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AIFIT 2021 : AI for Future Intelligent Transportation: Smarter and Greener Design


When Feb 15, 2021 - May 31, 2021
Where India
Abstract Registration Due Feb 15, 2021
Submission Deadline Apr 30, 2021
Notification Due May 15, 2021
Final Version Due May 31, 2021

Call For Papers

Transport is the biggest source of air and noise pollution. Emission of CO2 is a major source for climate change and traffic noise. The ecological effect of transport is huge in light of the fact that transport is a significant user of energy, and consumes the vast majority of the world's oil. This makes air contamination, including nitrous oxides and particulates, and is a huge supporter of an global-warming boost through discharge of carbon dioxide. The major key issues of transportation are car pollution, low emission zones, vehicle emission testing and aviation pollution. The fast advancement of Artificial Intelligence ( AI) advances provides unparalleled opportunities to boost the efficiency of various industries and companies, including the transport sector.The inventions developed by AI include highly sophisticated methods of computation that replicate the way the human brain operates. The intention of the application of AI in the transportation sector is to overcome the challenges of growing demand for travel, CO2 emissions, safety issues and environmental deterioration. In view of the availability in this digital age of a large amount of primary and secondary data sources and AI, it has become more feasible to answer these issues in a more efficient and successful way.

Through new inventions from AI, machine learning, deep learning, and the Internet of things (IoT), expert system, neutral networks , smart sensors, drones etc come out to be the most often used techniques for pollution control. Some of the examples of AI techniques that are forcing their way to transportation sector includes Artificial Neural Networks (ANN), Genetic algorithms (GA), Simulated Annealing (SA), Artificial Immune system (AIS), Ant Colony Optimiser (ACO) and Bee Colony Optimization (BCO) and Fuzzy Logic Model (FLM). Artificial intelligence makes self-governing autos conceivable and encourages them to navigate, yet additionally do as such as proficiently as would be prudent. This book brings in the best of Artificial Intelligence techniques and it will sketch how it can be implemented to provide solutions to mitigate, minimize and control pollution. Highlighting a wide range of topics in AI techniques, this book is ideal for AI researchers, AI innovators, machine learning engineers, scientist from deep learning community, academicians, students.

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