Design of Human Detection in Home Security
Abstract & Details
Research Area
Electrical Engineering
Keywords
CCTV
SSD
Smartphone
Raspberry Pi
Human detection
Abstract
A home security system is needed to keep objects in the house safe from human interference. This system requires early information on human presence that might endanger security, so the human detection system is one of the most important parts of a home security system. Many people install Closed-Circuit Television (CCTV) at home to maintain home security, so that events that occur around the house can be known. Most of the CCTV installed at home functions as a monitoring and recording of events that occur around the house. With current technological developments, an object such as a human can be recognized and identified through a human object recognition program. By combining a human recognition system with CCTV, as well as a smartphone communication device, a home security system will be produced that can provide information to the smartphone if humans are detected around the house. A human recognition program that is embedded in mini-computer devices such as the Raspberry Pi 4 and gets input in the form of video results from CCTV, then the recorded events around the house can be displayed on a smartphone. In this paper, before the system can recognize human objects, the system first performs the process of detecting human objects using the Single-shot Multibox Detector (SSD) method. The use of the SSD method in detecting human objects has an accuracy rate of more than 80%. By integrating this home security system into a smartphone, users can carry out monitoring functions online and in person and will receive alerts in the form of notifications from applications when video recordings of CCTV detect a human objects.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Wahyudi | Diponegoro University |
| 2 | Kevin Inzaghi Zezha | Diponegoro University |
| 3 | Munawar Agus Riyadi | Diponegoro University |
| 4 | Imam Santoso | Diponegoro University |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Wahyudi, Zezha, Kevin Inzaghi, Riyadi, Munawar Agus, & Santoso, Imam (2024). Design of Human Detection in Home Security. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 5366-5374.
MLA Style
Wahyudi, et al. "Design of Human Detection in Home Security." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 5366-5374.
IEEE Style
Wahyudi, Kevin Inzaghi Zezha, Munawar Agus Riyadi, and Imam Santoso, "Design of Human Detection in Home Security," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 5366-5374, 2024.
Vancouver Style
Wahyudi, Zezha Kevin Inzaghi, Riyadi Munawar Agus, Santoso Imam. Design of Human Detection in Home Security. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):5366-5374.
Harvard Style
Wahyudi, Zezha, Kevin Inzaghi, Riyadi, Munawar Agus, & Santoso, Imam (2024) 'Design of Human Detection in Home Security', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 5366-5374.
Chicago Style
Wahyudi, et al. "Design of Human Detection in Home Security." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 5366-5374.
Turabian Style
Wahyudi, et al. "Design of Human Detection in Home Security." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 5366-5374.
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