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Edge Computing and Machine Learning Integration for Autonomous Electrical Vehicles
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Author(s): Mallireddy Naresh (Department of Computer Science Engineering, Aditya College of Engineering, Surampalem, India), D. Abdus Subhahan (Department of Computer Science Engineering, B V Raju Institute of Technology, Narsapur, India), Vivek Narula Narula (Department of Management, Shri Venkateshwara University, Gajraula, India), Dayana K. Roslin (Department of Computer Science Engineering, R.M.D. Engineering College, Thiruvallur, India), Shaweta Narula (Department of Electronics and Telecommunication, Nutan College of Engineering and Research, Pune, India)and Sampath Boopathi (Department of Mechanical Engineering, Muthayammal Engineering College, Namakkal, India)
Copyright: 2024
Pages: 29
Source title:
Solving Fundamental Challenges of Electric Vehicles
Source Author(s)/Editor(s): Mazhar Hussain Shaik (Middle East College, Oman)
DOI: 10.4018/979-8-3693-4314-2.ch005
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Abstract
The growth of autonomous small aircraft and drones has significantly impacted the aviation industry. This chapter provides a comprehensive guide for researchers, engineers, and enthusiasts interested in developing intelligent aerial systems. It also covers the fundamentals of edge computing and machine learning, the evolution of autonomous systems, and the design and implementation of edge computing architectures in small aircraft. The machine learning algorithms' applications in navigation, path planning, obstacle avoidance, and decision-making have also been discussed. The security and privacy of autonomous systems and ethical considerations in flight control have been illustrated. The project's future trends and emerging technologies are also elaborated.
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