AN INVESTIGATION INTO THE FEASIBILITY OF INCORPORATING ESSENTIAL COMPUTER VISION CAPABILITIES FROM NETWORK VIDEO ANALYTICS (NVA) INTO A CLOUD-BASED SURVEILLANCE SYSTEM.

Abstract

The cloud-based surveillance system can be identified as transmitting footage from security cameras on the internet while using remote cloud servers for storing them, management of the footages as well as analysis of the same. On the other hand, network video analytics can be assessed as a technology using computer algorithms that is powered by artificial intelligence (AI) and computer vision to manage automatic streaming of video from IP cameras, extracting important information, identifying as well as understanding the information in real time. The main purpose of this project, which is located in China, is to provide important computer vision features from Network Video Analytics (NVA) to cloud-based monitoring systems. The specific instance to be analysed is China. The investigation also looked into how possible the activity stated earlier is. People think that China's surveillance technology will change from passive recording to active, smart systems that can analyse and make choices in real time. Everyone is looking forward to this. This is beginning to happen more and more regularly, and people are learning to anticipate it. This is because China is always getting closer to reaching its goals in the fields of smart city development and national security. Because of this change, computer vision features including object identification, face recognition, anomaly detection, and behaviour analysis are in great demand. Object detection and face recognition are two of the numerous things that fall under this category. These traits help the flow that was spoken about before happen so that unstructured visual data may be turned into structured inputs for higher-order analytics.