Progressive-encoding-based transmission for DNN-enabled edge intelligence in unreliable network

Dong, Luobing; Luo, Haobin; Zhang, Shan; Ren, Yanan; Duan, Mingdong; Qin, Yifan

doi:10.1016/j.tcs.2022.06.014

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…The last section is GPS Application, which was used for navigating the directions for the users from starting point to the ending point with latitude and longitude. So, after collecting all directions from GPS, it will be sent to "Raspberry Pi 4" by using UDP [26] to show all directions gradually on the helmet's glass through a projector as arrows to track it and follow the directions to his destination point.…”

Section: Block Model Of the Smart Helmetmentioning

confidence: 99%

Helmet-Mounted Display System Based on IoT

Eldeib¹

2022

Journal of Engineering Research

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Many people enjoy motorcycle riding, but there are thousands of people lost their lives because of road accidents. This is mainly due to the delayed response to emergencies that must be provided to the injured and victims. The helmetmounted display system that uses the Internet of Things (IoT) reduces accidents and informs its contacts in emergencies, as the helmet module contains sensors to determine the passenger's pulse rate, alcohol content, and vibration intensity. The pulse rate sensor is used to determine whether the rider has worn the helmet and which will be connected to the rider's start of his trip on the road. That's why a prototype proposal was implemented using the (IoT) to connect all devices and make it easier for the user to reduce road accidents by displaying all their needs in full on the helmet screen. Furthermore, in the implementation of our proposal, several systems were connected with Raspberry Pi 4, which are Global Positioning System (GPS) applications, camera systems, and sensors that display all output data in the background, such data will be transmitted after that from Raspberry Pi 4 to Raspberry Pi 3 through User Datagram Protocol (UDP), which Raspberry Pi 3 connected with Digital Light Processing (DLP) projector to display all background data as a hologram to the user giving him safety on the road without any distractions.

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Section: Block Model Of the Smart Helmetmentioning

confidence: 99%

Helmet-Mounted Display System Based on IoT

Eldeib¹

2022

Journal of Engineering Research

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Reliability assessment and optimization of computer networks based on neural networks

Liu

2024

Applied Mathematics and Nonlinear Sciences

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Amidst the swift evolution of computer technologies, the prevalence of computer networks has become pivotal across diverse sectors, increasingly reliant on their robust functionality. This study rigorously evaluates and enhances the reliability of computer networks by leveraging an index system and an evaluation model devised through neural networks. To strengthen network dependability, this research employs a Hopfield neural network to address multi-constraint Quality of Service (QoS) multicast routing challenges, thereby elevating network reliability. Simulation experiments demonstrate that the Hopfield neural network effectively mitigates network latency and exhibits superior convergence performance compared to conventional QoS multicast routing methods. Further, this paper applies the neural network-based evaluation model to analyze the reliability of the air traffic network within the H-area after integrating the optimized computer network framework. It is observed that the most significant contributor to traffic flow loss is the network's degree value. An analysis of traffic flow density, employing actual sector flow data, reveals that high traffic volumes typically precipitate congestion. Nonetheless, the traffic flow density value consistently exceeds 100, suggesting that the enhanced computer network model holds practical applicability in real-world scenarios.

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Progressive-encoding-based transmission for DNN-enabled edge intelligence in unreliable network

Cited by 2 publications

References 31 publications

Helmet-Mounted Display System Based on IoT

Helmet-Mounted Display System Based on IoT

Reliability assessment and optimization of computer networks based on neural networks

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