A cost-effective system for triggering alarm to distracted drivers/ nurses. (June 2019)

• Record Type: Journal Article
• Authors: Bej, Debabrata; Rakshit, Subhajit; Mal, Ashis Kumar; Mahapatra, Rajat
• Is Part Of: Computers & electrical engineering. Volume 76(2019)
• Page Start: 24
• Page End: 39
• Publication Date: 2019-06
• Subjects: Vehicle/ patient safety -- Fatigue -- Surveillance -- Microcontroller -- Finite State Machine; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.03.001
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Distraction alarm for drivers/nurses through systematic and sensor-less approach. Cost-effective system design and its application to avoid distraction. Tracking of distraction through pseudorandom events. Identification of distraction from response recording of drivers/ nurses. Abstract: In this study, a systematic, low-cost, sensor-less solution for generating random alarm to distracted drivers/ nurses is proposed and designed to save them from accidents. A simple Finite State Machine (FSM) based algorithm is proposed for this work which has been implemented using an ATmega 328P – PU microcontroller. For testing the status of the driver/nurse, Linear Feedback Shift Register (LFSR) has been used to generate pseudo-random events at arbitrary intervals. In addition to this, a Register Transfer Level (RTL) diagram has also been investigated, and system output has been verified through Field Programmable Gate Arrays (FPGA) simulation. The prototype system has been deployed in a real-life environment by placing it in dashboard of a driver in a running vehicle or by putting the system on desk of a nurse on duty. The effective alertness of the driver and the nurse is found to be 76% and 87% respectively.