ABSTRACT. The purpose of the paper is to explore how spatial cognition and sensor data processing algorithms, immersive visualization and smart city software systems, and visual modeling and big data-driven planning technologies can drive urban digital twins in smart and environmentally sustainable cities. Deep learning and spatial cognition algorithms, digital twin simulation modeling and deep learning-based sensing technologies, and virtual modeling and simulation tools can redefine simulated 3D environments and digital twin cities.

Keywords: computer vision; digital twin smart city; spatial computing; big data mapping and processing; immersive 3D virtual urban environments

How to cite: Bonciu, C. I., Yong, S. W. (M.)., Bîgu, A.-M., Abdullah, J. (2026). “Computer Vision and Digital Twin Smart City Algorithms, Deep Learning-based Sensing and Spatial Computing Technologies, and Big Data Mapping and Processing Tools in Immersive 3D Virtual Urban Environments,” Geopolitics, History, and International Relations 18(1): 47–58. doi: 10.22381/GHIR18120264.

Received 11 February 2026 • Received in revised form 22 June 2026
Accepted 26 June 2026 • Available online 30 June 2026