Optimization of User Comfort Index for Ambient Intelligence Using Dynamic Inertia Weight Artificial Bees Colony Optimization Algorithm

Citation

Baharudin, Farah Nur Arina and Ab Aziz, Nor Azlina and Abdul Malek, Mohamad Razwan and Ibrahim, Zuwairie (2021) Optimization of User Comfort Index for Ambient Intelligence Using Dynamic Inertia Weight Artificial Bees Colony Optimization Algorithm. Lecture Notes in Mechanical Engineering. pp. 351-363. ISSN 2195-4356

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Abstract

Ambient intelligence (AmI) aims to bring intelligence to human daily lives and making the environment more sensitive and comfortable by applying computational intelligence, sensors and sensors networks. The occupant’s comfort can be measured using the user comfort index. A user comfort index in an indoor environment can be affected by the temperature of the room, the illumination of the lighting and the indoor air quality. In this work, these parameters are optimized using dynamic inertia weight artificial bees colony (DIW-ABC) optimization algorithm. The inertia weight in DIW-ABC controls the exploration and exploitation of the colony. The findings show that the DIW-ABC achieved better performance than the original ABC. The optimized parameter can be feed to a controller to provide a room with ambient intelligence.

Item Type: Article
Additional Information: RiTA 2020-Proceedings of the 8th International Conference on Robot Intelligence Technology and Applications
Uncontrolled Keywords: Ambient intelligence, Artificial bees colony
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 04 Oct 2021 02:59
Last Modified: 21 Dec 2022 05:59
URII: http://shdl.mmu.edu.my/id/eprint/9634

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