Edge Computing and Machine Learning Integration for Autonomous Electrical Vehicles-Reference-Cited by-同舟云学术

Edge Computing and Machine Learning Integration for Autonomous Electrical Vehicles

Published:2024-07-26 Issue: Volume: Page:99-127
ISSN:2328-8205
Container-title:Advances in Mechatronics and Mechanical Engineering
language:
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Author:

Naresh Mallireddy¹^ORCID,Subhahan D. Abdus²,Narula Vivek Narula³,Roslin Dayana K.⁴,Narula Shaweta⁵,Boopathi Sampath⁶^ORCID

Affiliation:

1. Department of Computer Science Engineering, Aditya College of Engineering, Surampalem, India

2. Department of Computer Science Engineering, B V Raju Institute of Technology, Narsapur, India

3. Department of Management, Shri Venkateshwara University, Gajraula, India

4. Department of Computer Science Engineering, R.M.D. Engineering College, Thiruvallur, India

5. Department of Electronics and Telecommunication, Nutan College of Engineering and Research, Pune, India

6. Department of Mechanical Engineering, Muthayammal Engineering College, Namakkal, India

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.

Publisher

IGI Global

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