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Microclimate investigation of vehicular traffic on the urban heat island through IoT-Based device

Anthropogenic is defined as one of the influencing factors of the climatic phenomenon, called Urban Heat Island (UHI), in which urban areas have higher air temperatures than their rural surroundings. Analyzing the impact of anthropogenic factors, such as vehicular traffic, has implications for the p...

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Detalles Bibliográficos
Autores principales: Husni, Emir, Prayoga, Galang Adira, Tamba, Josua Dion, Retnowati, Yulia, Fauzandi, Fachri Imam, Yusuf, Rahadian, Yahya, Bernardo Nugroho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678727/
https://www.ncbi.nlm.nih.gov/pubmed/36425428
http://dx.doi.org/10.1016/j.heliyon.2022.e11739
Descripción
Sumario:Anthropogenic is defined as one of the influencing factors of the climatic phenomenon, called Urban Heat Island (UHI), in which urban areas have higher air temperatures than their rural surroundings. Analyzing the impact of anthropogenic factors, such as vehicular traffic, has implications for the potential benefits of health monitoring systems; however, the spatiotemporal impact of anthropogenic factors, as well as vehicle mobility, has not been thoroughly investigated. This study incorporates vehicle mobility data by leveraging two different sensors; fixed station sensor instruments designed to integrate with the Internet of Things (IoT), and the camera of an area traffic control system (ATCS) that uses CCTV visualization with object detection. Using object detection and time-based traffic volume analysis, we obtain the level of the queue rate (λ) to present the level of the traffic flow based on the average velocity of the vehicle flow. Based on the results, it showed that the average temperature in urban areas is higher than in suburban areas, and the severe traffic jams caused a significant increase in temperature, that is until 7 Celsius when the weather is sunny. In addition, the theoretical UHI (UHI(T)) model developed in this study can be used to estimate the UHI which is influenced by the queue rate.