Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions

The Internet of Vehicles (IoV) is a developing technology attracting attention from the industry and the academia. Hundreds of millions of vehicles are projected to be connected within the IoV environments by 2035. Each vehicle in the environment is expected to generate massive amounts of data. Curr...

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Autores principales:	Haruna Chiroma, Shafi’i M. Abdulhamid, Ibrahim A. T. Hashem, Kayode S. Adewole, Absalom E. Ezugwu, Saidu Abubakar, Liyana Shuib
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/60ab02f2ab0d4d88a6fd25d6a471ddbf
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spelling	oai:doaj.org-article:60ab02f2ab0d4d88a6fd25d6a471ddbf2021-11-22T01:11:17ZDeep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions1563-514710.1155/2021/9022558https://doaj.org/article/60ab02f2ab0d4d88a6fd25d6a471ddbf2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9022558https://doaj.org/toc/1563-5147The Internet of Vehicles (IoV) is a developing technology attracting attention from the industry and the academia. Hundreds of millions of vehicles are projected to be connected within the IoV environments by 2035. Each vehicle in the environment is expected to generate massive amounts of data. Currently, surveys on leveraging deep learning (DL) in the IoV within the context of big data analytics (BDA) are scarce. In this paper, we present a survey and explore the theoretical perspective of the role of DL in the IoV within the context of BDA. The study has unveiled substantial research opportunities that cut across DL, IoV, and BDA. Exploring DL in the IoV within BDA is an infant research area requiring active attention from researchers to fully understand the emerging concept. The survey proposes a model of IoV environment integrated into the cloud equipped with a high-performance computing server, DL architecture, and Apache Spark for data analytics. The current developments, challenges, and opportunities for future research are presented. This study can guide expert and novice researchers on further development of the application of DL in the IoV within the context of BDA.Haruna ChiromaShafi’i M. AbdulhamidIbrahim A. T. HashemKayode S. AdewoleAbsalom E. EzugwuSaidu AbubakarLiyana ShuibHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Haruna Chiroma Shafi’i M. Abdulhamid Ibrahim A. T. Hashem Kayode S. Adewole Absalom E. Ezugwu Saidu Abubakar Liyana Shuib Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
description	The Internet of Vehicles (IoV) is a developing technology attracting attention from the industry and the academia. Hundreds of millions of vehicles are projected to be connected within the IoV environments by 2035. Each vehicle in the environment is expected to generate massive amounts of data. Currently, surveys on leveraging deep learning (DL) in the IoV within the context of big data analytics (BDA) are scarce. In this paper, we present a survey and explore the theoretical perspective of the role of DL in the IoV within the context of BDA. The study has unveiled substantial research opportunities that cut across DL, IoV, and BDA. Exploring DL in the IoV within BDA is an infant research area requiring active attention from researchers to fully understand the emerging concept. The survey proposes a model of IoV environment integrated into the cloud equipped with a high-performance computing server, DL architecture, and Apache Spark for data analytics. The current developments, challenges, and opportunities for future research are presented. This study can guide expert and novice researchers on further development of the application of DL in the IoV within the context of BDA.
format	article
author	Haruna Chiroma Shafi’i M. Abdulhamid Ibrahim A. T. Hashem Kayode S. Adewole Absalom E. Ezugwu Saidu Abubakar Liyana Shuib
author_facet	Haruna Chiroma Shafi’i M. Abdulhamid Ibrahim A. T. Hashem Kayode S. Adewole Absalom E. Ezugwu Saidu Abubakar Liyana Shuib
author_sort	Haruna Chiroma
title	Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
title_short	Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
title_full	Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
title_fullStr	Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
title_full_unstemmed	Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
title_sort	deep learning-based big data analytics for internet of vehicles: taxonomy, challenges, and research directions
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/60ab02f2ab0d4d88a6fd25d6a471ddbf
work_keys_str_mv	AT harunachiroma deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT shafiimabdulhamid deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT ibrahimathashem deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT kayodesadewole deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT absalomeezugwu deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT saiduabubakar deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections AT liyanashuib deeplearningbasedbigdataanalyticsforinternetofvehiclestaxonomychallengesandresearchdirections
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Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions

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