Abstract
Mobile automated video surveillance system involves application of real-time image and video processing algorithms which require a vast quantity of computing and storage resources. To support the execution of mobile automated video surveillance system, a mobile ad hoc cloud computing and networking infrastructure is proposed in which multiple mobile devices interconnected through a mobile ad hoc network are combined to create a virtual supercomputing node. An energy efficient resource allocation scheme has also been proposed for allocation of realtime automated video surveillance tasks. To enable communication between mobile devices, a Wi-Fi Direct based mobile ad hoc cloud networking infrastructure has been developed. More specifically, a routing layer has been developed to support communication between Wi-Fi Direct devices in a group and multi-hop communication between devices across the group. The proposed system has been implemented on a group of Wi-Fi Direct-enabled Samsung mobile devices.
Highlights
Automated Video Surveillance Systems (AVSS) are used to monitor and analyze numerous situations and take necessary actions in real-time (Valera and Velastin, 2005)
The proposed scheme focuses on allocation of real time tasks and aims to reduce energy consumption
Allocate to task ti to node ni Automated video surveillance system comprising of object detection, object tracking and object classification tasks have been implemented on a single node and on a mobile ad hoc cloud system consisting of three mobile nodes
Summary
Automated Video Surveillance Systems (AVSS) are used to monitor and analyze numerous situations and take necessary actions in real-time (Valera and Velastin, 2005). The AVSS comprises of object detection, object tracking, object classification, behavior analysis and action tasks. The object detection task detects the object such as a person, vehicle, or an animal in digital images and videos. Object classification task is used to label the detected object as a person, a group of person, vehicle, or an animal (Shah et al, 2007; Teddy, 2011). One of the complicated tasks in AVSS is behavior analysis which is responsible for activity recognition and situation awareness. Based on the outcome of behavior analysis task, necessary actions are taken (Teddy, 2011; Yilmaz et al, 2006). AVSS have applications in numerous areas including disaster management and military operations
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