The Smart Vehicle Management System for Accident Prevention by Using Drowsiness, Alcohol, and Overload Detection

Mizan, Al Mamun; Kabir, A. Z. M. Tahmidul; Zinnurayen, Nadim; Abrar, Tawsif; Ta-sin, Akib Jawad; Mahfuzar,

doi:10.1109/eeccis49483.2020.9263429

Cited by 12 publications

(6 citation statements)

References 14 publications

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“…We highlight the advantages and limitations of existing systems and identify the research gaps that need to be addressed in future studies. Kabir et al (2020) has developed a smart car management system that aims to reduce traffic accidents. The system consists of three key components: an overload detector, an alcohol detector, and a sleep detector.…”

Section: Related Workmentioning

confidence: 99%

“…In (Xie et al, 2022), the authors introduce a novel algorithm using variational Bayesian learning and a neural network to efficiently reconstruct a crashed car's deformation field and pre crash state from its damaged structure, aiding in 3D collision analysis and forensic assessment. It achieves accurate results with fewer iterations, highlighting its These studies encompass a range of approaches, including the development of smart car management systems incorporating overload, alcohol, and sleep detectors (Kabir et al, 2020). Other systems feature sensors for accident detection (Gowri et al, 2019;Jacob et al, 2020;Khan & Howlader, 2019;Manikandan et al, 2021;Selvathi et al, 2017), collision prevention using Arduino and various sensors (Kinage & Patil, 2019), obstacle detection using ultrasonic sensors (Lim et al, 2018), and automatic braking for motorcycles (Suryana et al).…”

Section: Related Workmentioning

confidence: 99%

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Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Jagatheesaperumal,

Bibri,

Huang

et al. 2024

Comput.Urban Sci.

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In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. Thus, there is a compelling imperative to develop advanced solutions to enhance road safety within smart city frameworks. In this article, we introduce a comprehensive vehicle safety framework tailored specifically for smart cities in the realm of Artificial Intelligence of Things (AIoT). This framework seamlessly integrates a variety of sensors, including eye blink, ultrasonic, and alcohol sensors, to bolster road safety. The utilization of eye blink sensor serves to promptly detect potential hazards, alerting drivers through audible cues and thereby enhancing safety on smart city roads. Moreover, ultrasonic sensors provide real time information about surrounding vehicle speeds, thereby facilitating smoother traffic flow. To address concerns related to alcohol consumption and its potential impact on road safety, our framework incorporates a specialized sensor that effectively monitors the driver’s alcohol levels. In instances of high alcohol content, the system utilizes GPS and GSM technology to automatically adjust the vehicle’s speed while simultaneously notifying pertinent authorities for prompt intervention. Additionally, our proposed system optimizes inter-vehicle communication in smart cities by leveraging Li-Fi technology, enabling faster and more efficient data transmission via visible light communication (VLC). The integration of Li-Fi enhances connectivity among connected vehicles, contributing to a more cohesive and intelligent urban transportation network. Through the structured integration of AIoT technologies, our framework lays a robust foundation for a safer, smarter, and more sustainable future in smart city transportation. It offers significant advancements in road safety and establishes the groundwork for further enhancement in intelligent urban transportation networks.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Jagatheesaperumal,

Bibri,

Huang

et al. 2024

Comput.Urban Sci.

View full text Add to dashboard Cite

show abstract

“…The authors further stated that their method will carry out an operation for finding a safe parking space, allowing their autonomous vehicle to travel there on its own. In one paper [21], the combination of drowsiness, alcohol, and overload detection sensors is recommended to diminish the accident rate. This technology uses the eye blinking ratio to determine whether or not to slow down the vehicle.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart vehicle management by using sensors and an IoT based black box

Rahman

Kabir

Mizan

et al. 2022

IJRES

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As the number of transports on the road increases every day, so does the number of accidents. Reckless driving and consuming alcohol are two of the leading causes of accidents. Apart from these issues, the safety of humans and vehicles is also critical. A thorough investigation is required to minimize the accident rate and improve human safety, particularly if an incident occurs. The purpose of this study is to develop a few sensor-based black box system that will help us reduce traffic accidents by continuously providing precise guidance to the driver. At the same time, the evidence will be uploaded to its server for further evaluation. This system also includes a way of detecting drowsiness in the driver. Finally, using global positioning system (GPS) and global system for mobile communications (GSM), the relevant authorities will get information on the vehicle's condition and whereabouts. For security purposes, a panic button is introduced here to get emergency help from the security personnel by detecting the victim’s area.

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“…Researchers have always come forward to solve different kinds of problems in society. These include prevention of fire accidents [7], prevention of vehicle accidents [8]- [11], security system [12], [13], different types of projects for humanity [14]- [16]. In continuation of this, various researchers proposed different kinds of women's safety solutions at different times, considering these types of incidents.…”

Section: Introductionmentioning

confidence: 99%

A review on notification sending methods to the recipients in different technology-based women safety solutions

Kabir

Mizan

Saha

et al. 2022

IJ-ICT

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<span>Women have progressed a lot in terms of social empowerment and economics. They are going for higher education, jobs, and many other similar endeavors, but harassment cases have also been on the rise. So, women’s safety is a big concern nowadays, especially in developing countries. Many previous studies and attempts were made to create a feasible safety solution for women. Out of various features to ensure women’s safety in critical situations, location tracking is a very common and key feature in most previously proposed solutions. This study found mechanisms of sending the location to different types of recipients in various women safety solutions. In addition, the advantages and drawbacks of location sending methods in women's safety solutions were analyzed.</span>

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The Smart Vehicle Management System for Accident Prevention by Using Drowsiness, Alcohol, and Overload Detection

Cited by 12 publications

References 14 publications

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Smart vehicle management by using sensors and an IoT based black box

A review on notification sending methods to the recipients in different technology-based women safety solutions

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