Predicting climate factors based on big data analytics based agricultural disaster management

Jaber, Mustafa Musa; Ali, Mohammed Hasan; Khalil, Sura; Jassim, Mustafa Mohammed; Alkhayyat, Ahmed; Aziz, Hussein Waheed; Alkhuwaylidee, Ahmed Rashid

doi:10.1016/j.pce.2022.103243

Cited by 13 publications

(3 citation statements)

References 28 publications

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“…In this case, Volume, Velocity and Value are the matches in the 'Vs', at least. Jaber et al [117] apply Big Data to predict climate factors according to information about natural disasters. To achieve this, they must process and manage a huge volume of data from different sources with interoperability problems.…”

Section: Big Data Applicationsmentioning

confidence: 99%

What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey

García

Álvarez-Fernández²

2022

BDCC

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Big Data has changed how enterprises and people manage knowledge and make decisions. However, when talking about Big Data, so many times there are different definitions about what it is and what it is used for, as there are many interpretations and disagreements. For these reasons, we have reviewed the literature to compile and provide a possible solution to the existing discrepancies between the terms Data Analysis, Data Mining, Knowledge Discovery in Databases, and Big Data. In addition, we have gathered the patterns used in Data Mining, the different phases of Knowledge Discovery in Databases, and some definitions of Big Data according to some important companies and organisations. Moreover, Big Data has challenges that sometimes are the same as its own characteristics. These characteristics are known as the Vs. Nonetheless, depending on the author, these Vs can be more or less, from 3 to 5, or even 7. Furthermore, the 4Vs or 5Vs are not the same every time. Therefore, in this survey, we reviewed the literature to explain how many Vs have been detected and explained according to different existing problems. In addition, we detected 7Vs, three of which had subtypes.

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Section: Big Data Applicationsmentioning

confidence: 99%

What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey

García

Álvarez-Fernández²

2022

BDCC

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“…These applications include disaster predictions on melting snow hurricanes and landslides, disaster awareness distribution and disaster incident information in real time. Jaber et al (2022) investigated the role of big data in agricultural disaster management and emphasised the technical status of providing practical and efficient disaster management solutions. Balti et al (2022) created a big data framework for decision-makers to use in tracking the effects of drought disasters and, as a result, planning mitigation and remediation measures.…”

Section: Introductionmentioning

confidence: 99%

Cloud-based big data framework towards strengthening disaster risk reduction: systematic mapping

Mahrin¹,

Subbarao

Chuprat

et al. 2023

JSTPM

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Purpose Cloud computing promises dependable services offered through next-generation data centres based on virtualization technologies for computation, network and storage. Big Data Applications have been made viable by cloud computing technologies due to the tremendous expansion of data. Disaster management is one of the areas where big data applications are rapidly being deployed. This study looks at how big data is being used in conjunction with cloud computing to increase disaster risk reduction (DRR). This paper aims to explore and review the existing framework for big data used in disaster management and to provide an insightful view of how cloud-based big data platform toward DRR is applied. Design/methodology/approach A systematic mapping study is conducted to answer four research questions with papers related to Big Data Analytics, cloud computing and disaster management ranging from the year 2013 to 2019. A total of 26 papers were finalised after going through five steps of systematic mapping. Findings Findings are based on each research question. Research limitations/implications A specific study on big data platforms on the application of disaster management, in general is still limited. The lack of study in this field is opened for further research sources. Practical implications In terms of technology, research in DRR leverage on existing big data platform is still lacking. In terms of data, many disaster data are available, but scientists still struggle to learn and listen to the data and take more proactive disaster preparedness. Originality/value This study shows that a very famous platform selected by researchers is central processing unit based processing, namely, Apache Hadoop. Apache Spark which uses memory processing requires a big capacity of memory, therefore this is less preferred in the world of research.

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“…As a country prone to natural disasters, all industries in China are currently facing the key test and challenge of economic stagnation or recession caused by disasters [1][2][3]. As an important way to reduce the loss caused by disasters and avoid the regressive phenomenon of social and economic level, under the premise of big data technology, research on the construction of safety and comprehensive disaster prevention system has an important practical role and value [4]. And disaster prevention system as a national security, especially reduce the serious consequences brought by the disaster comes, social and economic level of steady development, comprehensive analysis of its related system research to promote the economic level of development and social stability matching industry demand, and the promotion of China's disaster, high level and high quality professional technology development are of great practical significance [5].…”

Section: Introductionmentioning

confidence: 99%

Research on Safety and Integrated Disaster Prevention System Based on Big Data Technology

Sun

2023

IJIIS Int. J. Informatics Inf. Syst.

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Safety integrated disaster prevention systems, as a guarantee of national safety, especially to reduce the serious consequences of disasters, promote the steady development of the economic and social level, have important practical value for the comprehensive study of safety and disaster prevention systems. However, the current application and update of such systems by relevant government agencies and the social level cannot effectively follow the development needs of the society and the industry, and there is an urgent need for effective reform. Based on this, this paper first analyzes the problems existing in the research and construction system of big data technology in the security and integrated disaster prevention system, and then gives the construction strategy of the research system of safety and disaster prevention in view of these problems.

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Predicting climate factors based on big data analytics based agricultural disaster management

Cited by 13 publications

References 28 publications

What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey

What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey

Cloud-based big data framework towards strengthening disaster risk reduction: systematic mapping

Research on Safety and Integrated Disaster Prevention System Based on Big Data Technology

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