Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway Systems

Bin, Sheng; Sun, Gengxin

doi:10.3390/s20020482

Cited by 58 publications

(40 citation statements)

References 22 publications

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“…Under the condition of no reference image, the image clarity measuring method [22] can achieve high accuracy, monotony, and consistency. Therefore, this method was adopted to evaluate the quality of the image enhanced by various algorithms.…”

Section: Experiments and Results Analysismentioning

confidence: 99%

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An Image Sharpness Enhancement Algorithm Based on Green Function

Huang¹

2021

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The traditional image sharpness enhancement algorithm faces several defects, namely, the lack of details, and the poor subjective effect. To solve these defects, this paper proposes an image sharpness enhancement algorithm based on the Green function. Specifically, the Retinex model was employed to ensure that the enhanced image has outstanding details, and the Poisson’s equation was solved to maintain the consistency between the enhanced image and the original image in the gradient domain. Then, adaptive brightness mapping was carried out to determine the boundary conditions suitable for display, and the boundary of the region was sampled to reduce the complexity of our algorithm. Experimental results show that our algorithm improved the contrast and sharpness of images from the levels of contrastive image enhancement algorithms.

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Section: Experiments and Results Analysismentioning

confidence: 99%

“…Substituting formula (24 into formula (22), the Green function in circular region can be expressed as:…”

Section: Solving Poisson Equation With Green Functionmentioning

confidence: 99%

An Image Sharpness Enhancement Algorithm Based on Green Function

Huang¹

2021

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“…To improve container loading/unloading, Xiong et al [8] proposed a container recognition system based on stereo vision: the original image was segmented; the container was recognized and located by binocular stereo vision system; the container-spreader distance was computed based on the container position. Bin and Sun [9] derived a new programming model to analyze the position of container and improve the operation efficiency of crane.…”

Section: Literature Reviewmentioning

confidence: 99%

Recognition and Positioning of Container Lock Holes for Intelligent Handling Terminal Based on Convolutional Neural Network

Wang¹

2021

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Container handling is a key link in container transport. In an automated handling terminal, the work efficiency directly depends on the time cost of the alignment between the spreader and the lock holes of the container. This paper attempts to improve the recognition and location of container lock holes with the aid of machine vision. Firstly, a lock hole recognition algorithm was designed based on local binary pattern (LBP) feature and classifier. After feature extraction and classifier training, multi-scale sliding window was used to recognize each lock hole. To realize real-time, accurate recognition of lock holes, the convolutional neural network (CNN) with improved threshold was incorporated to our algorithm. The tests on actual datasets show that our algorithm can effectively locate container lock holes.

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“…Therefore, IEEE published IEEE 802.15.4e TSCH standard [1], which can optimize the current physical layer and media access layer to improve the stability of the system. The core of TSCH technology is the integration of channel hopping and time synchronization technology to complete the scheduling of time slot and frequency [2]. Voulgaris et al [3] pointed out that TSCH technology can guarantee 99% end-to-end communication stability under the premise of 1% radio duty cycle.…”

Section: Related Workmentioning

confidence: 99%

Optimization of Time and Power Resources Allocation in Communication Systems Under the Industrial Internet of Things

Wang

2020

IEEE Access

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In the Industrial Internet of Things (IIoT), it is an urgent task to reduce power loss and enhance energy efficient through reasonable allocation of resources. Inspired by time slot channel frequency hopping, this paper puts forward a dynamic allocation model for time and power resources. Based on the proposed model, a dynamic resource allocation algorithm was designed to reduce energy consumption. In addition, a power and time allocation algorithm was developed to maximize the energy efficiency of the system. The workflows of the two algorithms were introduced in details. Simulation results show that both dynamic resource allocation algorithm could reduce the energy loss of the communication system, while ensuring the stability of the data queue. The research findings help to promote the performance of communication systems in different scenarios of the IIoT.

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Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway Systems

Cited by 58 publications

References 22 publications

An Image Sharpness Enhancement Algorithm Based on Green Function

An Image Sharpness Enhancement Algorithm Based on Green Function

Recognition and Positioning of Container Lock Holes for Intelligent Handling Terminal Based on Convolutional Neural Network

Optimization of Time and Power Resources Allocation in Communication Systems Under the Industrial Internet of Things

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