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All Journal International Journal of Electrical and Computer Engineering Emerging Science Journal Indonesian Journal of Electrical Engineering and Computer Science
Abdullah, Mohd. Fikri Azli
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Environmental Science

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Applications of internet of things for monitoring drivers-a comprehensive study Yogarayan, Sumendra; Razak, Siti Fatimah Abdul; Azman, Afizan; Abdullah, Mohd. Fikri Azli
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 3: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i3.pp1599-1606

Abstract

Driving is a complex task that involves interacting adequately with the vehicle and the environmental changes simultaneously. Drivers' health is an essential factor in determining performance outcomes and enhancing road safety. It is a known reality that drivers with sudden health complications are most likely to be involved in road accidents and suffer several injuries. Besides that, drunk driving is another aspect of a significant public health issue, where drivers under the influence of alcohol show a clear vision loss and vehicle control. The internet of things (IoT) is a trendsetting advancement in which all sensor data can be collected in the cloud. In this paper, an active monitoring tool is developed to record the driver's heart rate if these readings reach vital values while on the move. Additionally, the tool monitors the driver's alcohol concentration, and if it rises beyond a certain threshold, an alarm is sent to the designated emergency contact. The tool has been tested and has been found to work satisfactorily.
Advancement in driver drowsiness and alcohol detection system using internet of things and machine learning Sivaprakasam, Avenaish; Yogarayan, Sumendra; Mogan, Jashila Nair; Razak, Siti Fatimah Abdul; Abdullah, Mohd. Fikri Azli; Azman, Afizan; Raman, Kavilan
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3477-3493

Abstract

Globally traffic accidents are influenced by factors such as drowsiness and alcohol consumption. Consequently, there has been a considerable focus on the development of detection systems as part of ongoing efforts to mitigate these risks. This review paper aims to offer a comprehensive analysis of various drowsiness and alcohol detection methods. The paper particularly emphasizes drowsiness and alcohol detection methods, including those centered on sensor-based approaches, physiological-based techniques, and visual analysis of the eye and mouth state. The aim is to evaluate their method, effectiveness and highlight recent advancements within this domain. Additionally, this review paper evaluates the research gaps of these detection methods, considering factors such as precision, sensitivity, specificity, and adaptability to different environmental conditions.
Assessing the Impact of Ghost Car Attacks on Traffic Flow in Vehicular Ad Hoc Networks Drahman, Isyraf Nazmi; Yogarayan, Sumendra; Abdul Razak, Siti Fatimah; Sayeed, Md. Shohel; Abdullah, Mohd. Fikri Azli; Kannan, Subarmaniam; Azman, Afizan
Emerging Science Journal Vol. 10 No. 1 (2026): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2026-010-01-024

Abstract

Vehicular Ad Hoc Networks (VANETs) play a crucial role in enhancing road safety, traffic management, and driving efficiency through real-time communication between vehicles and infrastructure. However, VANETs are vulnerable to various security threats, one of which is the “ghost car” attack. In this attack, a malicious entity injects false information into the network, simulating the presence of a non-existent or “ghost” vehicle. This can lead to severe consequences such as traffic disruptions, accidents, and a compromised trust in the system’s reliability. This study aims to simulate and analyze the impacts of ghost car attacks on Vehicular Ad Hoc Networks (VANETs), focusing specifically on intersection waiting times and overall traffic flow. We used Simulation of Urban Mobility (SUMO) integrated with ns-3 for realistic VANET simulations, introducing varying numbers of ghost vehicles. Results indicate significant increases in waiting times and vehicle counts at intersections due to ghost cars, leading to traffic disruptions. This study evaluates ghost car attacks within realistic urban scenarios and proposes targeted detection and mitigation strategies, leveraging authentication, machine learning, and blockchain technologies.
Co-Authors Abdul Razak, Siti Fatimah Azman, Afizan Drahman, Isyraf Nazmi Kannan, Subarmaniam Mogan, Jashila Nair Raman, Kavilan Sayeed, Md. Shohel Siti Fatimah Abdul Razak Sivaprakasam, Avenaish Yogarayan, Sumendra