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Human Suspicious Activity Detection Using Ensemble Machine Learning Techniques

Publication Type : Conference Proceedings

Source : 2022 2nd International Conference on Intelligent Technologies (CONIT)

Url : https://ieeexplore.ieee.org/document/9848183

Campus : Bengaluru

School : School of Computing

Verified : No

Year : 2022

Abstract : Public safety is a concern, especially with our growing population. An increasing population also calls for effective crowd management and it is not possible to manually monitor a huge crowd. A lot of approaches to this problem are being analyzed, and with this paper, we have implemented the problem with ensemble learning techniques which will detect suspicious activities. An automated alert system is also set up to detect, record and report suspicious activities to the concerned authorities. Therefore, the anomalous activity detection system will provide a basic surveillance system with an alarm which will help for safety of the public along with lesser costs and more security.

Cite this Research Publication : Aqil Shamnath, Meena Belwal "Human Suspicious Activity Detection Using Ensemble Machine Learning Techniques", 2022 2nd International Conference on Intelligent Technologies (CONIT)

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