Channel Congestion Control in VANET for Safety and Non-Safety Communication: A Review

Rahim, Nurul Fazleen Binti Abdul; Khang, Adam Wong Yoon; Hassan, Aslinda; Elias, Shamsul Jamel; Gani, Johar Akbar Mohamat; Jasmis, Jamaluddin; Abedalrahim, Jamil

doi:10.1109/icraie52900.2021.9704017

Cited by 7 publications

(4 citation statements)

References 33 publications

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“…When negative labels are assigned, the classification process concludes, and the detector proceeds to shift the window to the next position. On the other hand, if a positive label is assigned, the region is subjected to further examination [29], [30]. The detector progresses through phases, swiftly discarding the negative samples, assuming that the object of interest is absent in most windows.…”

Section: Background Of the Studymentioning

confidence: 99%

Precision Face Mask Detection in Crowded Environment using Machine Vision

Alsayaydeh,

Yusof,

Lin

et al. 2024

IJACSA

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In the face of rampant global disease transmission, effective preventive strategies are imperative. This study tackles the challenge of ensuring compliance in crowded settings by developing a sophisticated face mask detection system. Utilizing MATLAB and the Cascade Object detector, the system focuses on detecting white surgical masks in frontal images. Training the system is critical for accuracy; therefore, cross-validation is employed due to limited data. The results reveal accuracies of 76.67% for initial training, 67.50% for a 9:11 cropping ratio, and 89.17% for a 9:4:7 cropping ratio, highlighting the system's remarkable precision in mask detection. Looking ahead, the system's adaptability can be further expanded to include various mask colors and types, extending its effectiveness beyond COVID-19 to combat a range of respiratory illnesses. This research represents a significant advancement in reinforcing preventive measures against future disease outbreaks, especially in densely populated environments, contributing significantly to global public health and safety initiatives.

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Section: Background Of the Studymentioning

confidence: 99%

Precision Face Mask Detection in Crowded Environment using Machine Vision

Alsayaydeh,

Yusof,

Lin

et al. 2024

IJACSA

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“…VANET congestion control is an important and active area of research, and has received significant attention in recent years, for both safety and comfort applications [23][24][25]. Integrating 5G technology with VANET communications for future applications has received significant research attention [26], including issues related to security and privacy [27,28].…”

Section: Background Reviewmentioning

confidence: 99%

Data Rate Selection Strategies for Periodic Transmission of Safety Messages in VANET

St. Amour,

Jaekel

2023

Electronics

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Vehicular ad hoc networks (VANETs) facilitate communication among vehicles and possess designated infrastructure nodes to improve road safety and traffic flow. As the number of vehicles increases, the limited bandwidth of the wireless channel used for vehicle-to-vehicle (V2V) communication can become congested, leading to packets being dropped or delayed. VANET congestion control techniques attempt to address this by adjusting different transmission parameters, including the data rate, message rate, and transmission power. In this paper, we propose a decentralized congestion control algorithm where each factor adjusts the data rate (bitrate) used to transmit its wireless packet congestion based on the current load on the channel. The channel load is estimated independently by each vehicle using the measured channel busy ratio (CBR). The simulation results demonstrate that the proposed approach outperforms existing data rate-based algorithms, in terms of both packet reception and overall channel load.

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“…Vehicular Ad Hoc Networks (VANETs) are considered as a major component of future intelligent transportation systems (ITSs) [1]. In VANETs, Connected and Automated Vehicles (CAVs) are equipped with On-Board Units (OBUs) and are provided with varieties of applications, including safety related, non-safety related and infotainment applications [2]. To implement those applications, timely delivery of relevant messages or data packets need to be guaranteed.…”

Section: Introductionmentioning

confidence: 99%

PreZcast: A Preferred-Zone Based Broadcast Protocol for Urban Areas of VANETs

Wang,

Mitton,

Zheng

2023

ICC 2023 - IEEE International Conference on Communications

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Channel Congestion Control in VANET for Safety and Non-Safety Communication: A Review

Cited by 7 publications

References 33 publications

Precision Face Mask Detection in Crowded Environment using Machine Vision

Precision Face Mask Detection in Crowded Environment using Machine Vision

Data Rate Selection Strategies for Periodic Transmission of Safety Messages in VANET

PreZcast: A Preferred-Zone Based Broadcast Protocol for Urban Areas of VANETs

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