Detection of Road Traffic Congestion Using V2V Communication Based on IoT

Abood, Zainab A.; Taher, Hazeem B.; Ghani, Rana Fareed

doi:10.24996/ijs.2021.62.1.32

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…The positioning principle of RTK is to use carrier-phase technology [ 22 ] to process the carrier-phase observation values of two monitoring stations in real time to complete the dynamic positioning [ 23 ]. In this paper, one GPS receiver is set as the reference station, and another GPS receiver is installed on the detection vehicle.…”

Section: Gps System For Road Undulation Elevation Detectionmentioning

confidence: 99%

The Key Technologies of Road Elevation Detection Based on Sensor Fusion

Han

Liu

Chang

2022

Sensors

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The detection of long-distance pavement elevation undulation is the main data basis for pavement slope detection and flatness detection, and is also the data source for 3D modeling and quality evaluation of pavement surfaces. The traditional detection method is to use a level and manual coordination to measure; however, the detection accuracy is low and the detection speed is slow. In this paper, the high-speed non-contact vehicle-mounted road undulationelevation detection method is adopted, combined with the advantages of each sensor measurement; three methods are proposed to detect the road undulation elevation: rotary encoders, accelerometers, attitude sensor data fusion detection; GPS RTK detection; and Kalman filtering detection. Through modeling and experimental comparison, Kalman filter detection is not disturbed by the environment, and the detection accuracy is higher than the current international standard.

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Section: Gps System For Road Undulation Elevation Detectionmentioning

confidence: 99%

The Key Technologies of Road Elevation Detection Based on Sensor Fusion

Han

Liu

Chang

2022

Sensors

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“…The ISCX VPN-NonVPN traffic dataset has been used [30][31][32][33][34][35][36]. The dataset includes two scenarios (A and B).…”

Section: Practical Framework: Datasetmentioning

confidence: 99%

Network Traffic Prediction Based on Boosting Learning

Kashmoola

Ahmed

Alsaleem

2022

eijs

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Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traffic patterns that can be categorized based on statistical characteristics. These methods help determine the type of traffic and protect user privacy at the same time. To classify encrypted traffic from end to end, this paper proposes using (XGboost) algorithms, finding the highest parameters using Bayesian optimization, and comparing the proposed model with machine learning algorithms (Nearest Neighbor, Logistic Regression, Decision Trees, Naive Bayes, Multilayer Neural Networks) to classify traffic from end to end. Network traffic has two classifications: whether the traffic is encrypted or not, and the target application. The research results showed the possibility of classifying dual and multiple traffic with high accuracy. The proposed model has a higher classification accuracy than the other models, and finding the optimal parameters increases the model accuracy.

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“…From the beginning of the 1970s to today, microcontrollers and microcomputers have evolved very quickly. Nowadays, most embedded systems created based on microcontrollers are used in many applications including industrial [5,21], consumer [33], commercial [3], automotive [13], medical [12,18], home appliances [17,31], telecommunications [2], spacecraft [14], military applications [8,15], and so forth. The total-global microcontrollers market was estimated to be USD 86.5 billion in 2020 and predicted to reach USD 116.2 billion by 2025 [4].…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of a microcontroller training kit for blend learning

Mahmood

Ahmed

Mahmood

2022

Comp Applic In Engineering

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Today, microcontrollers are of paramount importance in various aspects of life. They are used for design in many industrial fields from simple to highly complex devices. With a COVID-19 crisis going on, blending learning is the ideal solution for a post-pandemic society. This paper proposes a blended learning system as a solution to address today's problem in teaching microcontroller courses through collaboration between distance learning with the proposed training toolkit for real work. Implementation of the proposed solution began by constructing an inexpensive training kit (100$), to empower all students, even those in remote rural areas. The distance learning model allows the simulation of the proposed IoT projects electronically anywhere and at any time using the Proteus design suite, which helps students to conduct them before the actual laboratory appointment. Two learning models are programmed in assembly language which is directly related to the internal architecture of the microcontroller and provides access to all the real capabilities of its central processing unit. To get acquainted with all the features offered by the microcontroller integrated circuit, various IoT projects were constructed, each one dedicated to learning its architecture features, important to engineering students. The proposed IoT systems operate with a minimum consuming power that is very important for portable devices.Questionnaire questions for students were formulated to measure the proposed system benefit over three academic years.

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Detection of Road Traffic Congestion Using V2V Communication Based on IoT

Cited by 8 publications

References 13 publications

The Key Technologies of Road Elevation Detection Based on Sensor Fusion

The Key Technologies of Road Elevation Detection Based on Sensor Fusion

Network Traffic Prediction Based on Boosting Learning

Design and implementation of a microcontroller training kit for blend learning

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