臺灣博碩士論文加值系統

近年來，智慧型手機的發展日新月異，行動應用軟體(Application， App)所能提供的服務也隨之成長，這些行動應用軟體結合以地理為基礎的服務(Location-Based Service, LBS)，已經發展到隨時可以處理人們在日常生活所會遇到的問題。只要透過3G以及搭配全球衛星定位系統(Global Positioning System ,GPS)的輔助，就能夠輕易的提供導航服務，但是相對的為了取得使用者需要的服務資訊，行動裝置必須承擔電能快速消耗的代價，以現在的智慧型手機續航力來說，待機大約使用225小時就必須做更換電池或充電，而根據過去的研究GPS感測模組是目前耗電量最高的原件，因為GPS導航為了取得地理位置，必須不斷的更新它的地理資訊，而不斷的更新地理資訊加上處理這些數據的動作是電力消耗主要因素。如果開啟3G或者GPS的服務電池的續航力只能達到4到6小時。
為了解決上述GPS耗電問題，過去的研究基於各個單一感測器來判斷行動裝置的所在情境，根據不同情境控制定位模組執行節能調配，但是這些方法均是以一兩種的感測資訊，來推測使用者的情境進而執行節能策略，如果我們能夠分析智慧型手機上提供的加速度計以及電子羅盤的數據，來預測使用者的目前位置，或者使用3G網路向Google Map 取得當前路段的道路資訊，搭配加速度計和電子羅盤結合道路資訊預測移動路徑，減少GPS的定位，就能減少定位模組不必要的電能消耗。
本篇研究以行動導航環境為基礎，探討行動裝置帶領使用者導航各個地點時，過於使用GPS所造成的大量電能消耗，在論文中我們以修改GPS定位資訊的更新頻率，來減少多餘更新時所消耗的電能，由於GPS在某些情況下會處於一個做白工的狀態，例如:停紅綠燈時無意義的座標更新，在可預測筆直路段上抵達路段終點的時間，在這些情況下GPS定位資訊的更新就沒有太大的效益，假如我們能夠善用行動裝置上的感測設備，判斷目前的情境，再決定GPS座標更新的頻率，就可以減少不必要的電能消耗。

In recent years, the number of smartphone users increases rapidly. The applications used on the Mobile devices one also developed quickly. By integrating the location based services into the context-aware applications, the context-aware applications will become more popular. GPS sensor is the one of widespread used device in various LBS applications. The main defect of GPS sensor is energy consumption. Therefore, designing an energy aware mechanism to save the battery power on smartphone is a great challenge. We can save energy of battery by employing existing context information of smartphone to obtain geographic location. Current smartphone have rich information of sensor context. This data can be directly obtained from the user’s smartphone in real-time. However, dispersed context (e.g., the user’s activity) has become highly useful for LBS applications since it can provide a human-understandable description of the user’s current situation. With this information, dispersed context can be substituted for GPS. In this thesis, we propose a strategy to save energy by using sensor context of smartphone. Base on that, we take advantage of accelerometer/compass and road information of Google Map to predict coordinates further. Consequently, it decreases the unnecessary receiver of GPS geographical coordination. And the final result shows that it can enhance the battery life of the device to 16% more than before and extend the length of using time l hour longer by using this method.

摘要...........i
Abstract...........ii
謝誌...........ii
目錄...........iv
表目錄...........v
圖目錄...........vi
第一章...........1
簡介............1
1.1 研究背景...........1
1.2 研究動機...........1
1.3 研究方法...........3
1.4 論文架構...........4
第二章 文獻探討...........5
2.1 全球衛星定位系統（Global Positioning System）.........5
2.2 加速度計(Accelerometer)...........8
2.3 電子羅盤(Electronic Compass)...........10
2.4 電子地圖(Google Map)...........11
2.5 行動裝置與節能...........14
第三章 研究方法...........18
3.1 情境資訊分類............21
3.2 節能演算法...........21
3.3 情境感知預測節能策略...........35
第四章 實驗模擬與驗證...........37
4.1 實驗環境與設置...........37
4.2 電量評估方法...........39
4.3 實驗結果與分析...........41
第五章 結論與未來展望...........46
參考文獻...........47
Extended Abstract...........49
簡歷(CV)...........53

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http://doi.ieeecomputersociety.org/10.1109/TPDS.2011.128
[21]卡爾曼濾波器介紹 Greg Welch and Gary Bishop , TR 95-041, Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill
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http://googlepolicyeurope.blogspot.tw/2010/04/data-collected-by-google-cars.html
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http://productforums.google.com/forum/#!category-topic/maps/google-maps-for-mobile/kw4gEPtmrcw
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http://zh.wikipedia.org/wiki/%E5%85%A8%E7%90%83%E5%AE%9A%E4%BD%8D%E7%B3%BB%E7%BB%9F。
[25]GPS 座標計算原理，
http://4rdp.blogspot.com/2008/05/gps.html
[26]三層架構模式，
http://zh.wikipedia.org/wiki/MVC