Open AccessA Development of the Internet of Things based Intruder Detection and Security Alarm System
Author(s) -
Akkasit Sittisaman,
Naruepon Panawong
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f8606.088619
Subject(s) - alarm , computer science , android (operating system) , python (programming language) , raspberry pi , the internet , home security , embedded system , internet of things , real time computing , computer security , operating system , engineering , aerospace engineering
Intruders usually break into houses with the intention of committing burglaries. This research proposed a development of an intrusion detection and security Alarm System using the Internet of Things. The methodology of the proposed system consists of five components. First, the hardware components are Raspberry Pi 3 Model B+, a camera for Raspberry Pi, motion sensors, relays and speakers, while the software system was developed by Python. Second, the architecture of the proposed system. Third, the design and construction of the electronic circuit connected with sensors. Fourth, the intruder image analysis for the alarm system using OpenCV and Deep Learning. The face detected by the camera was compared with homeowner’s pictures. If the detected face was not the homeowner, the system alarms the user or the owner via the smartphone LINE Application. Last, the Anto, which is the free and easy Internet of Things platform, connect the devices and the smartphone application together via the internet. Hence, the users or homeowners can control the devices or take the picture from a distance using a smartphone. The experimental results show that the proposed system can detect the intruder and alarm the homeowner via LINE Application on the smartphone. The experimental results show that the proposed system can efficiently detect the intruder and alarm the homeowner via LINE Application on the smartphone. The performance of the proposed system is excellent with the average score of 97.40%. The developed application on the Android smartphone is user-friendly, simple and efficient as well.