classification of Depressive Episodes

Diagnostics ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 162 ◽  
Author(s):  
Julieta G. Rodríguez-Ruiz ◽  
Carlos E. Galván-Tejada ◽  
Laura A. Zanella-Calzada ◽  
José M. Celaya-Padilla ◽  
Jorge I. Galván-Tejada ◽  
...  
Keyword(s):  
Data Mining ◽  
Motor Activity ◽  
Random Forest Classifier ◽  
Machine Learning Algorithms ◽  
World Population ◽  
Activity Data ◽  
The World ◽  
Depressive Episodes ◽  
Full Day

Major Depression Disease has been increasing in the last few years, affecting around 7 percent of the world population, but nowadays techniques to diagnose it are outdated and inefficient. Motor activity data in the last decade is presented as a better way to diagnose, treat and monitor patients suffering from this illness, this is achieved through the use of machine learning algorithms. Disturbances in the circadian rhythm of mental illness patients increase the effectiveness of the data mining process. In this paper, a comparison of motor activity data from the night, day and full day is carried out through a data mining process using the Random Forest classifier to identified depressive and non-depressive episodes. Data from Depressjon dataset is split into three different subsets and 24 features in time and frequency domain are extracted to select the best model to be used in the classification of depression episodes. The results showed that the best dataset and model to realize the classification of depressive episodes is the night motor activity data with 99.37% of sensitivity and 99.91% of specificity.

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