Usage of Artificial Intelligence in Smart Tourism: A CNN-based Landmark Classification for Diyarbakir Province

Öz

The integration of artificial intelligence (AI) in the tourism sector has emerged as a transformative approach to enhance the travel experiences and promote regional attractions. This study explores the application of AI in smart tourism by developing a convolutional neural network (CNN)-based landmark classification system for Diyarbakır Province, a culturally rich region in South-East Turkey. The method specifically focuses on classifying images of five popular landmarks in Diyarbakır, leveraging state-of-the-art AI techniques to enhance regional visibility and tourist engagement. To achieve this, a pre-trained CNN model, namely AlexNet, was fine-tuned for the landmark classification task. By adapting the parameters of AlexNet to the specific dataset, the model was optimized for improved feature extraction and classification accuracy for totally 5 classes (places). The proposed framework was evaluated using a carefully curated dataset, yielding a remarkable 97.5% classification accuracy on the test set. The performance of the proposed model highlights the reliability and effectiveness of the methodology in accurately identifying landmarks, even with complex architectural and environmental features. These results can concretely contribute to both academic research and practical applications by providing a lightweight and accurate model that can be embedded into mobile travel applications or digital tourism platforms for real-time landmark recognition, enhancing tourist engagement and regional visibility.

Anahtar Kelimeler

• Smart tourism
• artificial intelligence
• deep learning
• landmark classification

Akıllı Turizmde Yapay Zeka Kullanımı: Diyarbakır İli için Evrişimsel Sinir Ağı Tabanlı Bir Turistik Yer Sınıflandırması

Öz

Yapay zekanın turizm sektörüne entegrasyonu, seyahat deneyimlerini geliştirmek ve bölgesel cazibe merkezlerini tanıtmak için dönüştürücü bir yaklaşım olarak ortaya çıkmıştır. Bu çalışma, Türkiye'nin Güneydoğusunda yer alan kültürel açıdan zengin bir bölge olan Diyarbakır ili için Evrişimli Sinir Ağı (CNN) tabanlı bir turistik yer noktası sınıflandırma sistemi geliştirerek akıllı turizmde yapay zeka uygulamasını araştırmaktadır. Yöntem, özellikle bölgesel görünürlüğü ve turist katılımını artırmak için en son yapay zeka tekniklerinden yararlanarak, Diyarbakır'daki beş popüler turistik yer görüntülerini sınıflandırmaya odaklanmaktadır. Bunu başarmak için, AlexNet adlı önceden eğitilmiş bir CNN modeli, turistik yer sınıflandırma görevi için ince ayarlanmıştır. AlexNet'in parametrelerini belirli veri setine uyarlayarak, model toplam 5 sınıf (yer) için iyileştirilmiş özellik çıkarma ve sınıflandırma doğruluğu için optimize edilmiştir. Önerilen model, dikkatlice düzenlenmiş bir veri seti kullanılarak değerlendirilmiş ve test setinde %97,5’lik dikkate değer bir sınıflandırma doğruluğu elde edilmiştir. Önerilen modelin performansı, karmaşık mimari ve çevresel özelliklere sahip olsa bile turistik yer noktalarını doğru bir şekilde tanımlamada metodolojinin güvenilirliğini ve etkinliğini vurgulamaktadır. Bu çalışmanın sonuçları, mobil seyahat uygulamalarına entegre edilebilecek hafif ve doğru bir model sunarak, hem akademik çalışmalara hem de turistik etkileşimi arttırabilecek pratik uygulamalara katkı sağlamaktadır.

Anahtar Kelimeler

• Akıllı turizm
• yapay zeka
• derin öğrenme
• turistik yer sınıflandırma

Kaynakça

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