Venue & metadata

• Journal/Proceedings: Journal of Ambient Intelligence and Smart Environments
• Volume: 15
• Number: 3
• Pages: 211 – 233
• Note: Cited by: 1; All Open Access, Bronze Open Access
• Author keywords: building energy management system; fluid stochastic Petri nets; Input-output Petri nets; model driven engineering; quantitative evaluation

Abstract

Sustainability is one of the main goals to pursue in several aspects of everyday life; the recent energy shortage and the price raise worsen this problem, especially in the management of energy in buildings. As the Internet of Things (IoT) is an assessed computing paradigm able to capture meaningful data from the field and send them to cloud infrastructures, other approaches are also enabled, namely model-based approaches. These methods can be used to predict functional and non-functional properties of Building Energy Management Systems (BEMS) before setting up them. This paper aims at bridging the gap between model-based approaches and physical realizations of sensing and small computing devices. Through an integrated approach, able to exploit the power of different dialects of Petri Nets, this paper proposes a methodology for the early evaluation of BEMS properties as well as the automatic generation of IoT controllers. © 2023 - IOS Press. All rights reserved.

Keywords

Buildings GS Energy management GS Energy management systems GS Internet of things GS Petroleum reservoir evaluation GS Stochastic models GS Stochastic systems GS Building energy management systems GS Computing paradigm GS Energy in buildings GS Energy shortages GS Fluid Stochastic Petri Nets GS Input-output GS Input-output petri net GS Model based approach GS Model-driven Engineering GS Quantitative evaluation GS Petri nets GS

Links & artifacts

DOI Publisher Copy BibTeX Download .bib

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Suggested citation

Marrone, S., Campanile, L., De Fazio, R., Di Giovanni, M., Gentile, U., Marulli, F., & Verde, L. (2023). A Petri net oriented approach for advanced building energy management systems [Article]. Journal of Ambient Intelligence and Smart Environments, 15(3), 211–233. https://doi.org/10.3233/AIS-230065