面向Petri网的先进建筑能源管理系统方法

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
S. Marrone, L. Campanile, Roberta De Fazio, Michele Di Giovanni, U. Gentile, F. Marulli, Laura Verde
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引用次数: 0

摘要

可持续性是日常生活中几个方面追求的主要目标之一;近年来的能源短缺和价格上涨加剧了这一问题,特别是在建筑能源管理方面。由于物联网(IoT)是一种评估计算范式,能够从现场捕获有意义的数据并将其发送到云基础设施,因此也启用了其他方法,即基于模型的方法。这些方法可用于在建立建筑能源管理系统(BEMS)之前预测其功能和非功能特性。本文旨在弥合基于模型的方法与传感和小型计算设备的物理实现之间的差距。通过一种集成的方法,能够利用Petri网的不同方言的力量,本文提出了一种早期评估BEMS属性以及自动生成物联网控制器的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Petri net oriented approach for advanced building energy management systems
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.
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来源期刊
Journal of Ambient Intelligence and Smart Environments
Journal of Ambient Intelligence and Smart Environments COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
4.30
自引率
17.60%
发文量
23
审稿时长
>12 weeks
期刊介绍: The Journal of Ambient Intelligence and Smart Environments (JAISE) serves as a forum to discuss the latest developments on Ambient Intelligence (AmI) and Smart Environments (SmE). Given the multi-disciplinary nature of the areas involved, the journal aims to promote participation from several different communities covering topics ranging from enabling technologies such as multi-modal sensing and vision processing, to algorithmic aspects in interpretive and reasoning domains, to application-oriented efforts in human-centered services, as well as contributions from the fields of robotics, networking, HCI, mobile, collaborative and pervasive computing. This diversity stems from the fact that smart environments can be defined with a variety of different characteristics based on the applications they serve, their interaction models with humans, the practical system design aspects, as well as the multi-faceted conceptual and algorithmic considerations that would enable them to operate seamlessly and unobtrusively. The Journal of Ambient Intelligence and Smart Environments will focus on both the technical and application aspects of these.
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