A Numerical Analysis Based Internet of Things (IOT) and Big Data Analytics to Minimize Energy Consumption in Smart Buildings

Q4 Engineering
A. Zouhri, Abderahamane EZ-ZAHOUT, Said Chakouk, M. El Mallahi
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引用次数: 0

Abstract

The new wave of performant technology devices generates massive amounts of data. These devices are used in cities, homes, buildings, companies, and more. One of the reasons for digitalizing their tasks is that over the past few years, there has been an interest in reducing carbon emissions and increasing energy efficiency to create a friendly ecosystem and protect nature. One of which granted the explosion of data. After deploying these new devices, a significant increase in the use of the other face of energy to implement the components of the new devices was noticed. Above all, the interconnection of these intelligent devices is the central concept of the Internet of Things (IoT). This domain has widened the possibilities for the interconnection of building management systems (also named Smart Grids) and devices for better energy management. Furthermore, its potential is realized only after organizing and analyzing a large amount of data. Real-time management and maintenance of big data are critical to improving energy management in buildings. The benefits of big data analytics go beyond savings on electricity bills. It can provide comfort for building users and extend the life of building equipment, enhancing the value of commercial buildings. Intelligent interconnection of a building’s technical installations (lighting, heating, hot water, photovoltaic installations, etc.) not only allows for connected management of this equipment but also meets high energy efficiency criteria that indicate an increase in comfort and energy savings. With building automation, the technical installations of a building interact optimally. In this article, we will simulate an intelligent building based on the Cisco packet tracer software. To better manage the energy consumption of our project, we will focus on the processing of data in real-time, especially since we will have a massive amount of data generated by the sensors.
基于物联网(IOT)和大数据分析的数值分析,最大限度降低智能楼宇能耗
新一轮的高性能技术设备会产生海量数据。这些设备用于城市、家庭、楼宇、公司等。将它们的任务数字化的原因之一是,在过去几年里,人们对减少碳排放和提高能源效率以创建友好的生态系统和保护自然产生了兴趣。其中一个原因是数据爆炸。在部署了这些新设备后,人们注意到使用其他能源来实施新设备组件的情况显著增加。最重要的是,这些智能设备的互联是物联网(IoT)的核心概念。这一领域拓宽了楼宇管理系统(也称为智能电网)与设备互联的可能性,以实现更好的能源管理。此外,只有在对大量数据进行组织和分析之后,才能实现其潜力。大数据的实时管理和维护对于改善楼宇能源管理至关重要。大数据分析的好处不仅仅在于节省电费。它可以为楼宇用户提供舒适度,延长楼宇设备的使用寿命,提升商业楼宇的价值。楼宇技术装置(照明、供暖、热水、光伏装置等)的智能互联不仅可以实现这些设备的互联管理,还能满足高能效标准,从而提高舒适度并节约能源。有了楼宇自动化,楼宇内的技术设备就能实现最佳互动。在本文中,我们将以思科数据包跟踪软件为基础,模拟一座智能楼宇。为了更好地管理项目的能源消耗,我们将重点关注数据的实时处理,特别是因为我们将拥有由传感器产生的大量数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Automation, Mobile Robotics and Intelligent Systems
Journal of Automation, Mobile Robotics and Intelligent Systems Engineering-Control and Systems Engineering
CiteScore
1.10
自引率
0.00%
发文量
25
期刊介绍: Fundamentals of automation and robotics Applied automatics Mobile robots control Distributed systems Navigation Mechatronics systems in robotics Sensors and actuators Data transmission Biomechatronics Mobile computing
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