A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System Through UAV Speed Control

Li, Xiong; Tan, Jiawei; Liu, Anfeng; Vijayakumar, Pandi; Kumar, Neeraj; Alazab, Mamoun

doi:10.1109/tits.2020.3040557

Cited by 122 publications

(33 citation statements)

References 29 publications

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“…It is a special type of communication, which groups wireless transmission devices and vehicles to create a cluster and it has no limitations for adding any number of devices within its coverage range, since it is a dynamic cluster 12,27 . The members of the clusters can join and leave any cluster through its cluster head coverage range 28,29 . Every cluster has a cluster head, and it is in‐charge of transmission of members.…”

Section: Proposed Workmentioning

confidence: 99%

“…From that collection, 80% of the data are used for training and the remaining 20% for testing. The network architecture is built using Theano a network implementation 1,29 . The duration of the computation takes 2–4 h using RX 5600XT layers in each trial.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…12,27 The members of the clusters can join and leave any cluster through its cluster head coverage range. 28,29 Every cluster has a cluster head, and it is in-charge of transmission of members. The higher transmission capability devices are elected as cluster heads.…”

Section: Cluster Communication Using Proximity Servicesmentioning

confidence: 99%

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An improved public transportation system for effective usage of vehicles in intelligent transportation system

Rajkumar

Deborah²

2021

Int J Communication

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Summary Procuring usage of the public transportation system enhances the promising effect of limiting the number of own vehicles usage in the contemporary world. The present research advocates a new paradigm of the Intelligent Transportation System (ITS) in the near future, to rescue fossil fuel and to maintain a healthy environment for the current generation. To provide this facility, Long Short Term Memory (LSTM) based intelligent learner has been proposed. This intelligent learner is mainly used to predict high vehicle demand requests in order to utilize a public transport system effectively. In this way, excess usages of vehicles are reduced from low vehicle demand request locations to the locations where high vehicles demand requests are generated. Moreover, a new enhanced approach has also been designed to establish communication between the onboard vehicles and the passengers for instant reservation of their seats based on real‐time sensors. To achieve the effective usage of the public transportation system, an effective dynamic scheduling algorithm that dedicates more convenient travel in the complex transportation system, has been proposed. The proposed system results are evaluated using real‐time transport data, which are collected from major cities and they are implemented to predict the exact vehicles demand. The performance results are compared with various existing methods and the proposed system has proved its efficiency than the existing methods. When the proposed system is implemented, it improves 87% usage of public transportation as well as the usage of taxis and own vehicles would be reduced drastically in the city.

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Section: Proposed Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

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An improved public transportation system for effective usage of vehicles in intelligent transportation system

Rajkumar

Deborah²

2021

Int J Communication

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“…The data generated by these IoT devices reaches 2.5 quintillion bytes every day [4], [5]. On the other hand, the Artificial Intelligence (AI) technology has enriched the ability of humans to use data [6]- [8], thus making humans' desire for sensing and collection data more urgent [9]- [11]. Therefore, many sensing devices are increasingly being deployed in various applications to sense and obtain data [12]- [14], making edge computing, fog computing and other emerging computing models fully developed [15]- [17].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Data Aggregation Scheme Based on Differentiated Threshold Configuring Joint Optimal Relay Selection in WSNs

Liu

Zeng

et al. 2021

IEEE Access

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In Wireless Sensor Networks (WSNs), when multiple data packets meet during routing to the sink, redundant data can be removed through data fusion, thereby reducing the amount of data transmitted, and increasing the life of the network. However, how to increase the data fusion rate as much as possible and ensure that the delay is lower than the deadline is a challenge issue. To solve this problem, a Differentiated Threshold Configuring joint Optimal Relay Selection based Data Aggregation (DTC-ORS-DA) scheme is proposed, which can significantly reduce redundant data routing and guarantee the delay for WSN. The main innovation is as follow: (1) In DTC-ORS-DA scheme, there are two thresholds: data volume threshold and time threshold. Data routing can only be performed when or of the node meet the threshold requirements, so that the data can be fully integrated to minimize the amount of data to be transmitted. More importantly, DTC-ORS-DA adopts differentiated threshold settings based on the characteristics of unbalanced energy consumption in WSNs, and sets a smaller threshold in the far sink area with sufficient energy, so that data packets can be routed quickly. And the near sink area where the energy is tight uses a larger threshold to maximize data fusion, so that the combination can make the data fusion high, the energy is effectively used, and the delay is small. (2) We propose a priority-based relay selection algorithm, which enables child nodes to dynamically select the parent node with the highest priority based on the number of data packets, waiting time, and remaining energy. In the process of routing, the probability of nodes with many data packets or long waiting time being selected as transmission relay is high, which can either increase the data fusion rate or reduce the delay. Finally, the performance comparison with Common data collection Scheme (CS) proves that, the DTC-ORS-DA scheme reduces the average delay by 10.74%-19.91%, increases the life cycle by 9.81% at most, and the energy utilization rate is increased by 6.67%-9.48%.

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“…Recently, UAV-enabled data collection, which avoids complex road environments and has higher speed and lower traveling costs, is becoming more and more popular [ 29 , 30 ]. Due to its inherent attributes, such as high flexibility, high mobility, and adaptive altitude, UAVs have been proven as an efficient solution to collect data from these networks [ 31 ].…”

Section: Introductionmentioning

confidence: 99%

A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

Tian

Jiao

Chen

2021

Sensors

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In wireless rechargeable sensor networks, mobile vehicles (MVs) combining energy replenishment and data collection are studied extensively. To reduce data overflow, most recent work has utilized more vehicles to assist the MV to collect buffered data. However, the practical network environment and the limitations of the vehicle in the data collection are not considered. UAV-enabled data collection is immune to complex road environments in remote areas and has higher speed and less traveling cost, which can overcome the lack of the vehicle in data collection. In this paper, a novel framework joining the MV and UAV is proposed to prolong the network lifetime and reduce data overflow. The network lifetime is correlated with the charging order; therefore, we first propose a charging algorithm to find the optimal charging order. During the charging period of the MV, the charging time may be longer than the collecting time. An optimal selection strategy of neighboring clusters, which could send data to the MV, was found to reduce data overflow. Then, to further reduce data overflow, an algorithm is also proposed to schedule the UAV to assist the MV to collect buffered data. Finally, simulation results verified that the proposed algorithms can maximize network lifetime and minimize the data loss simultaneously.

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A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System Through UAV Speed Control

Cited by 122 publications

References 29 publications

An improved public transportation system for effective usage of vehicles in intelligent transportation system

An improved public transportation system for effective usage of vehicles in intelligent transportation system

An Efficient Data Aggregation Scheme Based on Differentiated Threshold Configuring Joint Optimal Relay Selection in WSNs

A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

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