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  • Driving Safety Application Using Wearable Device and Mobile Technology

    Driving Safety Application Using Wearable Device and Mobile Technology

    Author: Eko Budi Setiawan ; Tubagus F. Fatoni

    Abstract

    This research is conducted to help motorbike riders in avoiding accidents caused by drowsiness. The wearable device technology used was smartband and accelerometer from Android smartphone. It was used to obtain heart rate data and detect drowsiness experienced by motorbike riders. An accelerometer was used to detect if an accident occurs and send the information to the driver’s family. The method in this research was quantitative research and development. The results obtained showed that detecting drowsiness is equal to 80% and the accident detection test gets an accuracy of 100%. The accuracy of drowsiness detection during the day is 75% and testing that carried out at night has an accuracy rate of 90%. Functional suitability test results obtained a value of 100%, compatibility aspects have 100%, usability aspects of 84.7%, and performance aspects in terms of response time are in the range of satisfaction equal to 3.88 seconds. The tests conducted using Likert scale showed that the application is feasible to use, and the driving safety application has reached its desired purpose. This research impacts on driving safety that must prioritize safety both for self and for others. © School of Engineering, Taylor’s University.

    Author keywords

    Accelerometer; Drowsiness; Motorbike driver; Safety ride; Smartband


    This article can be accessed at: https://www.scopus.com/pages/publications/85114312008

  • Human Detection and Avoidance Control Systems of an Autonomous Vehicle

    Human Detection and Avoidance Control Systems of an Autonomous Vehicle

    Author: Nizar T.N. ; Hartono R. ; Meidina D.

    DOI: 10.1088/1757-899X/879/1/012103

    Abstract

    A long-range and short-range navigation systems of an autonomous vehicle are the most important thing to develop because it is very complex and related to safety in the driving of an automatic vehicle. The purpose of this research is to develop a short-range navigation system for autonomous vehicles focused to detect and avoid humans which implemented on an autonomous vehicle prototype. Image Processing and deep learning algorithm used for human detection and ultrasonic sensor used for distance calculation. Decision making for human avoidance system using the Fuzzy algorithm based on the position of detected human and human distance. The implemented system has a success rate of 85.71% to avoid human which ideal distance more than 2 meters. The implemented prototype of an autonomous vehicle can be implemented in the real vehicle with some adjustments in the sensor and hardware system, however, the systems are expected to reduce traffic accidents caused by human error. © Published under licence by IOP Publishing Ltd.


    This article can be accessed at: https://www.scopus.com/pages/publications/85091368100