Smart Journey in Istanbul: A Mobile Application in Smart Cities for Traffic Estimation by Harnessing Time Series
Yazarlar (1)
Dr. Öğr. Üyesi Senem TANBERK Huawei R&D İstanbul, Türkiye
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Tebliğ/Bildiri
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Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| Kongre Adı | 2023 Innovations in Intelligent Systems and Applications Conference (ASYU) | ||
| Kongre Tarihi | 11-10-2023 / 11-10-2023 | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | |
| Bildiri Linki | https://ieeexplore.ieee.org/abstract/document/10296669/ | ||
| UAK Araştırma Alanları |
Eğitim Bilimleri
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| Özet |
| In recent decades, mobile applications (apps) have gained enormous popularity. Smart services for smart cities increasingly gain attention. The main goal of this proposed research was to present a new artificial intelligence (AI)powered mobile app on Istanbul’s traffic congestion forecast using traffic density data. It addresses the research question using time series approaches (long short-term memory (LSTM), Transformer, and eXtreme Gradient Boosting (XGBoost)) based on past data over the traffic load dataset combined with meteorological conditions. While previous studies were limited to direct Istanbul traffic forecasting, in this study, we focused on district-based traffic forecasting that can be queried with a mobile app. The proposed pipeline was tested on the summarized Istanbul traffic dataset for 6 main distinct districts (Fatih, Buyukcekmece, Atasehir, Kagithane, Tuzla, and Bagcilar). Analysis of the simulation … |
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