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Developing A Smart Home Surveillance System Using Autonomous Drones

delete2023-10-12
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PRE
AI
C
Chongju Mai *
A
Anwar Haque
DOI:10.1109/WF-IOT58464.2023.10539449delete
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摘要

摘要

En 中文
Placing a number of home surveillance cameras around the property can enhance home security. However, camera coverage and their true effectiveness can be limited due to the limited number of cameras that can be installed, camera's field of view, camera's fixed position, and associated privacy issues. Unmanned aerial vehicles (UAVs), commonly known as drones, are able to fly independently without any human intervention. There are already a few commercially available options for outdoor drone surveillance, but none for indoor applications. We believe the drones can be effectively deployed for home monitoring purposes in a cost-effective and privacy-preserving manner. In this paper, we developed a novel autonomous drone prototype that can offer economically viable effective smart home monitoring capabilities than currently available home monitoring solutions in today's smart home industry. While in flight, our developed drone navigation system can fly on any predefined paths, dynamically change the paths based on user requirements to inspect any place within its range and adapt to unanticipated situations, such as obstacle avoidance and low battery. In addition, the system can utilize machine learning to evaluate the camera stream from the onboard camera and perform object detection tasks and notify users accordingly. In our testing, we demonstrated that our developed prototype successfully performed all the functions mentioned above. Also, our novel findings from this paper shed light on some of the important parameters of indoor drone-based monitoring systems, which will contribute to the further advancement in drone-based home monitoring technology.
Keyword:
UAV
Quadrotor
Smart home
Home monitoring
Indoor drone surveillance

期刊

I
IEEE World Forum on Internet of Things
IF:
0
论文数:
26
被引数:
0

机构

W
western university (university of western ontario)
学者数:
2.9W
论文数: 2.7W
被引数: 33
引用论文

引用论文

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PREAI
errJin-Hong Lin; Xing Zheng; Ji-Chang Xiao; Jin Long; Jia Chen; Rong Li; Zhuo Liu; Xuan Xiao
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