International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 19 |
Year of Publication: 2021 |
Authors: Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain |
10.5120/ijca2021921533 |
Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain . Intruder Detection System using Posture Recognition and Machine Learning. International Journal of Computer Applications. 183, 19 ( Aug 2021), 17-23. DOI=10.5120/ijca2021921533
Generally, Science and technology always being persuaded when there is a need. Being secured is the utmost desire of every creatures in this world of insecurity. It is very much tough to have human security systems everywhere all the time. So in that case a system capable of atleast detection and warning of possible threats or dangers can be welcomed. In this context , one of the best way to achieve this goal is to build an intruder detection system . Intruders may be physical in nature or in case of computer networks there are network intruders also. But here in this paper it has been tried to present a comprehensive study about physical intruder detection system. In this attempt it has been presented a detailed hypothesis about intruder detection system in the light of gait recognition. It is also put in front of how research works had been done in earlier days and also used some machine learning algorithms on some human gait datasets to obtain results which is thought to give a brief idea in this domain.