Title: Intelligent traffic congestion discrimination method based on wireless sensor network front-end data acquisition

Authors: Maokai Lai

Addresses: Chang'an Dublin International College of Transportation, Chang'an University, Xi'an, Shaanxi, China

Abstract: Conventional intelligent traffic congestion discrimination methods mainly use GPS terminals to collect traffic congestion data, which is vulnerable to the influence of vehicle time distribution, resulting in poor final discrimination effect. Necessary to design a new intelligent traffic congestion discrimination method based on wireless sensor network front-end data collection. That is to use the front-end data acquisition technology of wireless sensor network to generate a front-end data acquisition platform to obtain intelligent traffic congestion data, and then design an intelligent traffic congestion discrimination algorithm based on traffic congestion rules so as to achieve intelligent traffic congestion discrimination. The experimental results show that the intelligent traffic congestion discrimination method designed based on the front-end data collection of wireless sensor network has good discrimination effect, the obtained discrimination data is more accurate, effective and has certain application value, which has made certain contributions to reducing the frequency of urban traffic accidents.

Keywords: wireless sensor network; front-end; data acquisition; transportation; intelligence; traffic jam; distinguish; traffic congestion data.

DOI: 10.1504/IJCAT.2024.141916

International Journal of Computer Applications in Technology, 2024 Vol.74 No.3, pp.147 - 157

Received: 04 Apr 2023
Accepted: 31 Jul 2023
Published online: 03 Oct 2024 *

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