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HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications

The development of IoT-based Android health monitoring mobile applications (apps) using traditional software development methods is a challenging task. Developers need to be familiar with various programming languages to manage the heterogeneity of hardware and software systems and to support differ...

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Detalles Bibliográficos
Autores principales: Mehrabi, Maryam, Zamani, Bahman, Hamou-Lhadj, Abdelwahab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514186/
https://www.ncbi.nlm.nih.gov/pubmed/36185751
http://dx.doi.org/10.1007/s10515-022-00363-9
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author Mehrabi, Maryam
Zamani, Bahman
Hamou-Lhadj, Abdelwahab
author_facet Mehrabi, Maryam
Zamani, Bahman
Hamou-Lhadj, Abdelwahab
author_sort Mehrabi, Maryam
collection PubMed
description The development of IoT-based Android health monitoring mobile applications (apps) using traditional software development methods is a challenging task. Developers need to be familiar with various programming languages to manage the heterogeneity of hardware and software systems and to support different communication technologies. To address these problems, in this paper, we first analyze the domain of health monitoring mobile applications and then propose a framework based on model-driven engineering that accelerates the development of such systems. The proposed framework, called HealMA, includes a domain-specific modeling language, a graphical modeling editor, several validation rules, and a set of model-to-code transformations, all packed as an Eclipse plugin. We evaluated the framework to assess its applicability in generating various mobile health applications, as well as its impact on software productivity. To this end, four different health monitoring applications have been automatically generated. Then, we evaluated the productivity of software developers by comparing the time and effort it takes to use HealMA compared to a code-centric process. As part of the evaluation, we also evaluated the usability of HealMA-generated apps by conducting a user study. The results show that HealMA is both applicable and beneficial for automatic generation of usable IoT-based Android health monitoring apps.
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spelling pubmed-95141862022-09-28 HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications Mehrabi, Maryam Zamani, Bahman Hamou-Lhadj, Abdelwahab Autom Softw Eng Article The development of IoT-based Android health monitoring mobile applications (apps) using traditional software development methods is a challenging task. Developers need to be familiar with various programming languages to manage the heterogeneity of hardware and software systems and to support different communication technologies. To address these problems, in this paper, we first analyze the domain of health monitoring mobile applications and then propose a framework based on model-driven engineering that accelerates the development of such systems. The proposed framework, called HealMA, includes a domain-specific modeling language, a graphical modeling editor, several validation rules, and a set of model-to-code transformations, all packed as an Eclipse plugin. We evaluated the framework to assess its applicability in generating various mobile health applications, as well as its impact on software productivity. To this end, four different health monitoring applications have been automatically generated. Then, we evaluated the productivity of software developers by comparing the time and effort it takes to use HealMA compared to a code-centric process. As part of the evaluation, we also evaluated the usability of HealMA-generated apps by conducting a user study. The results show that HealMA is both applicable and beneficial for automatic generation of usable IoT-based Android health monitoring apps. Springer US 2022-09-27 2022 /pmc/articles/PMC9514186/ /pubmed/36185751 http://dx.doi.org/10.1007/s10515-022-00363-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Mehrabi, Maryam
Zamani, Bahman
Hamou-Lhadj, Abdelwahab
HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title_full HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title_fullStr HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title_full_unstemmed HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title_short HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications
title_sort healma: a model-driven framework for automatic generation of iot-based android health monitoring applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514186/
https://www.ncbi.nlm.nih.gov/pubmed/36185751
http://dx.doi.org/10.1007/s10515-022-00363-9
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