現今資訊產業蓬勃發展，智慧型手機的普及率亦逐漸上升，而這些智慧型手機通常都配有感測器，用來蒐集使用者資訊或週遭資料，若以這些資料作為依據，開發情境感知服務程式，將能自動提供符合使用者所需之功能。目前建構在Android系統上且以電子地圖作呈現的情境感知應用程式，多半是以GPS位置作為情境判斷之條件，進而提供差異化的服務，鮮少有以多個Context作為選擇的系統，這樣單一的判斷標準顯得捉襟見肘，使用上也不具彈性；而Android的開源特性造成的版本分裂，更使得程式本身在各版本間產生不相容的問題。
本研究旨在發展一套以Android平台為基底，實作情境感知結合定位服務之系統。不同以往單一的位置判斷情境，本研究以多種感測資料為依據，諸如GPS位置、時間及速度，判斷使用者位於何種場景內，自動提供相關功能與服務。本系統根據Android與Google Maps開放的API進行開發，以多種的感測資料提升場景判斷的周全性，並採用Web Application的方法作呈現主軸，夾帶其Thin Client與跨平台之優勢，降低手持裝置負擔且一併解決版本不相容問題，並具有手動模式的設定介面使其更具彈性。

Recently, smart phones are usually embedded with sensors to provide the context information such as location, time, ambient light, etc. These context information detected by sensors can be used in the context aware services in these handheld devices. However, most of the context-aware applications in handheld devices only use the location information from GPS to identify the scenes and services. There are few systems using more contexts as an optional.
In this thesis, we develop a context aware platform which can dynamically use more than one context as the reasoning base. Our system is built on the electronic map of the Android system for smart phones. This system provides the flexibility of using different contexts, such as location, time, and speed, as the main reasoning context to switch among different services, in addition, manual mode is also provided in this system. Our system is developed using Google Maps Library and thin client web programming technology, which provides the merits of better compatibility for different versions of Android systems. It can reduce the burden of handheld devices and versions fragmentation.

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