Big data, analytics and artificial intelligence for sustainability

Bolanle A. Ojokoh; Oluwarotimi W. Samuel; Olatunji M. Omisore; Oluwafemi A. Sarumi; Peter A. Idowu; Emile R. Chimusa; Ashraf Darwish; Adebayo F. Adekoya; Ferdinand A. Katsriku

Scientific African (Sep 2020)

Big data, analytics and artificial intelligence for sustainability

Bolanle A. Ojokoh,
Oluwarotimi W. Samuel,
Olatunji M. Omisore,
Oluwafemi A. Sarumi,
Peter A. Idowu,
Emile R. Chimusa,
Ashraf Darwish,
Adebayo F. Adekoya,
Ferdinand A. Katsriku

Affiliations

Bolanle A. Ojokoh: Department of Information Systems, Federal University of Technology, Akure, Nigeria; Corresponding author.
Oluwarotimi W. Samuel: Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China
Olatunji M. Omisore: Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Oluwafemi A. Sarumi: Department of Computer Science, The Federal University of Technology, Akure, Nigeria
Peter A. Idowu: Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria
Emile R. Chimusa: Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
Ashraf Darwish: Department of Information Systems, Federal University of Technology, Akure, Nigeria; Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China; Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Department of Computer Science, The Federal University of Technology, Akure, Nigeria; Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria; Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
Adebayo F. Adekoya: Department of Information Systems, Federal University of Technology, Akure, Nigeria; Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China; Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Department of Computer Science, The Federal University of Technology, Akure, Nigeria; Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria; Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
Ferdinand A. Katsriku: Department of Information Systems, Federal University of Technology, Akure, Nigeria; Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China; Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Department of Computer Science, The Federal University of Technology, Akure, Nigeria; Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria; Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa

Journal volume & issue: Vol. 9
p. e00551

Abstract

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Big data technologies, Analytics and Artificial Intelligence are great tools with capabilities to accomplish complex tasks at levels beyond human skills. The trio are becoming more and more prominent these days as they can be utilized to collect, organize, and analyze large varied data sets in order to reveal hidden patterns and trends that can help address several problems peculiar to sustainable development. Nevertheless, a number of challenges arise in the process of exploring these technologies for proffering solutions. This special issue presents novel research approaches adopted in Africa in relation to Big Data, Analytics and Artificial Intelligence in different domains. It also presents the challenges and issues that can be explored in the future.

Published in Scientific African

ISSN: 2468-2276 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science
Website: https://www.journals.elsevier.com/scientific-african

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