Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization

Turan Göktuğ Altundoğan; Mehmet Karaköse

Makale detayları

Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization

Yazarlar:

Turan Göktuğ Altundoğan | Mehmet Karaköse

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering | Electronics | Sensors and Digital Hardware (Other) | Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.133-145

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309689

pISSN:

1308-9080

Anahtar kelimeler:

Özet:

 With the widespread use of wireless communication technologies and IoT applications, researchers are developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength RSSI values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.

 With the widespread use of wireless communication technologies and IoT applications, researchers are developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength RSSI values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.

 With the widespread use of wireless communication technologies and IoT applications, researchers are developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength RSSI values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.

 Kablosuz iletişim teknolojilerinin ve IoT uygulamalarının yaygınlaşmasıyla birlikte araştırmacılar, WiFi sinyallerini iç mekân konum tespiti için kullanan yaklaşımlar geliştirmektedir. Bu çalışmada WiFi sinyal gücü RSSI değerlerine dayalı erişim noktalarının ağırlıklı görünürlük matrisleri oluşturularak sezgisel optimizasyon tabanlı yöntemlere dayalı iç mekan konumlandırma işlemi gerçekleştirilmiştir. Önerilen yöntemde, PSO ve GA yaklaşımları, görünürlük ağırlık matrislerine dayalı ortak bir uygunluk fonksiyonu kullanarak mobil kullanıcının konumunu belirler. Önerilen yöntem, RSSI aralıklarına dayalı konum aralıklarının belirlendiği sanal bir senaryo üzerinde test edilmiştir. Her iki sezgisel optimizasyon yöntemi farklı kriterlere göre karşılaştırılmış ve GA tabanlı yöntem için maksimum 3m, PSO tabanlı yöntem için maksimum 1,5m hata ile konumlandırma işlemi gerçekleştirilmiştir.

Makale detayları

Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization

Yazarlar:

Turan Göktuğ Altundoğan | Mehmet Karaköse

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering | Electronics | Sensors and Digital Hardware (Other) | Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.133-145

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309689

pISSN:

1308-9080

WiFi Indoor Positioning

Visibility Graphs

PSO

GAWiFi

Kapalı Alan Konumlandırma

Görünürlük Grafları

PSO

GA

Sayı

Makale detayları

Yazarlar: Turan Göktuğ Altundoğan | Mehmet Karaköse

Yayıncı: Fırat University

Ana Başlıklar: Engineering | Electronics | Sensors and Digital Hardware (Other) | Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Dergi: Turkish Journal of Science and Technology Vol.19 Issue 1, pp.133-145

Belge Tipi: Makale

Yayın Tarihi: 3/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001309689

pISSN: 1308-9080

Sayı

Yazarlar:

Turan Göktuğ Altundoğan | Mehmet Karaköse

Yayıncı:

Fırat University

Ana Başlıklar:

Engineering | Electronics | Sensors and Digital Hardware (Other) | Wireless Communication Systems and Technologies (Incl. Microwave and Millimetrewave)

Dergi:

Turkish Journal of Science and Technology Vol.19 Issue 1, pp.133-145

Belge Tipi:

Makale

Yayın Tarihi:

3/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001309689

pISSN:

1308-9080