Energy Efficient Temperature Control with Particle Swarm Optimization for Smart Buildings

Kim, Jeong Hyuk; Boo, Chang Jin; Kim, Ho-Chan

doi:10.4028/www.scientific.net/amr.711.518

Cited by 1 publication

(1 citation statement)

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“…PSO cannot work alone with sensors it needs a controller that can communicate with them. In [15] research, PSO is proposed to manage the energy consumption and efficiency in a smart building by managing the temperature. The PSO is utilized with a control horizon switching method to achieve optimal control, including the Time On Use (TOU) tariff, to calculate the energy costs.…”

Section: Ai Algorithmmentioning

confidence: 99%

Optimized Smart Energy Management System for Campus Buildings: A Conceptual Model

Shalaby

Sidhu

Tan

et al. 2023

ijaste

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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. Therefore, 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 will be then conducted on existing prior work which will be over-viewed in this paper in the area of 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 us with the aid of Particle Swarm Optimization (PSO) and LTMS AI model to design a fully automatic system capable of reducing the consumed power in campus with monitoring the past readings that can be accessed through a web app dashboard.

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Section: Ai Algorithmmentioning

confidence: 99%