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 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.
Highlights
IoT as a network of interconnected devices has emerged as a disruptive technology and an enabling platform that interconnects heterogeneous things such as humans, systems, services, and devices in a smart environment [1]–[3]
We propose that by unifying (i) software engineering processes, (ii) internet of things development, and (iii) data analytics methods, an engineering lifecycle can be adopted that supports design, development, operationalisation, and evolution of emerging and generation of Internet of Things Driven Data Analytics (IoT-DA) applications
We will see that limited research exists on how IoT-DA applications are designed, implemented, operationalised, and evolved in the context of software and system engineering life-cycle
Summary
IoT as a network of interconnected devices has emerged as a disruptive technology and an enabling platform that interconnects heterogeneous things such as humans, systems, services, and devices in a smart environment [1]–[3]. A rapid proliferation of IoT systems is primarily due to portable devices that unify hardware (embedded sensors) software (applications that manipulate sensors) and network Sensors) to enable things that collect, process, and exchange contextualised data [2]. Typical example of such contextualised data includes crowd-sensed traffic congestions or environmental pollution that can be captured by embedded sensors of mobile devices, manipulated by mobile applications, and transmitted over wireless networks [3].
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