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Ulzhan Bissarinova, Aidana Tleuken, Sofiya Alimukhambetova, Huseyin Atakan Varol and Ferhat Karaca
This paper introduces a deep learning (DL) tool capable of classifying cities and revealing the features that characterize each city from a visual perspective. The study utilizes city view data captured from satellites and employs a methodology involving...
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Fidel Lozano, Seyyedbehrad Emadi, Seyedmilad Komarizadehasl, Jesús González Arteaga and Ye Xia
The development of low-cost structural and environmental sensors has sparked a transformation across numerous fields, offering cost-effective solutions for monitoring infrastructures and buildings. However, the affordability of these solutions often come...
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Mazen A. Al-Sinan, Abdulaziz A. Bubshait and Zainab Aljaroudi
Recent advancements in machine learning (ML) applications have set the stage for the development of autonomous construction project scheduling systems. This study presents a blueprint to demonstrate how construction project schedules can be generated aut...
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Ioannis Nikolaou and Leonidas Anthopoulos
Contextual data are receiving increasing attention in Smart Cities as they enable the development and delivery of smart services for their citizens. The homogenization of contextual data flows has become an important topic for standardization bodies as t...
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Anas A. Makki and Ammar Y. Alqahtani
This study analyzes the barriers to developing smart cities (SCs) using the decision-making trial and evaluation laboratory (DEMATEL) approach. The primary objective is to identify, classify, and assess the main barriers hindering the progress of SCs. Th...
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