Cloud-based surveillance system under Hadoop

• Main Authors: Wang, Kuang-Hsin, 王廣新
• Other Authors: Yuan, Shyan-Ming
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/59297974316482725855

碩士 === 國立交通大學 === 資訊學院資訊學程 === 100 === Information technology has been widely used to solve many problems in many domains. Many cameras have been installed at the corner of streets for maintaining public order or monitoring traffic status. The recorded video data is stored to the traditional surveillance system or NVR in public department for future inquiry. However, the traditional surveillance system could not process and store large amount of data generated from large number of cameras. Moreover, user must to increase NVR by manual. Thus, scaling up traditional surveillance system increases the cost and complexity of management. In addition, traditional surveillance system is not capable of handling exception break situations such as blackout and system crash while storing streaming data to storage nodes. Thus, the purpose of this thesis is to propose a cloud-based surveillance system to solve these problems. The proposed system integrates Hadoop to store large amount of streaming and provides a backup mechanism to handle the exception break situations. By integrating HaDoop File System(HDFS), the approach of this thesis can easily scale up the system for processing corresponding large amount of data generated from cameras. The cluster central of Hadoop is integrated with a novel backup mechanism for handling exception break situations. The evaluation results show that the proposed system can easily process the increasing number of video streams and lost only a few frames while handling the exception break situation. The result suggested that replacing NVR to the proposed cloud-based surveillance system under Hadoop with our backup mechanism is practicable.