Touchless Gesture-Based Human-Machine Interaction for Industrial Safety and Automation

Recent research explores the integration of computer vision to advance industrial automation, specifically focusing on touchless gesture control and safety monitoring. The sources describe systems designed to replace physical interfaces with hand gestures for controlling Programmable Logic Controllers (PLCs) and collaborative robots, thereby enhancing hygiene and worker safety in hazardous zones [1][4]. These technological advancements utilize deep learning models like LSTM and 3D Convolutional Neural Networks to ensure real-time recognition accuracy [1][4]. Nevertheless, user-centered evaluations highlight barriers such as the absence of tactile feedback and social concerns regarding the professional perception of gesturing [2]. Complementing these control interfaces, the sources also propose action-aware safety frameworks that automatically verify Personal Protective Equipment (PPE) compliance based on the specific task being performed [3]. Collectively, these contributions illustrate a shift toward more intuitive, hands-free industrial environments that prioritize both operational efficiency and proactive risk mitigation.