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  • 學位論文

利用適地性服務建構行動空氣品質預警系統

Using Location-Based Services to Build a Mobile Air Quality Warning System

指導教授 : 蔡博文

摘要


由於地理資訊技術的成熟,加上近年來行動裝置、無線網路的普及化,帶動適地性服務(Location-Based Service; LBS)的廣泛應用,行動裝置使用者已能享有隨時隨地取得所需資訊的便利性。本研究以自願性地理資訊(Volunteered Geographic Information, VGI)的概念,利用適地性服務的應用,結合即時交通資訊,選取臺北市主要路段,針對一氧化碳汙染濃度進行推估,並在Android平台的行動裝置上建立空氣品質預警系統的行動裝置應用程式(Mobile Application,簡稱APP)。 以往國內外針對造成都市空氣汙染的各種因素已有相當多的研究,然而針對即時交通狀況與空氣品質的實際轉換關係,卻鮮有應用案例。本研究推估一氧化碳濃度的方式乃是利用臺北市交通局主要道路的車輛偵測器,獲取即時的交通資料,參考環保署公布之車輛排放係數,並以街谷的概念假設一氧化碳的擴散範圍,推估出各主要道路的一氧化碳汙染濃度,以建立即時交通狀況與一氧化碳濃度的關係。並以本模式推估出的一氧化碳濃度,與鄰近的環保署空氣品質測站監測的即時一氧化碳濃度進行比對,發現模式推估而得的一氧化碳濃度與測站濃度相當接近,顯見模式具有一定的可信度。 在適地性服務的應用上,空氣品質預警系統APP執行後,可依據使用者所在位置,以Google Maps路段分級著色的方式,呈現即時空氣汙染狀況,並提供使用者接近空氣品質現況不良路段時的預警服務,以提醒使用者避開空氣品質不良的路段。

並列摘要


Due to the developing of geographic information technologies, and the popularity of both mobile devices and wireless networks, promote location-based service (LBS) are widely applied. Mobile device users are now able to enjoy the convenience of obtaining necessary information whenever and wherever. In this study, we use the concept of volunteered geographic information (VGI), and the use of location-based service applications, combined with real-time traffic information of main streets in Taipei, to estimate the concentration of carbon monoxide pollution, furthermore, an air quality warming system mobile applications (APP) is established in the Android platform. A considerable number of studies have been made on various urban air pollution factors. However, there are few practical cases refer to the relationship between the actual real-time traffic conditions and the conversion of air quality. In this study, we access real-time traffic information offering by vehicle detectors on main streets constructed by the Department of Transportation, Taipei city government, then compute the concentrate of CO referring to vehicle emission factor published by EPA. At the meantime, the diffusion of carbon monoxide is assumed by the concept of street canyon to estimate a spatial carbon monoxide concentration model. To evaluate the model, we compare the carbon monoxide concentration data provided by the nearest EPA air quality monitoring stations, the result indicate that the estimating carbon monoxide concentration in this study is very close to the real data, showing that model has a certain credibility. Mentioned on the application of location-based services, the air quality warning system APP shows real-time air pollution information with grading colors on Google Maps, remind users to avoid poor air quality sections.

參考文獻


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被引用紀錄


陳奎元(2016)。應用時空分析方法建立動態交通事故預警系統之研究〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342%2fNTU201603598

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