Indoor localization system using particle swarm optimization
Tracking the user location in indoor environment becomes substantial issue in recent research. Location based services have been used in many mobile applications as well as wireless sensor networks. One of the techniques that are used in localization systems is particle swarm optimization (PSO). Thi...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/66805/ http://psasir.upm.edu.my/id/eprint/66805/1/IICIST%202015-5.pdf |
| _version_ | 1848855671547625472 |
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| author | Alhammadi, Abdulraqeb Shaif Ahmed Hashim, Fazirulhisyam Shami, Tareq M. |
| author_facet | Alhammadi, Abdulraqeb Shaif Ahmed Hashim, Fazirulhisyam Shami, Tareq M. |
| author_sort | Alhammadi, Abdulraqeb Shaif Ahmed |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Tracking the user location in indoor environment becomes substantial issue in recent research. Location based services have been used in many mobile applications as well as wireless sensor networks. One of the techniques that are used in localization systems is particle swarm optimization (PSO). This technique is a stochastic optimization based on the movement and velocity of particles. In this paper, we introduce an algorithm using PSO for indoor localization system. The suggested algorithm is called circular PSO (CPSO) which depends on the distribution of the particles at each access point. The simulation results show the effectiveness of the suggest algorithm on average location error. |
| first_indexed | 2025-11-15T11:29:28Z |
| format | Conference or Workshop Item |
| id | upm-66805 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:29:28Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-668052019-03-04T00:33:25Z http://psasir.upm.edu.my/id/eprint/66805/ Indoor localization system using particle swarm optimization Alhammadi, Abdulraqeb Shaif Ahmed Hashim, Fazirulhisyam Shami, Tareq M. Tracking the user location in indoor environment becomes substantial issue in recent research. Location based services have been used in many mobile applications as well as wireless sensor networks. One of the techniques that are used in localization systems is particle swarm optimization (PSO). This technique is a stochastic optimization based on the movement and velocity of particles. In this paper, we introduce an algorithm using PSO for indoor localization system. The suggested algorithm is called circular PSO (CPSO) which depends on the distribution of the particles at each access point. The simulation results show the effectiveness of the suggest algorithm on average location error. 2015 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/66805/1/IICIST%202015-5.pdf Alhammadi, Abdulraqeb Shaif Ahmed and Hashim, Fazirulhisyam and Shami, Tareq M. (2015) Indoor localization system using particle swarm optimization. In: 1st ICRIL-International Conference on Innovation in Science and Technology (IICIST 2015), 20 Apr. 2015, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia. (pp. 574-577). |
| spellingShingle | Alhammadi, Abdulraqeb Shaif Ahmed Hashim, Fazirulhisyam Shami, Tareq M. Indoor localization system using particle swarm optimization |
| title | Indoor localization system using particle swarm optimization |
| title_full | Indoor localization system using particle swarm optimization |
| title_fullStr | Indoor localization system using particle swarm optimization |
| title_full_unstemmed | Indoor localization system using particle swarm optimization |
| title_short | Indoor localization system using particle swarm optimization |
| title_sort | indoor localization system using particle swarm optimization |
| url | http://psasir.upm.edu.my/id/eprint/66805/ http://psasir.upm.edu.my/id/eprint/66805/1/IICIST%202015-5.pdf |