2014/07/09 by Monali Gulhane, Gulhane, Monali, P. S. Mohod +1 · 2 citations
Computer Science · Engineering · Medicine · Psychology · #Artificial intelligence #Computer science #Control (management) #Control system #Engineering #FOS: Computer and information sciences #Falling (accident) #Heart Rate Variability and Autonomic Control #Non-Invasive Vital Sign Monitoring #Other Computer Science (cs.OH) #Psychology #Real-time computing #SIGNAL (programming language) #Simulation #Sleep (system call) #Sleep and Work-Related Fatigue #State (computer science) #cs.OH
paper · pdf · doi:10.48550/arxiv.1407.2412
published in arXiv (Cornell University) (Cornell University)
arxiv created 2014/07/09 · openalex publication_date 2014/07/09 · arxiv updated 2014/07/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the status of the drivers. In addition of the advance technology of heart rate sensors is also added in the system for correct detection of status of driver if in either case driver is falling to fatigue due to any sever medical problems .The fatigue is detected in the system by the image processing method of comparing the image(frames) in the video and by using the human features we are able to estimate the indirect way of detecting fatigue. The technique also focuses on modes of person when driving the train i.e. awake, drowsy state or sleepy and sleep state. The system is very efficient to detect the fatigue and control the train also train can be controlled if it cross any such signal by which the train may collide on another train.