A Prototype Model of Monitoring Energy Consumption and Optimizing Distribution of Smart Buildings

A. Shalaby, M. Sidhu, W. C. Tan, Low Zhia Wei, Chua Jing Yong, Lee Yun Xi
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Abstract

Given the upcoming post-pandemic times, there are more universities considering adopting the hybridization model. As such, not all the facilities and building utilities will be fully utilized as only half of the student population will be expected, thus wasting the campus's energy consumption. An intelligent management system can be implemented into smart campuses to reduce the overall electrical bills to adapt to the hybrid education model. The research was then conducted on existing prior work around intelligent buildings and energy optimization. It was found that many of the energy optimization models utilized an IoT application highly specific to the designed IoT system only. This inspired developing an open source generalized IoT application to provide two-way communication between the energy optimization models and IoT devices. This would allow researchers to test their intelligent energy optimization models without building a support application from scratch. During the development phase, Firebase and open-source Chart JS were used to create an interactive web application with features including a dashboard, insightful data analysis, and remote-control features to be applied in a smart campus. A successful connection was established with a Raspberry Pi-based IoT system, where data could be stored and retrieved from the database into the web application. The second phase is going to be implementation of AI model which is currently in progress and being trained to fulfill the required criteria.
智能建筑能耗监测与优化分配的原型模型
考虑到即将到来的后大流行时代,越来越多的大学正在考虑采用杂交模式。因此,并不是所有的设施和建筑设施都能得到充分利用,因为预计只有一半的学生人口会被利用,从而浪费了校园的能源消耗。在智慧校园中实施智能管理系统,降低整体电费,适应混合式教育模式。然后,对围绕智能建筑和能源优化的现有先前工作进行了研究。研究发现,许多能源优化模型只利用了高度特定于所设计的物联网系统的物联网应用。这启发了开发一个开源的通用物联网应用程序,以提供能源优化模型和物联网设备之间的双向通信。这将允许研究人员测试他们的智能能源优化模型,而无需从头开始构建支持应用程序。在开发阶段,使用Firebase和开源Chart JS创建了一个交互式web应用程序,其功能包括仪表板,有洞察力的数据分析和远程控制功能,将应用于智能校园。与基于树莓派的物联网系统建立了成功的连接,数据可以从数据库中存储和检索到web应用程序。第二阶段将是人工智能模型的实施,该模型目前正在进行中,并正在接受培训,以满足所需的标准。
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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