https://zealpress.com/jms/index.php/ijrat <p>International Journal of Robotics and Automation Technology providing a platform to researchers, scientists, engineers and practitioners throughout the world to publish the most up-to-date accomplishment, upcoming challenges and thrilling applications in the field of Robotics and Automation Technology.</p> <p>This technology deals with the design, construction, operation, and application of robots as well as control systems for operating equipment such as machinery, processes in factories, boilers and heat treating ovens, switching in telephone networks, steering and stabilization of ships or aircraft and other applications with minimal or reduced human intervention.</p> Zeal Press en-US International Journal of Robotics and Automation Technology 2409-9694 https://zealpress.com/jms/index.php/ijrat/article/view/565 <p><strong>Abstract:</strong> This work aims to test the performance of the you only look once version 8 (YOLOv8) model for the problem of drone detection. Drones are very slightly regulated and standards need to be established. With a robust system for detecting drones the possibilities for regulating their usage are becoming realistic. Five different sizes of the model were tested to determine the best architecture size for this problem. The results indicate high performance across all models and that each model is to be used for a specific case. Smaller models are suited for lightweight system approaches where some false identification is tolerable, while the largest models are to be used with stationary systems that require the best precision.</p> Aleksandar Petrovic Nebojsa Bacanin Luka Jovanovic Jelena Cadjenovic Jelena Kaljevic Miodrag Zivkovic Milos Antonijevic Copyright (c) 2024 2024-05-22 2024-05-22 11 1 12 10.31875/2409-9694.2024.11.01