Software Engineering for IoT-Driven Data Analytics Applications
Aakash Ahmad, Mahdi Fahmideh, Ahmed B. Altamimi, Iyad Katib, Aiiad, Albeshri, Abdulrahman Alreshidi, Adwan Alanazi, Rashid Mehmood

TL;DR
This paper presents a systematic framework for evaluating and improving software engineering processes in IoT-driven data analytics applications, demonstrated through a healthcare case study.
Contribution
It develops an evaluation framework and applies it to analyze SE processes for IoT-DA, addressing a gap in systematic engineering approaches for these applications.
Findings
Identified key challenges in IoT-DA software engineering
Provided a set of best practices for IoT-DA development
Demonstrated the framework on a healthcare IoT-DA case study
Abstract
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…
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Taxonomy
TopicsSoftware System Performance and Reliability · IoT and Edge/Fog Computing · Advanced Software Engineering Methodologies
