Enhancing Urban Sustainability: The Role of AI-Driven Transportation Systems in Reducing Carbon Footprints
Nash et al. · 2025-08-01
This study shows that AI-driven transportation systems can significantly reduce urban carbon emissions and improve energy efficiency by optimizing routes, easing congestion, and enhancing public transit, while offering policy guidance for sustainable implementation.
Source identity and required public metadata were editorially reviewed on 2026-09-15.
Nash et al.. 2025-08-01. Enhancing Urban Sustainability: The Role of AI-Driven Transportation Systems in Reducing Carbon Footprints. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1602&context=amcis2025 (AI & Environment Resource Hub; record paper-303; collection snapshot 2026-09-15).
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Included in the original Scientific Paper collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
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Source sheet: Scientific Paper · Row 307 · Original ID: paper-303.
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Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure; Transport and logistics
As the global climate crisis intensifies, governments, industries, and communities worldwide face an increasing pressure to accelerate efforts toward achieving Net Zero emissions. Although the rapid adoption of Artificial Intelligence (AI) is transforming the Information and Communications Technology (ICT) landscape, it presents both opportunities and challenges. While AI offers powerful tools to optimize energy use, […]
Next G Alliance
Shared topics: Cross-cutting sustainability; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure; Transport and logistics
By the end of this course, you will be able to explain how data centers power AI‑driven decarbonization across the global economy and why sustainable digital infrastructure is foundational to achieving net‑zero goals. You will learn how AI, enabled by cloud and edge data centers, supports clean energy grids, optimizes buildings and manufacturing operations, and accelerates electrified, efficient transportation systems
Coursera
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
AI and ML optimize optoelectronic systems for sustainability by enhancing energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities while also advancing ocean optics and photonics for marine ecosystem monitoring and climate change mitigation.
Library Progress International
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity; Climate and greenhouse gases; Built environment and infrastructure
Open access book assembling cutting-edge research exploring AI infrastructures and sustainability across media and communication, covering AI-driven media, energy consumption, climate change, and policies/ethics.
