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Dr. Rashmita Padhi is an Assistant Professor in the Department of Computer Science and Applications at Utkal University, Odisha, India. Her research interests include artificial intelligence, deep learning, data analytics, and intelligent transportation systems.
Deep learning has emerged as a revolutionary technology for logistics, transportation, and mobility solutions by facilitating intelligent automation, predictive analytics, and real-time decision-making inside intricate transportation ecosystems. Organisations can enhance traffic management, demand forecasting, route planning, fleet operations, autonomous driving, and public transportation services with sophisticated deep learning architectures, including CNNs, LSTMs, Transformers, and hybrid neural networks. The amalgamation of deep learning with IoT, cloud computing, edge intelligence, digital twins, and linked mobility platforms improves operational efficiency, safety, sustainability, and customer experience. Despite persistent challenges concerning data quality, computational complexity, cybersecurity, interpretability, and infrastructure, continuous advancements in explainable AI, federated learning, autonomous systems, and smart mobility technologies are propelling the evolution of next-generation transportation solutions. Future logistics and mobility ecosystems powered by deep learning will be essential for facilitating efficient supply chains, robust transportation networks, diminished environmental impact, and sustainable urban mobility.