Geospatial Neural Networks: Enhancing Smart City Through Location Intelligence
Year: 2025
Type: conference-paper
Abstract: Large cities are increasingly leveraging technology to enhance urban living and operational efficiency. The emergence of Geospatial Neural Networks (GeoNNs) offers a novel solution to improve smart city initiatives through advanced location intelligence. By effectively integrating both spatial and temporal data, GeoNNs can learn from the complexities of urban environments. This innovative method enhances applications in areas such as traffic management, environmental monitoring, and urban planning. Utilizing graph neural networks, our approach captures the intricate interactions among urban elements, which significantly aids in informed decision-making. GeoNNs also support real-time data processing, essential for responding dynamically to the demands of smart city infrastructure.
Author: Junjie Chen
Institution: Columbia University
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4410855340