現在城市發展越來越迅速，人們想要讓生活更便利的需求也越來越多，基於這些需求所以我們針對城市提供一套系統供使用者去檢索路況圖片的以及該路況的圖片的環境感測資訊，例如：溫度、濕度、二氧化碳濃度⋯⋯由於現在智慧型手機在大型城市的普及化，所以前端的程式設計便以手機APP爲主；鑒於後端需要儲存大量資訊且提供使用者快速的搜索查詢，因為Hadoop可平行化資料處理，且建置成本便宜，所以我們採用Hadoop雲端資料處理系統爲主軸;我們先進行圖片的蒐集與資料的探測統計上傳至Hadoop雲端系統經由MapReduce後，配合HDFS檔案系統和HBase資料庫儲存照片及感測資訊，再提供給前端Android手機作存取，期望實現基於Hadoop平台之智慧城市感測資訊檢索系統Android APP實作，以利使用者可以簡單地利用Android APP對整個城市能更完善且便利地了解到整個城市的環境情況。 With the rapid development of modern cities, the demands for convenience of living in big cities are also increasing, which lead to the ubiquitous deployment of sensor devices in intelligent cities. It is without doubt that how to deal with the huge amount of data collected by various sensors in an efficient way and to transform these data to useful information for people to make use of has become an important research topic. In this thesis, we developed a sensor data retrieval system for the citizens to query the information that are stored in a Hadoop cluster. The sensor data are captured along the roads, and are embedded in the image files that were also taken along the roads. Therefore, the system is designed to allow citizens to view the street images around the city, as well as read the road conditions such as the temperature, humidity, carbon dioxide concentration, and so on. Furthermore, due to the popularity of smartphones, we developed an Android APP as the front end for citizens who would like to access the sensor data. Through this Android APP, users can be authenticated and then granted access to the system, in which the street images and the sensor data are stored in Hadoop Distributed File System (HDFS) and HBase, respectively. By clicking on the Google Maps user interface, users are able to view the road conditions along and nearby a specific route between the origin and the destination. We believe that the developed Android APP can contribute to better living of the citizens in intelligent cities.