Enhancing Urban Traffic Management Through Deep Learning: A Comprehensive Approach to Intelligent Infrastructure Optimization

NT Binh - … of Sustainable Technology and Infrastructure for …, 2024 - research.tensorgate.org
Urban traffic congestion remains a persistent and growing challenge in cities worldwide,
driven by rapid urbanization and increasing vehicle ownership. Traditional traffic …

Developing Robust Deep Learning Models for Intelligent Infrastructure: Addressing Scalability, Security, and Privacy Challenges

SC Amarasinghe - Applied Research in Artificial Intelligence and …, 2024 - researchberg.com
The integration of deep learning models into intelligent infrastructure systems presents
significant opportunities for enhancing efficiency, safety, and resilience in urban …

Deep Reinforcement Learning for Adaptive Traffic Signal Control in Smart Cities: An Intelligent Infrastructure Perspective

NBA Rahman - Applied Research in Artificial Intelligence and …, 2024 - researchberg.com
The rise of smart cities has necessitated the development of advanced traffic management
systems that can adapt to dynamic urban traffic conditions. Traditional traffic signal control …

Utilizing Deep Learning for Automated Inspection and Damage Assessment in Civil Infrastructure Systems

SFBA Manaf - Applied Research in Artificial Intelligence and …, 2024 - researchberg.com
The integrity of civil infrastructure systems, including bridges, roads, tunnels, and buildings,
is critical for public safety and economic stability. Traditional methods of inspection and …

Implementing Deep Learning for Autonomous Infrastructure Management: From Predictive Analytics to Proactive Maintenance

P Bhattarai - Tensorgate Journal of Sustainable Technology …, 2024 - research.tensorgate.org
The management of urban infrastructure is a complex task involving monitoring,
maintenance, and upgrading of various components such as roads, bridges, and utilities …

Deep Learning-Driven Anomaly Detection for Intelligent Transportation Networks: A Multi-Modal Data Fusion Approach

N Priyadarshini - Tensorgate Journal of Sustainable …, 2024 - research.tensorgate.org
The proliferation of data from diverse sources such as sensors, cameras, and vehicle
telemetry has ushered in an era where Intelligent Transportation Networks (ITNs) can be …

A Holistic Analysis of the Impact of Integrated Energy Efficiency Measures on Greenhouse Gas Emission Reduction in Industrial Manufacturing Processes

I Sari - Journal of Sustainable Urban Futures, 2023 - neuralslate.com
Industrial manufacturing processes are significant contributors to global greenhouse gas
(GHG) emissions, accounting for a substantial portion of carbon dioxide (CO₂) and other …

Exploring the Potential of Artificial Intelligence to Enhance Energy Efficiency in Smart Grid Systems: A Detailed Review and Future Directions

A Tan - Journal of Sustainable Urban Futures, 2023 - neuralslate.com
The rapid evolution of energy infrastructure, driven by increasing energy demands and the
integration of renewable energy sources, necessitates the transformation of traditional …

Enhancing the Quality of Ambulance Crew Work by detecting Ambulance Equipment using Computer Vision and Deep Learning

J Hussain, N Al-Masoody, A Alsuraihi… - … , Technology & Applied …, 2024 - etasr.com
Ambulance crews play an important role in responding quickly to emergencies and rescuing
patients by providing appropriate treatment. Typically, fully equipped emergency vehicles …

Exploring the Role of Deep Learning in Developing Intelligent Urban Mobility Solutions for Sustainable Cities

TTT Trang - Journal of Sustainable Technologies and …, 2024 - publications.dlpress.org
The rapid urbanization of cities worldwide has led to significant challenges in urban mobility,
including traffic congestion, increased emissions, and inefficient public transportation …