Software Engineering for IoT-Driven Data Analytics Applications

Aakash Ahmad; Mahdi Fahmideh; Ahmed B. Altamimi; Iyad Katib; Aiiad Albeshri; Abdulrahman Alreshidi; Adwan Alownie Alanazi; Rashid Mehmood

doi:10.1109/ACCESS.2021.3065528

IEEE Access (Jan 2021)

Software Engineering for IoT-Driven Data Analytics Applications

Aakash Ahmad,
Mahdi Fahmideh,
Ahmed B. Altamimi,
Iyad Katib,
Aiiad Albeshri,
Abdulrahman Alreshidi,
Adwan Alownie Alanazi,
Rashid Mehmood

Affiliations

Aakash Ahmad: ORCiD; Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia
Mahdi Fahmideh: School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, Australia
Ahmed B. Altamimi: ORCiD; Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia
Iyad Katib: ORCiD; Department of Computer Science, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University, Jeddah, Saudi Arabia
Aiiad Albeshri: ORCiD; Department of Computer Science, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University, Jeddah, Saudi Arabia
Abdulrahman Alreshidi: Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia
Adwan Alownie Alanazi: ORCiD; Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia
Rashid Mehmood: ORCiD; High Performance Computing Center, King Abdulaziz University, Jeddah, Saudi Arabia

DOI: https://doi.org/10.1109/ACCESS.2021.3065528
Journal volume & issue: Vol. 9
pp. 48197 – 48217

Abstract

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Internet of Things Driven Data Analytics (IoT-DA) has the potential to excel data-driven operationalisation of smart environments. However, limited research exists on how IoT-DA applications are designed, implemented, operationalised, and evolved in the context of software and system engineering life-cycle. This article empirically derives a framework that could be used to systematically investigate the role of software engineering (SE) processes and their underlying practices to engineer IoT-DA applications. First, using existing frameworks and taxonomies, we develop an evaluation framework to evaluate software processes, methods, and other artefacts of SE for IoT-DA. Secondly, we perform a systematic mapping study to qualitatively select 16 processes (from academic research and industrial solutions) of SE for IoT-DA. Thirdly, we apply our developed evaluation framework based on 17 distinct criterion (a.k.a. process activities) for fine-grained investigation of each of the 16 SE processes. Fourthly, we apply our proposed framework on a case study to demonstrate development of an IoT-DA healthcare application. Finally, we highlight key challenges, recommended practices, and the lessons learnt based on framework’s support for process-centric software engineering of IoT-DA. The results of this research can facilitate researchers and practitioners to engineer emerging and next-generation of IoT-DA software applications.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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