Transfer Öğrenme Kullanılarak Mobil Uygulama Tabanlı İç Mekan Yönlendirme Sistemi

Year 2024, Volume: 12 Issue: 4, 2245 - 2261, 23.10.2024

Nesrin Aydın Atasoy , Ebru Çıracı

https://doi.org/10.29130/dubited.1397767

Abstract

Günümüzde hastaneler, alışveriş merkezleri, kapalı otoparklar ve kamu binaları gibi karmaşık çok katlı mimariye sahip yerlerde iç mekan yönlendirmesi geleneksel olarak tabelalar veya sabit konumdaki cihazlar kullanılarak gerçekleştirilmektedir. Literatürü incelediğimizde genel olarak belirli ihtiyaçlara yönelik iç mekan yönlendirme çalışmalarının yapıldığı görülmektedir. Yönlendirme sistemlerinin sabit olması ve tabelaların etkili bir araç olmaması bu çalışmanın motivasyonunu oluşturmaktadır. Bu çalışmada, mobil cihaz kullanılarak donanımdan bağımsız ve diğer iç mekanlara uyarlanabilen, görüntü tabanlı bir mobil uygulama gerçekleştirilmiştir. Uygulama temel olarak iki bölümden oluşmaktadır. İlk bölümde, ilk mağaza konumunu belirlemek için transfer öğrenme tabanlı MobileNetV2 mimarisi kullanıldı. Önerilen model, kameradan alınan mağaza tabela görüntüsünü %96 başarı ile tespit etmektedir. İkinci bölümde kullanıcı Dijkstra algoritması kullanılarak hedefe başarılı bir şekilde yönlendirilmektedir. Geliştirilen mobil uygulama ile kullanıcı aynı veya farklı katlardaki hedeflere zaman kaybetmeden ve kimseye sormadan en hızlı şekilde ulaşabilmektedir. Uygulama gerçek zamanlı olarak bir alışveriş merkezinde denenmiş ve başarılı sonuçlar alınmıştır.

Keywords

Dijkstra algoritması, İç mekan navigasyon, Transfer öğrenme

Mobile Application Based Indoor Routing System Using Transfer Learning

Abstract

Nowadays, indoor routing in places with complex multi-storey architecture such as hospitals, shopping malls, parking garages and public buildings is traditionally carried out using signage or devices in a fixed position. When we examine the literature, it is generally seen that indoor orientation studies for certain needs are seen. The fact that the routing systems are fixed, and the signage is not an effective tool constitutes the motivation of this study. In this study, an image-based mobile application that is hardware-independent and adaptable to other interior spaces has been implemented using a mobile device. The application basically consists of two parts. In the first part, transfer learning based MobileNetV2 architecture is used to determine the initial store location. The proposed model detects the store signage image taken from the camera with 96% success. In the second part, the user is successfully guided to the target using the Dijkstra algorithm. With the developed mobile application, the user can reach the targets on the same or different floors in the fastest way without wasting time and without asking anyone. The application was tried in real time in a shopping center and successful results are obtained.

Keywords

Dijkstra algorithm, Indoor navigation, Transfer learning

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