What is it about?
The excessively increasing demand for bandwidth resources entails many challenges in terms of acquiring data while saving its acquisition resources. Surveillance systems are of those vital applications that consume data bandwidth. In this paper, a smart prototype surveillance system is proposed using machine learning techniques as a means of saving bandwidth by transmitting only significant information through the system's resources. The proposed system operates in two modes; motion detection and face recognition. Promising and interesting results were obtained in terms of bandwidth and storage saving.
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Why is it important?
We use networks in our everyday lives almost every day, on this paper we focused on making that usage much more efficient with as few resources as possible.
Perspectives
Writing this article was a great experience, we the authors have different expertise and skillsets and we tried to merge our software and network expertise to develop a tool that makes network utilization more powerful.
Salim Alsaeh
Read the Original
This page is a summary of: A Smart Resource-efficient Surveillance System, September 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3410352.3410805.
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