Edge computing provides the ability to link distributor users for multimedia content, while retaining the power of significant data storage and access at a centralized computer. Two requirements of significance include: what information show be processed at the edge and how the content should be stored. Answers to these questions require a combination of query-based search, access, and response as well as indexed-based processing, storage, and distribution. A measure of intelligence is not what is known, but is recalled, hence, future edge intelligence must provide recalled information for dynamic response. In this paper, a novel event-oriented indexable and queryable intelligent surveillance (EIQIS) system is introduced leveraging the on-site edge devices to collect the information sensed in format of frames and extracts useful features to enhance situation awareness. The design principles are discussed and a preliminary proof-of-concept prototype is built that validated the feasibility of the proposed idea.
For instance, in a smart transportation application following a hierarchical system architecture, data is accessed by the sensors implemented on buses and transferred to a fog node where contextualization and decision making happens @cite_2 . For video surveillance systems, the remote cloud is mainly used for profile building, pattern analysis, and long term historical record analysis.
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Recently, various conferences and journals have published articles related to Video Surveillance Systems, indicating researchers' attention. The goal of this review is to examine the latest works were published in journals, propose a new classification framework of video surveillance systems and investigate each aspect of this classification framework. This paper provides a comprehensive and systematic literature review of video surveillance systems from 2010-2011, extracted from six online digital libraries using article's title and keyword. The proposed classification framework is expanded on the basis of architecture of video surveillance systems, which is composed of six layers: Concept and Foundation Layer, Network Infrastructure Layer, Processing Layer, Communication Layer, Application Layer, and User Interaction Layer. This review shows, although many publication and research focus on real-time aspect of the challenge, only few researches have investigated the deployment of extracted and retrieved information for forensic video surveillance.