Surveillance camera for doorstep motion detection and face recognition
As we are transforming into a smart nation, our standard of living has increased as well, especially the improved comfort and security in our in-house systems. Home security system has become an essential add-on not just for tech-loving home owners but as well as the most households now. Home securi...
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2017
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sg-ntu-dr.10356-708782023-07-07T16:28:31Z Surveillance camera for doorstep motion detection and face recognition Yang, Jingxia Chong Yong Kim School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems As we are transforming into a smart nation, our standard of living has increased as well, especially the improved comfort and security in our in-house systems. Home security system has become an essential add-on not just for tech-loving home owners but as well as the most households now. Home security is an expensive investment itself, but with the introduction of a tiny supercomputer called the Raspberry Pi, inexpensive security systems can now be created and even customised to suit the owners’ needs. This project aims to design and implement a security surveillance camera using Python language with the support of OpenCV library on Rasbian OS using a low-cost Raspberry Pi and camera module. Unlike any surveillance projects which use laptops or desktops, Raspberry Pi serves as a portable camera which can run on its own. This surveillance camera includes features with motion detection and face recognition abilities. Overall, this project aims to aid elderly and children, who are home alone, by alerting them when motion can be detected within the radius of their door steps and aid in recognising friends from strangers to prevent scam intruders. Bachelor of Engineering 2017-05-12T02:11:06Z 2017-05-12T02:11:06Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70878 en Nanyang Technological University 56 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems Yang, Jingxia Surveillance camera for doorstep motion detection and face recognition |
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As we are transforming into a smart nation, our standard of living has increased as well, especially the improved comfort and security in our in-house systems. Home security system has become an essential add-on not just for tech-loving home owners but as well as the most households now. Home security is an expensive investment itself, but with the introduction of a tiny supercomputer called the Raspberry Pi, inexpensive security systems can now be created and even customised to suit the owners’ needs. This project aims to design and implement a security surveillance camera using Python language with the support of OpenCV library on Rasbian OS using a low-cost Raspberry Pi and camera module. Unlike any surveillance projects which use laptops or desktops, Raspberry Pi serves as a portable camera which can run on its own. This surveillance camera includes features with motion detection and face recognition abilities. Overall, this project aims to aid elderly and children, who are home alone, by alerting them when motion can be detected within the radius of their door steps and aid in recognising friends from strangers to prevent scam intruders. |
author2 |
Chong Yong Kim |
author_facet |
Chong Yong Kim Yang, Jingxia |
format |
Final Year Project |
author |
Yang, Jingxia |
author_sort |
Yang, Jingxia |
title |
Surveillance camera for doorstep motion detection and face recognition |
title_short |
Surveillance camera for doorstep motion detection and face recognition |
title_full |
Surveillance camera for doorstep motion detection and face recognition |
title_fullStr |
Surveillance camera for doorstep motion detection and face recognition |
title_full_unstemmed |
Surveillance camera for doorstep motion detection and face recognition |
title_sort |
surveillance camera for doorstep motion detection and face recognition |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/70878 |
_version_ |
1772828012008439808 |