AI-Powered Tactile Glove for Human Recognition in Low-Visibility Fire Environments
Open Access
Article
Conference Proceedings
Authors: Feng Jiang, Yongshi Guo, Jianhua Yan
Abstract: Firefighters and rescue robots often face extremely low-visibility environments during fire emergencies, making it difficult and dangerous to locate and save victims. To address this challenge, we developed an AI-powered glove capable of automatically recognizing human body parts without requiring visual input or manual guidance.The system integrates 22 flexible, fire-resistant cermet matrix sensors onto a heat-resistant glove, forming a tactile sensing array. When the glove comes into contact with different body parts—such as the shoulder, arm, chest, or abdomen—it detects distinct pressure patterns that generate unique electrical signal distributions. These signals are then analyzed by a deep learning model trained to identify specific human body parts with high accuracy.This fusion of tactile sensing and artificial intelligence enables precise human recognition in low-visibility fire conditions, enhancing the safety and effectiveness of rescue operations. The project demonstrates how AI can be seamlessly integrated into real-world problem-solving to support first responders in life-saving missions.
Keywords: AI, sensor, recognition
DOI: 10.54941/ahfe1007077
Cite this paper:
Downloads
2
Visits
5


AHFE Open Access