Integrating AI and UAV Technologies for Enhanced and Workplace Safety

Abstract

The integration of artificial intelligence (AI) and unmanned aerial vehicle (UAV) technologies presents a significant advancement in enhancing safety in traffic, workplace, and healthcare environments. This study explores the application of AI-driven computer vision algorithms in UAVs to detect and mitigate risks associated with substance abuse, fatigue, and health impairments. Utilizing sophisticated image processing techniques, such as edge detection and support vector machine (SVM) algorithms, drones are equipped to autonomously monitor and analyze ocular characteristics and facial expressions of individuals. The research employs a mobile phone camera and Python-based libraries to conduct real-time assessments, providing critical data to medical and industrial professionals. The study demonstrates the potential of drones to enhance safety by checking sobriety and monitoring worker health. The experimental setup includes a detailed workflow for real-time video detection and facial analysis, leveraging pre-trained models and convolutional neural networks. The results confirm the effectiveness of this approach, highlighting significant progress in AI and UAV technology. Future work aims to transition these innovations from laboratory conditions to practical, real-world applications, continuously enhancing the algorithms and expanding their applicability across various safety-critical scenarios.