Abstract
The purpose of the system is to provide a powerful and intelligent surveillance tool to the police force so as to reduce crime. The law enforcement agencies have been motivated to use video surveillance systems to monitor and curb these threats. But this becomes a tedious task, prone to human errors. The core module of this system estimates the pose in humans present in the video and a backend capable of understanding the context as a whole. Many AI-powered surveillance systems are good at recognizing violent or malicious activity but fail to understand the context as a whole. We aim to understand the gradual change in human behavior in the given scenario, understand the confidence level of each expression and derive if the given scenario is truly violent or malicious. The Ornithopter is allowed to follow the suspect wherein the direction offsets are given by the server. The system differs from any state-of-the-art surveillance system as it provides aerial surveillance covering larger areas, and since the drone is bird-shaped, it can easily navigate the area without being easily detected. And as mentioned, the recognition of the true violent or malicious activity is context-based.
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This work was supported by Mumbai University’s Minor Research Grant.
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Suralkar, S., Gangurde, S., Chintakindi, S., Chawla, H. (2020). An Autonomous Intelligent Ornithopter. In: Pandian, A., Palanisamy, R., Ntalianis, K. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019). ICCBI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-030-43192-1_93
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DOI: https://doi.org/10.1007/978-3-030-43192-1_93
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