Big Data Management for Cloud-Enabled Geological Information Services

Zhu, Yueqin; Tan, Yongjie; Luo, Xiong; He, Zijie

doi:10.1155/2018/1327214

Cited by 8 publications

(3 citation statements)

References 45 publications

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“…Although RSBD is faced with the situation of massive data with difficulties in mining information and finding knowledge, the available infrastructure for RSBD is developing rapidly in terms of capacity, scalability, availability, and performance now. The wide application of cloud computing and artificial intelligence will also change the data processing and application methods, and solve RSBD handling issues, such as massive storage, large-scale management, intelligent processing, and data mining [21][22][23][24][25][26][27][28][29][30][31][32].…”

Section: Cloud-based Solution To Rsbdmentioning

confidence: 99%

A cloud-based solution and platform for remote sensing big data applications: challenges and opportunities

Wang,

Shi,

Liu

et al. 2023

Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023)

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Satellite remote sensing, as an important means of disseminating and perceiving spatio-temporal geographic information, is widely used in many fields. The accumulated satellite remote sensing data from various industries has gradually formed Remote Sensing Big Data, and its explosive growth has also brought challenges to various applications. It discusses the big data characteristics of Remote Sensing Big Data, and also the challenges posed by the lack of handling technologies in this paper. Meanwhile, it also discusses the opportunities and key technical issues from cloud computing technology to Remote Sensing Big Data handling, and provides a cloud RSBD solution and platform prototype.

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Section: Cloud-based Solution To Rsbdmentioning

confidence: 99%

A cloud-based solution and platform for remote sensing big data applications: challenges and opportunities

Wang,

Shi,

Liu

et al. 2023

Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023)

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“…Asymmetric scalar-product-preserving encryption scheme was studied in [16], to control the privacy of data. Successful processing of data and analysis for Geological Information Services was addressed in [17] with the aid of aggregation. Challenges related to security and privacy was analyzed in [18].…”

Section: Related Workmentioning

confidence: 99%

Cloud based multicasting using fat tree data confidential recurrent neural network

et al. 2019

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With the progress of cloud computing, more users are attracted by its strong and cost-effective computation potentiality. Nevertheless, whether Cloud Service Providers can efficiently protect Cloud Users data confidentiality (DC) remains a demanding issue. The CU may execute several applications with multicast needs. In Cloud different techniques were used to provide DC with multicast necessities. In this work, we aim at ensuring DC in the cloud. This is achieved using a two-step technique, called Fat Tree Data Confidential Recurrent Neural Network (FT-DCRNN) in a cloud environment. The first step performs the construction of Fat Tree based on Multicast model. The aim to use Fat Tree with Multicast model is that the multicast model propagates traffic on multiple links. With the Degree Restrict Multicast Fat Tree construction algorithm using a reference function, the minimum average between two links is measured. With these measured links, multicast is said to be performed that in turn improves the throughput and efficiency of cloud service. Then, with the objective of providing DC for the multi-casted data or messages, DCRNN model is applied. With the Non-linear Recurrent Neural Network using Logistic Activation Function, by handling complex non-linear relationships, average response time is said to be reduced.

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“…This valuable data can significantly reduce the time and cost of a project during the feasibility study phase. Geotechnical engineers rely on soil formation and physical properties to make informed decisions and designs, and information technology applications, such as Geographic Information Systems and database systems, are essential for effectively managing and interpreting data in the geotechnical field [24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Geotechnical information system employs spatial analysis to utilize information gathered from Cone Penetration Testing (CPT)

Yanto

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Surakarta has diverse structures, including malls, shopping centers, hotels, offices, markets, hospitals, colleges, and schools. However, the Regional Government lacks a comprehensive data information system about the Cone Penetration Test (CPT). Such a system benefits investors seeking to develop new infrastructure in Surakarta. In order to tackle this problem, a research study was carried out to develop an Information System based on CPT data regarding the depth of hard soil throughout the city. The investigation analyzed pre-existing CPT data, its compilation, and cartographic representation. However, the arbitrary allocation of CPT data presents a challenge. Results of the study indicate that the most predominant depth of compacted soil qc 250 kg/cm2 in Surakarta is 3-5 meters below the surface. Moreover, comparing the depth of CPT soil in the field with GIS at multiple observation points indicates findings that mostly conform to GIS predictions and those of in situ tests. Combining CPT data with ArcGIS software has been a highly successful approach in identifying projects and providing robust geotechnical information.

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Big Data Management for Cloud-Enabled Geological Information Services

Cited by 8 publications

References 45 publications

A cloud-based solution and platform for remote sensing big data applications: challenges and opportunities

A cloud-based solution and platform for remote sensing big data applications: challenges and opportunities

Cloud based multicasting using fat tree data confidential recurrent neural network

Geotechnical information system employs spatial analysis to utilize information gathered from Cone Penetration Testing (CPT)

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