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<p>This paper presents a model-centric prototyping framework for developing cloud-based mobile applications to optimize energy consumption and promote sustainable behavior. Integrating behavioral models such as the Heuristic Model, Geller’s Model and Fogg’s Behavior Model, the framework transitions users from passive consumers to active participants in energy conservation. Leveraging Mobile Cloud Computing (MCC), the system overcomes mobile device limitations by offloading resource-intensive tasks to the cloud, enhancing energy efficiency and user experience. The proposed system integrates smart devices, cloud-based services, and a user-centered application. Functional and non-functional requirements were derived from behavioral models and stakeholder perspectives. Usability testing validated the system’s design, achieving a System Usability Scale score of 84.6%, which corresponds to an “A” rating—indicating excellent usability and strong potential for long-term adoption. The system demonstrates its potential to align consumer energy savings with grid stability and efficiency. This research showcases the impact of combining behavioral science with advanced mobile cloud technologies to foster sustainability.</p>

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A framework for model-centric prototyping in cloud mobile application development applied to rationalized energy consumption

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月4日

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  • Daniel Voskergian,
  • Salaheddin Odeh

摘要

This paper presents a model-centric prototyping framework for developing cloud-based mobile applications to optimize energy consumption and promote sustainable behavior. Integrating behavioral models such as the Heuristic Model, Geller’s Model and Fogg’s Behavior Model, the framework transitions users from passive consumers to active participants in energy conservation. Leveraging Mobile Cloud Computing (MCC), the system overcomes mobile device limitations by offloading resource-intensive tasks to the cloud, enhancing energy efficiency and user experience. The proposed system integrates smart devices, cloud-based services, and a user-centered application. Functional and non-functional requirements were derived from behavioral models and stakeholder perspectives. Usability testing validated the system’s design, achieving a System Usability Scale score of 84.6%, which corresponds to an “A” rating—indicating excellent usability and strong potential for long-term adoption. The system demonstrates its potential to align consumer energy savings with grid stability and efficiency. This research showcases the impact of combining behavioral science with advanced mobile cloud technologies to foster sustainability.