Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm

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 i...

Full description

Bibliographic Details
Main Authors: Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Zuwairie, Ibrahim
Format: Conference or Workshop Item
Language:English
Published: Springer 2021
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/34333/
http://umpir.ump.edu.my/id/eprint/34333/1/Optimization%20of%20user%20comfort%20index%20for%20ambient%20intelligence.pdf
_version_ 1848824478831738880
author Farah Nur Arina, Baharudin
Nor Azlina, Ab. Aziz
Mohamad Razwan, Abdul Malek
Zuwairie, Ibrahim
author_facet Farah Nur Arina, Baharudin
Nor Azlina, Ab. Aziz
Mohamad Razwan, Abdul Malek
Zuwairie, Ibrahim
author_sort Farah Nur Arina, Baharudin
building UMP Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T03:13:40Z
format Conference or Workshop Item
id ump-34333
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T03:13:40Z
publishDate 2021
publisher Springer
recordtype eprints
repository_type Digital Repository
spelling ump-343332022-11-15T03:50:48Z http://umpir.ump.edu.my/id/eprint/34333/ Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm Farah Nur Arina, Baharudin Nor Azlina, Ab. Aziz Mohamad Razwan, Abdul Malek Zuwairie, Ibrahim QA76 Computer software T Technology (General) 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. Springer 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/34333/1/Optimization%20of%20user%20comfort%20index%20for%20ambient%20intelligence.pdf Farah Nur Arina, Baharudin and Nor Azlina, Ab. Aziz and Mohamad Razwan, Abdul Malek and Zuwairie, Ibrahim (2021) Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm. In: Lecture Notes in Mechanical Engineering; 8th International Conference on Robot Intelligence Technology and Applications, RiTA 2020 , 11-13 December 2020 , Virtual, Online. pp. 351-363.. ISSN 2195-4356 ISBN 978-981-16-4803-8 (Published) https://doi.org/10.1007/978-981-16-4803-8_35
spellingShingle QA76 Computer software
T Technology (General)
Farah Nur Arina, Baharudin
Nor Azlina, Ab. Aziz
Mohamad Razwan, Abdul Malek
Zuwairie, Ibrahim
Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title_full Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title_fullStr Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title_full_unstemmed Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title_short Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
title_sort optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
topic QA76 Computer software
T Technology (General)
url http://umpir.ump.edu.my/id/eprint/34333/
http://umpir.ump.edu.my/id/eprint/34333/
http://umpir.ump.edu.my/id/eprint/34333/1/Optimization%20of%20user%20comfort%20index%20for%20ambient%20intelligence.pdf