臺灣博碩士論文加值系統

物聯網是現今經常被提起及研究的項目，隨著感測器的設置增加，資料量也隨之增大，為了能夠快速的處理以及分析這些巨量資料(Big Data)，許多廠商或政府開始收集大量資料並從中挖掘對我們有利益價值的訊息，而如何有效率的存取資料並且以人們方便閱讀的方式呈現出來成為我們討論的目標。
是故在本論文中我們設計了一個系統並且收集了電動車的車輛資料及租賃資料去作分析，之後再以圖表、地圖的方式呈現出視覺化的效果。而為了避免重複計算資料，我們使用快取的方法將計算過的資料儲存在資料庫中，如此一來節省了查詢的時間。我們同時也以無快取及有快去的情況下作比較分析，最後結果顯示我們提出的方法可以大幅降低系統查詢的效能，能夠更快速的呈現出我們要的結果。

IoT is a currently popular research topic. As the number of devices grow, the amount of data increase dramatically. Efficiently processing and analyzing large amount of data become an important issue.
In this study, we design a database system to manage and analyze vehicular rental data, which can present different aspects of analytical results with visualized approaches, including hot-zone map, time series and so on. To avoid redundant calculations and reduce computation time, we cached the pre-processed data in the system. The comparison shot that the process time is vastly reduced.

書名頁 I
論文口試審定書 II
授權書 III
中文摘要 IV
英文摘要 V
誌謝 VI
表目錄 IX
圖目錄 X
第一章、緒論 1
第一節、研究背景 1
第二節、電動載具的發展 2
第三節、車輛資料收集目的及分析的重要性 3
第四節、相關文獻 4
第五節、研究目標 5
第二章、系統架構 6
第一節、 資料來源介紹 8
第一項、來源資料 9
第二項、快取資料 13
第三項、資料庫函式介紹 15
第二節、系統查詢方法與資料計算 16
第三節、快取資料方法與原因 21
第三章、系統效能評估 24
(一)執行查詢時 24
(二)執行熱區圖時 25
(三)預估成效與未來展望 26
第四章、分析結果 29
(一)使用者 29
(二)充電站 33
(三)車輛行駛熱區 35
第五章、系統實作 37
第一節、環境需求與安裝 37
第二節、實例操作 42
第一項、資料表格 42
第二項、行駛路線圖及熱區圖 44
第三項、長條圖 45
第六章、結論 50
參考文獻 51

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[3]Chung-HONG Lee and Chin-Hung Wu,” A Novel Big Data Modeling Method for Improving Driving Range Estimation of Evs, IEEE Access ( Volume: 3 ), Page(s):1980 – 1993, 19 October 2015
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