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Energy-efficient street lighting through embedded adaptive intelligence

机译:通过嵌入式自适应智能实现节能街道照明

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摘要

Streetlights place a heavy demand on electricity usage, providing significant financial and environmental burdens. Consequently, initiatives to reduce energy consumption have been proposed, usually by turning off or dimming the streetlight. In this paper, we propose an adaptive lighting scheme based on traffic sensing, which adaptively adjusts streetlight brightness based on current traffic conditions. The algorithm has been validated through simulation using the SUMO and OMNeT++ tools and, for two different geographical locations, the energy consumption evaluated with respect to traffic speed and volume. The simulation results presented indicate that the proposed lighting scheme can consume up to 30% less energy when compared to the state-of-the-art.
机译:路灯对用电有很高的要求,给财务和环境带来了沉重负担。因此,已经提出了通常通过关闭或调暗路灯来减少能耗的倡议。在本文中,我们提出了一种基于交通感知的自适应照明方案,该方案可根据当前交通状况自适应地调整路灯亮度。该算法已通过使用SUMO和OMNeT ++工具进行的仿真进行了验证,并且针对两个不同的地理位置,针对交通速度和交通量评估了能耗。呈现的仿真结果表明,与最新技术相比,拟议的照明方案可减少多达30%的能源。

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