Real-time artificial intelligence-powered multimodal drowsiness detection system in domains e.g. automotive driving, has alert mechanism for activating visual, auditory or haptic alerts when drowsiness is detected with adaptive alerting intensity
	GHOSH R K; MUKHERJEE S; NAYAK N C; BISWAS S; KUMAR C; TALUKDER S
	2025-04-08
专利权人	UNIV KOLKATA BRAINWARE (UYKO-Non-standard)
申请日期	2025-04-08
专利号	IN202531034318-A
成果简介	NOVELTY - The system has a camera which is configured to capture real-time facial data of an individual to monitor eye blink rate, yawning frequency, and head movement. An artificial intelligence (AI)-based processing unit is configured to analyze the captured facial data using deep learning algorithms to detect signs of drowsiness. Physiological sensors are integrated to monitor heart rate, heart rate variability, and skin temperature for additional drowsiness indicators. A behavioral analytics module is configured to analyze steering behavior or other behavioral patterns indicative of fatigue. An alert mechanism that activates visual, auditory, or haptic alerts when drowsiness is detected with adaptive alerting intensity. USE - Real-time AI-powered multimodal drowsiness detection system in domains e.g. automotive driving, industrial work environments, healthcare settings, transportation, healthcare and industrial operations. Can also be used in places e.g. construction sites, manufacturing facilities and chemical plants. ADVANTAGE - The system adapts to individual user behaviors, offers a non-invasive, scalable and highly accurate solution for proactive fatigue management, reduces false positives, the risk of accidents and unnecessary alerts, enhances overall safety and productivity, detects and manages drowsiness and fatigue in individuals across diverse environments, integrates advanced technologies e.g. computer vision, deep learning, physiological signal processing and behavioral analytics, monitors and assesses the alertness levels of individuals, enables real-time detection of fatigue-induced impairment, facilitates proactive safety measures, ensures operational efficiency, effective and real-time drowsiness detection and enhanced detection accuracy, avoids injuries and fatalities, incorporates high-resolution cameras to capture facial expressions e.g. eye blink rate, yawning frequency and head movement, provides accurate and reliable drowsiness detection for public safety and operational efficiency and insight into the individual's state of fatigue, processes the visual and behavioral data to classify the individual alertness level, enables timely detection of early signs of drowsiness or fatigue, learns from individual behavioral patterns and environmental factors continuously, allows real-time data sharing and predictive fatigue management, promotes safety and productivity across multiple sectors, identifies drowsiness and issue timely alerts proactively and ensures that individuals are intervened before safety or the safety of others is compromised. DESCRIPTION OF DRAWING(S) - The drawing shows a flow chart illustrating the operation of real-time AI-powered multimodal drowsiness detection system.
IPC 分类号	A61B-005/00 ; A61B-005/18 ; G06N-003/045 ; G06N-003/08 ; G06V-040/16
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13188
专题	中国科学院新疆生态与地理研究所
作者单位	UNIV KOLKATA BRAINWARE (UYKO-Non-standard)
推荐引用方式 GB/T 7714	GHOSH R K,MUKHERJEE S,NAYAK N C,et al. Real-time artificial intelligence-powered multimodal drowsiness detection system in domains e.g. automotive driving, has alert mechanism for activating visual, auditory or haptic alerts when drowsiness is detected with adaptive alerting intensity. IN202531034318-A[P]. 2025.

条目包含的文件
条目无相关文件。

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。