Evolution of Video Surveillance Systems: from Analog Cameras to Intelligent Video Analytics Systems Based on Edge Computing
DOI:
https://doi.org/10.15407/intechsys.2025.03.056Keywords:
video surveillance, video analytics, edge computing, artificial intelligence, computer vision, deep learning, neural networks, distributed systems, decentralized data processing, computational efficiencyAbstract
Introduction. Video surveillance systems have undergone significant evolution from primitive analog devices to highly intelligent networks with distributed computing and video analytics. Current industry development is characterized by the implementation of edge computing concept, which fundamentally changes architectural approaches to building intelligent video analytics systems. Unlike traditional centralized video data processing on remote servers, the edge computing paradigm involves transferring computational processes directly to surveillance cameras and local edge devices.
The purpose of the paper is a comprehensive analysis of the evolution of video surveillance systems from analog technologies to modern intelligent solutions based on edge computing, identification of key technological innovations, and forecasting promising development directions with particular attention to comparative analysis of traditional centralized approaches and edge computing technology.
Methods. The research is based on systematic analysis of historical stages of video surveillance systems development, comparative analysis of architectural solutions and functional capabilities of different generations of video analytics systems, study of artificial intelligence algorithms evolution and assessment of edge computing advantages over centralized approaches.
Results. Four main evolutionary stages were identified: analog systems era (1950-1990), digital revolution (1990–2010), cloud era (2010–2018) and edge computing era (2018-present). It was demonstrated that edge computing provides significant network traffic reduction, latency minimization, energy efficiency improvement and personal data protection compared to traditional approaches.
Conclusions. The evolution of video surveillance systems is characterized by paradigmatic changes from centralized to decentralized data processing. Edge computing forms the foundation for a new generation of solutions that combine high functionality, energy efficiency, and privacy protection. Future development is associated with convergence of 5G/6G technologies, augmented reality and Internet of Things.
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