A Graph Neural Network Approach for Identifying Decentralized Applications in Encrypted Traffic Proceedings of International Conference on Applied Innovation in IT, 2025
Dynamic analysis of traffic noise across various land uses based on real-time data Irwan LAKAWA, SUFRIANTO, HUJIYANTO, Agung SEPTIAWAN Scientific Review Engineering and Environmental Sciences, 2025 Traffic noise is one of the most significant forms of environmental pollution in urban areas. It can have negative impacts on both road users and residents living near highways. The high growth rate of motor vehicles from year to year in Kendari City has triggered an increase in traffic noise levels. This study aims to analyze the distribution of traffic noise across various land uses by utilizing real-time data. Noise measurements were conducted using a sound level meter (SLM) at several sampling points representing residential, commercial, service, office, school, and public facility areas. The SLM was positioned 1 m and 10 m away from the edge of the road. According to the findings of the analysis, Kendari City’s traffic noise levels have exceeded the environmental noise threshold. The study found that the main factors contributing to high noise levels are traffic volume and low vehicle speed. Areas with high traffic volumes, such as service, commercial, and office zones, produce higher noise exposure compared to other land use types. Land uses located near social activity centers are significantly impacted by noise exposure. Real-time data-based noise mapping is highly effective in designing sustainable urban transportation and spatial planning policies in cities with heterogeneous traffic categories.
Application of overlay method in interpreting of traffic noise distribution in land use I Lakawa, S Sufrianto, J Jusrin Iop Conference Series Earth and Environmental Science, 2021 Overlay studies with geographic information systems (GIS) are usually only to describe the condition of land elevation points, and various situations in land use. The purpose of this study was to analyze the intensity of noise in various types of land use and visualization of noise distribution maps. The research method uses a mathematical and overlay approach. The results showed that the average traffic flow was 1931 veh/h with a composition of motorcycle 61%, light vehicle 35%, and heavy vehicle 4%. Traffic noise level on Tuesday is 75.2 dB, while on Sunday it is 75.5 dB. There is no significant difference in noise intensity on Tuesday and Sunday at Ahmad Yani, MT. Haryono, Sao-Sao, and Abunawas Street. On Tuesday the highest noise level occurs in front of the education area while on Sunday in front of the shopping area. The intensity of noise distribution that reaches the highest land use occurs in the shopping area, followed by the office area, and the lowest in the school area. This is due to the increase in distance from the roadside.
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