傳統的監視系統大部分都是人們需要坐在監控端前面盯著螢幕，監視時間一旦久了，注意力就會相對的不集中，同時會造成即使物體進入監視畫面也會不易發現的情況發生，進而造成許多的意外事故或社會案件的發生；因此本文提出一個可人臉偵測的智慧雲端監視架構的系統，希望藉由雲端的高運算能力來實現遠端監視系統人臉偵測，以降低人工監視之缺點。在人臉偵測方面，本文使用了Apache公司所發展出來的軟體Hadoop，使用此軟體是因為Hadoop屬於分散式運算平台，其能有效的將數據量大的資料透過Map/Reduce的平行化處理方式，能比傳統的運算方式更加快速的將處理結果運算出來，對於人臉影像處理的速度有很大的幫助。本論文主要發展一套以雲端為中心的智慧型監控系統；此雲端系統可分為三大部分，第一部分是CCD(Charge-Coupled-Device)攝影機控制端，負責傳送影像資料；第二部分為影像處理端，負責處理影像中偵測人臉的部分，處理後的人臉數據保留在伺服器中，而人臉偵測結果則透過第三部分網路應用伺服器來顯示。 Traditional surveillance systems are mostly people need to sit staring at the screen in front of monitoring terminal. Once a long time for staring at the screen, attention will be relatively non-centralized, and it will cause the situation happened that even objects into the monitor screen will be difficult to find, and then cause the emergence of a lot of contingencies or social cases. Therefore this thesis proposed a cloud-based intelligence surveillance system for face detection. In this system, the face detecting function of remote monitoring system can be achieved through the high computing ability of the cloud to reduce the shortcomings of manual monitoring.In face detection, this research uses the Apache software developed by the company Hadoop, the reason for using this software is that Hadoop belong to a distributed computing platform,which can effectively process a large quantity of data through the Map/Reduce parallel processing mode, and the computing result is more fast than the traditional operation way, so it is very helpful for the face image processing speed.The purpose of this thesis is to developa cloud-centric intelligent monitoring system. This cloud system can be divided into three parts. The first part is the CCD(Charge-Coupled-Device) camera control side, which is responsible for transmitting the image data. The second part is the image processing end, which is responsible for the image data computing of face detection, and the treated face data will be remained on the server. Finally, the third part is the network application server, which is used to display the face detecting results.