research-article

Meteorological forecasting based on big data analysis

Authors:

Shadi Aljawarneh,

Juan Alfonso Lara TorralboAuthors Info & Claims

DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

Pages 9 - 11

https://doi.org/10.1145/3460620.3460622

Published: 04 June 2021 Publication History

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NOTICE OF CONCERN: ACM has received evidence that casts doubt on the integrity of the peer review process for the DATA 2021 Conference. As a result, ACM is issuing a Notice of Concern for all papers published and strongly suggests that the papers from this Conference not be cited in the literature until ACM's investigation has concluded and final decisions have been made regarding the integrity of the peer review process for this Conference.

Abstract

In this paper, we present the main ideas behind the development of a system that can be used to deal with meteorological big data. In particular, the system captures data online and downloads it locally onto a MongoDB database. After that, the user can create a particular database and corresponding minable views for analysis. The results provided by the systems are predictive models with the ability to predict some weather-related variables, such as temperature and rainfall. The system has been validated from a triple perspective (usability, experts’ validation, and performance assessment), obtaining satisfactory results. This paper aims to be a brief guide for authors who intend to developed similar systems either in the meteorological field or other domains generating big amounts of data.

References

[1]

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Eslam Hussein, Ronewa Sadiki, Yahlieel Jafta, Muhammad Mujahid Sungay, Olasupo Ajayi, and Antoine Bagula. 2020. Big data processing using hadoop and spark: The case of meteorology data. In Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, Vol. 311 LNICST. Springer, 180–185. https://doi.org/10.1007/978-3-030-41593-8_13

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Clifford Lynch. 2008. Big data: How do your data grow?, 28–29 pages. https://doi.org/10.1038/455028a

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Cited By

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Published In

DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

April 2021

277 pages

ISBN:9781450388382

DOI:10.1145/3460620

Editors:
Juan Alfonso Lara Torralbo
UDIMA, Madrid, Spain
,
Shadi A. Aljawarneh
JUST, Jordan
,
Vangipuram Radhakrishna
VNRVJIET, India
,
Arun N.
JAIN, India

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 June 2021

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DATA'21: International Conference on Data Science, E-learning and Information Systems 2021

April 5 - 7, 2021

Ma'an, Jordan

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Al-Momani AAljawarneh S(2022)Fraudulent Transactions Prediction Using Deep Neural Network2022 International Conference on Engineering & MIS (ICEMIS)10.1109/ICEMIS56295.2022.9914349(1-7)Online publication date: 4-Jul-2022
https://doi.org/10.1109/ICEMIS56295.2022.9914349
Sharea L(2022)mHealth: A Secure Health Monitoring System for Diabetes2022 International Conference on Engineering & MIS (ICEMIS)10.1109/ICEMIS56295.2022.9914169(1-4)Online publication date: 4-Jul-2022
https://doi.org/10.1109/ICEMIS56295.2022.9914169
Al-Jawarneh LMohammed T(2022)Service Quality in eLearning2022 International Conference on Engineering & MIS (ICEMIS)10.1109/ICEMIS56295.2022.9914135(1-5)Online publication date: 4-Jul-2022
https://doi.org/10.1109/ICEMIS56295.2022.9914135
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https://dl.acm.org/doi/10.1145/3492547.3492574
Aljawarneh F(2021)Enhancing the Quality of the Arabic Content for Nursing on InternetThe 7th International Conference on Engineering & MIS 202110.1145/3492547.3492573(1-4)Online publication date: 11-Oct-2021
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Al-Jawarneh L(2021)Acceptance of Blended learning Approach for Arab and European UniversitiesThe 7th International Conference on Engineering & MIS 202110.1145/3492547.3492572(1-4)Online publication date: 11-Oct-2021
https://dl.acm.org/doi/10.1145/3492547.3492572

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