Intelligent Lighting System of Urban Road Based on Internet of Things

Hao, Lu‐Lu; Gao, Jing

doi:10.33383/2018-125

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Mean pooling [22] is used, that is, the pooling box takes the mean value of the data inside the box when it slides on the convolutional feature map. Finally, the results are output in the output layer, i.e., recognize the target object in the target box (the marker to be tracked by the light source of the desk lamp) and give the coordinates of the target box in the image [23].…”

Section: Adjustment Strategy For the Smart Desk Lampmentioning

confidence: 99%

Design of 360° Dead-Angle-Free Smart Desk Lamp based on Visual Tracking

Sun,

Liu

2023

HighTech. Innov. J.

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Objectives: This study aims to design a dead-angle-free smart desk lamp. Methods: The convolutional neural network (CNN) algorithm was used to realize the identification and positioning of objects. Then, the desk lamp arm was driven according to positioning to realize dead-angle-free illumination. In the subsequent testing, the designed desk lamp was compared with others driven by the support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. Findings: The CNN algorithm implemented in the smart desk lamp demonstrated superior target recognition performance and positioning accuracy when compared to the other two algorithms. Moreover, with this algorithm, the smart desk lamp efficiently generated tracking responses for targets and displayed minimal positioning errors once tracking became stable. Novelty:The novelty of this article lies in the utilization of the CNN algorithm to achieve visual tracking for a smart desk lamp, which serves as the basis for its automatic adjustment. Doi: 10.28991/HIJ-2023-04-04-05 Full Text: PDF

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Section: Adjustment Strategy For the Smart Desk Lampmentioning

confidence: 99%

Design of 360° Dead-Angle-Free Smart Desk Lamp based on Visual Tracking

Sun,

Liu

2023

HighTech. Innov. J.

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Reducing Energy Consumption in Single-Hop and Multi-Hop Topologies of Road Lighting Communication Network

Çıbuk

2020

L&E

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This study aims to make the wireless sensor network based on a linear topology required in road lighting energy-efficient using the proposed new methods. Because the physical installation of road lighting systems will result in costliness and time-labour loss, the mentioned scenarios were created and analysed in a simulation design. Two new methods were proposed to organize the lighting system more quickly and to increase the speed performance of sensors that join the network and carrying the luminaire data. This is the proxy-based network connection method and a new time-division method for the nodes’ common channel access. Energy consumption scenarios for lighting systems with 50, 100, 150, and 200 luminaires were analysed comparatively during data exchange using wireless sensor networks. Accordingly, the classical method and the proposed novel method were evaluated for the singleand multi-hop scenarios. In the communication between luminaires, the proposed new method for a single-hop scenario was at least 80 % more efficient than the classical method in terms of total energy consumption. In linear topology lighting systems for the same scenario, if the classical method is compared with the proposed new method for 3-hop structures, 58 % efficiency of total energy consumption is achieved.

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Intelligent Lighting System of Urban Road Based on Internet of Things

Cited by 2 publications

References 6 publications

Design of 360° Dead-Angle-Free Smart Desk Lamp based on Visual Tracking

Design of 360° Dead-Angle-Free Smart Desk Lamp based on Visual Tracking

Reducing Energy Consumption in Single-Hop and Multi-Hop Topologies of Road Lighting Communication Network

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