Development of geotechnical sensor network analysis capabilities for slope stability monitoring, within a GIS based decision support system

Author(s):  
D Hutchinson ◽  
R Harrap ◽  
D Ball ◽  
M Diederichs ◽  
N Kjelland
Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1693
Author(s):  
Chanchan Du ◽  
Lixin Zhang ◽  
Xiao Ma ◽  
Xiaokang Lou ◽  
Yongchao Shan ◽  
...  

Scientific researchers have applied newly developed technologies, such as sensors and actuators, to different fields, including environmental monitoring, traffic management, and precision agriculture. Using agricultural technology to assist crop fertilization is an important research innovation that can not only reduce the workload of farmers, but also reduce resource waste and soil pollution. This paper describes the design and development of a water-fertilizer control system based on the soil conductivity threshold. The system uses a low-cost wireless sensor network as a data collection and transmission tool and transmits the data to the decision support system. The decision support system considers the change in soil electrical conductivity (EC) and moisture content to guide the application of water-fertilizer, and then improves the fertilization accuracy of the water-fertilizer control system. In the experiment, the proposed water-fertilizer control system was tested, and it was concluded that, compared with the existing traditional water-fertilizer integration control system, the amount of fertilizer used by the system was reduced by 10.89% on average, and it could save 0.76–0.87 tons of fertilizer throughout the whole growth period of cotton.


2013 ◽  
Vol 158 ◽  
pp. 109-118 ◽  
Author(s):  
Benni Thiebes ◽  
Rainer Bell ◽  
Thomas Glade ◽  
Stefan Jäger ◽  
Malcolm Anderson ◽  
...  

Network based data representation has received widespread attention over the years. Data is oriented in graph format by aligning information as nodes and edges. Some of the predominant network cases include biological and social sciences. There is a growing need to extract knowledge patterns from network orientations. In such scenario, the current study focuses on extracting data patterns from network data. Schizophrenia gene data and TRAI wireless performance data is identified for performing biological and social network analysis. Biological network analysis is performed to identify relevant gene ties which act as hotspots for identifying disease causing genes. On similar lines, social network analysis is performed on wireless dataset to identify essential telecom operators responsible for customer retention. Based on these outcomes, a decision support system, BioSocioLink is designed in R programming language to perform biological and social network analysis. The support system accurately detects knowledge patterns from both the datasets. The study is concluded by deploying the support system in local programming environment.


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