Challenges and Innovations in YOLO-Based Drone Detection for the Industry 5.0 Revolution-Reference-Cited by-同舟云学术

Challenges and Innovations in YOLO-Based Drone Detection for the Industry 5.0 Revolution

Published:2024-05-31 Issue: Volume: Page:59-74
ISSN:2327-0411
Container-title:Advances in Computational Intelligence and Robotics
language:
Short-container-title:

Author:

Dankan Gowda V.¹^ORCID,Jagtap Madan Mohanrao²^ORCID,Tarambale Manoj³,Prasad K. D. V.⁴^ORCID,Rayar Vijay⁵^ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, B.M.S. Institute of Technology and Management, Karnataka, India

2. Department of Operations Management, Symbiosis Institute of Operations Management, Symbiosis International University (Deemed), Pune, India

3. Pune Vidhyarthi Griha's College of Engineering and Technology, University of Pune, India

4. Symbiosis Institute of Business Management, Symbiosis International University (Deemed), India

5. Dr. M.S. Sheshgiri College of Engineering and Technology, KLE Technological University, Belagavi, India

Abstract

The Industry 5.0 revolution emerges as an amalgamation of advanced technological systems with human touch onset. In this transformative time, drone technologies have become essential pieces for varied uses and their detection poses a reliable identification. Several challenges that arise when implementing YOLO-based models for drone detection are thoroughly analyzed in this chapter. It clarifies the advanced innovations that got introduced to address these challenges making effective drone detection in the framework of Industry 5.0. By studying practical cases, innovations in deep learning and YOLO models' adaptability, the chapter provides an overview of the present situation and potential future for drone detection as we move into a new stage of industrial progress.

Publisher

IGI Global

Reference30 articles.

1. Intelligent Drone-based IoT Technology for Smart Agriculture System

2. Technological Modernizations in the Industry 5.0 Era: A Descriptive Analysis and Future Research Directions

3. An Innovative Air Quality Monitoring System based on Drone and IoT Enabling Technologies

4. The IoT based automate landing system of a drone for the round-the-clock surveillance solution;H.Chae;2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM),2015

5. An Overview of Drone Applications in the Construction Industry