智慧型行動裝置上能搜集到包含加速度計、磁力計、訊號強度、基地台ID等各式資料。現今，資料常用於輔助商業決策、進行使用者行為分析等。而在機器學習中，模型的建構也會需要大量的資料。
隨著科技的進步，擁有智慧型行動裝置的人越來越多，亦即有越來越多的資料可供收集。本論文建立了一個資料收集的函式庫，讓應用程式開發者利用本函式庫，輕鬆達到收集智慧型行動裝置資料的目的。
現行的智慧型行動裝置主流的作業系統為Google的Android與Apple的iOS，應用的開發方式除了使用Android、iOS官方推薦的語言呼叫原生API外，也有使用跨平台框架的開發方式，可以同時支援多個作業系統。目前主流的跨平台框架有Google推出的Flutter和Facebook推出的React Native等。為了讓應用程式開發者方便使用本函式庫進行程式開發，因此本論文開發之函式庫除了支援官方指定語言呼叫外，也支援Flutter和React Native兩個跨平台框架。

Various data including accelerometer, magnetometer, signal strength, base station ID, etc. can be collected on smart mobile devices. In the modern era, data is often used to assist business decision, user behavior analysis, etc. In machine learning, the training of models also requires a lot of data.
With the progress of science and technology, more and more people have their own smartphones. That is, more and more data can be collected from people’s smartphones. In this paper, we build a data collection library for application developers to easily achieve the goal of collecting data from smartphones.
The main operating systems for smartphones are Google Android and Apple iOS. In addition to calling native APIs in programming languages officially recommended by Google and Apple, using cross-platform framework is another way to develop smartphone’s applications. Cross-platform frameworks can support multiple operating systems at the same time. At present, main cross-platform frameworks include Flutter and React Native. The library proposed by this paper can support not only the development using native APIs officially recommended by Google and Apple, but also the development using cross-platform frameworks.

1. 前言 6
2. 研究動機 7
2.1 應用程式開發流程 8
2.2 開發支援不同平台與框架的函式庫 8
3. 背景 9
3.1 智慧型行動裝置上的感測器與可獲取的資料類型 9
3.2 原生應用程式開發 10
3.3 跨平台開發框架 10
3.4 SensingGO: 手機資料量測與應用系統 12
4. 實作 15
4.1 SensingGO Library: 多平台資料收集函式庫 15
4.2 函式庫架構 15
4.3 Android版函式庫 16
4.4 iOS版函式庫 18
4.5 Flutter實作 19
4.6 React Native版本函式庫 21
5. 實驗結果 23
5.1 實驗與環境設定 23
5.2 評估方式 23
5.3 實驗結果 24
6. 結論 32
7. 參考資料 33

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