Acoustic intruder detection system for home security

Choi, Y. S.; Kim, Ki-Man; Jung, Ji-Won; Chun, Seung-Yong; Park, Kyu-Sik

doi:10.1109/tce.2005.1405710

Cited by 19 publications

(9 citation statements)

References 9 publications

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“…In addition to video surveillance, acoustic [7] or infrared technology [11] can also be used to identify intrusion to some extent. Choi et al [12] estimated the amount of change in the acoustic signature in the house through the acoustic wave propagation function and then judged whether it was an intruder. Because the body temperature is similar to the constant temperature, and bodies will always emit heat, Cheng et al [13] used a pyroelectric infrared sensor to detect the body's infrared radiation.…”

Section: Related Workmentioning

confidence: 99%

CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

et al. 2018

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Passive indoor personnel detection technology is now a hot topic. Existing methods have been greatly influenced by environmental changes, and there are problems with the accuracy and robustness of detection. Passive personnel detection based on Wi-Fi not only solves the above problems, but also has the advantages of being low cost and easy to implement, and can be better applied to elderly care and safety monitoring. In this paper, we propose a passive indoor personnel detection method based on Wi-Fi, which we call FDF-PIHD (Frequency Domain Fingerprint-based Passive Indoor Human Detection). Through this method, fine-grained physical layer Channel State Information (CSI) can be extracted to generate feature fingerprints so as to help determine the state in the scene by matching online fingerprints with offline fingerprints. In order to improve accuracy, we combine the detection results of three receiving antennas to obtain the final test result. The experimental results show that the detection rates of our proposed scheme all reach above 90%, no matter whether the scene is human-free, stationary or a moving human presence. In addition, it can not only detect whether there is a target indoors, but also determine the current state of the target.

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Section: Related Workmentioning

confidence: 99%

CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

et al. 2018

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“…Further, it works properly only in the line-of-site transmission and is difficult to hide from intruders. Another intrusion detection system could be based on the scattered reflections generated by a pulsed light or acoustic signals [9][10][11]. This concept is analogous to the radar challenge of transmitting a pulsed signal.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing

Al-Khalli,

Alateeq,

Almansour

et al. 2023

Sensors

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Modern home automation systems include features that enhance security, such as cameras and radars. This paper proposes an innovative home security system that can detect burglars by analyzing acoustic signals and instantly notifying the authorized person(s). The system architecture incorporates the concept of the Internet of Things (IoT), resulting in a network and a user-friendly system. The proposed system uses an adaptive detection algorithm, namely the “short-time-average through long-time-average” algorithm. The proposed algorithm is implemented by an IoT device (Arduino Duo) to detect people’s acoustical activities for the purpose of home/office security. The performance of the proposed system is evaluated using 10 acoustic signals representing actual events and background noise. The acoustic signals were generated by the sounds of keys shaking, the falling of a small object, the shrinking of a plastic bag, speaking, footsteps, etc. The effects of different algorithms’ parameters on the performance of the proposed system have been thoroughly investigated.

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“…Intrusion detection using microphones is as effective as the use of security cameras in terms of detecting moving objects [4], and the related studies are summarized below. Studies on intrusion detection have been conducted to determine an intrusion in a security zone based on the change in the room transfer function [16], the sound field variation according to the acoustical transmission path of distributed microphones [17], and the coherence responses in low-frequency environments [18].…”

Section: Introductionmentioning

confidence: 99%

“…IR sensors have limitations that often cause errors because of their nonlinear sensitivity and the effects of nearby objects [21]. Therefore, if the acoustic-based intrusion detection in [16][17][18] is applied to the security system to compensate for the weakness in IR sensors, the two sensing systems can complement each other to increase the robustness of the intrusion detection. In the second example, when a microphone array detects the direction of an event, a pan-tilt-zoom (PTZ) camera is rotated and focused on the region of interest [8].…”

Section: Introductionmentioning

confidence: 99%

Acoustic-Based Position Estimation of an Object and a Person Using Active Localization and Sound Field Analysis

et al. 2020

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This paper proposes a new method to estimate the position of an object and a silent person with a home security system using a loudspeaker and an array of microphones. The conventional acoustic-based security systems have been developed to detect intruders and estimate the direction of intruders who generate noise. However, there is a need for a method to estimate the distance and angular position of a silent intruder for interoperation with the conventional security sensors, thus overcoming the disadvantage of acoustic-based home security systems, which operate only when sound is generated. Therefore, an active localization method is proposed to estimate the direction and distance of a silent person by actively detecting the sound field variation measured by the microphone array after playing the sound source in the control zone. To implement the idea of the proposed method, two main aspects were studied. Firstly, a signal processing method that estimates the position of a person by the reflected sound, and secondly, the environment in which the proposed method can be operated through a finite-difference time-domain (FDTD) simulation and the acoustic parameters of early decay time (EDT) and reverberation time (RT20). Consequently, we verified that with the proposed method it is possible to estimate the position of a polyvinyl chloride (PVC) pipe and a person by using their reflection in a classroom.

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Acoustic intruder detection system for home security

Cited by 19 publications

References 9 publications

CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

Real-Time Detection of Intruders Using an Acoustic Sensor and Internet-of-Things Computing

Acoustic-Based Position Estimation of an Object and a Person Using Active Localization and Sound Field Analysis

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