A STUDY TO ASSESS THE VIABILITY OF INTEGRATING CRUCIAL COMPUTER VISION FUNCTIONS FROM NETWORK VIDEO ANALYTICS (NVA) INTO A CLOUD-BASED SURVEILLANCE SYSTEM.

Abstract

One thing that makes a cloud-based surveillance system different is that it can send footage from security cameras via the internet. It also employs distant cloud servers for storage, data management, and analysis, which makes it different from other forms of surveillance systems. This feature makes the system more efficient than other surveillance systems. On the other hand, this technology might be considered as technology in a way that is different from how most people think of it. The goal of this system is to be able to control the automated streaming of video from IP cameras, as well as to obtain important information, figure out what the data is, and analyse it in real time. The main purpose of this study is to provide people access to important computer vision skills, which includes things like Network Video Analytics (NVA) and cloud-based monitoring tools. A lot of people think that China's surveillance technology will eventually go from just recording to active, smart systems that can analyse and evaluate things in real time. The reason for this is that China is steadily getting closer to reaching its goals in national security and smart city development. One of the many reasons this development is so important is because it came about because of this. Due to this change, benefits of computer vision are in great demand, especially for tasks like recognising faces, finding strange things, and analysing conduct. It is possible to turn unstructured visual data into structured inputs for advanced analytics by employing these features, which make the flow that was spoken about before possible.