A Multistage Procedure of Mobile Vehicle Acoustic Identification for Single-Sensor Embedded Device

Astapov, Sergei; Riid, Andri

doi:10.2478/eletel-2013-0018

Cited by 9 publications

(3 citation statements)

References 16 publications

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“…These features may offer a simple and cost-effective solution, as they can be directly extracted from the original signal without any transformation. 25 ZCR and root mean square (RMS) are considered to be the most important and influential time domain features; thus, these features have been adopted by numerous applications, including speech–music discrimination, 26 sound/object classification, 27–29 and animal classification tasks. 5,9…”

Section: Related Workmentioning

confidence: 99%

Energy-efficient scheme for target recognition and localization in wireless acoustic sensor networks

Algobail

Soudani

Al-Ahmadi

2019

International Journal of Distributed Sensor Networks

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The development of wireless acoustic sensor networks has driven the use of acoustic signals for target monitoring. Most monitoring applications require continuous network connectivity and data transfers, which can rapidly exhaust nodes’ energy. Consequently, sensors must collaborate in an adequate architecture to perform target recognition and localization tasks and then to send the results to a remote server with a reduced data volume. The design of an energy-efficient scheme that achieves acoustic target recognition and localization remains an open research problem. Accordingly, this article proposes a low-energy acoustic-based sensing scheme for target recognition and localization to be implemented in a cluster-based sensing approach designed to appropriately balance energy consumption and local processing performed by sensor nodes. A reduced set of low-complexity feature extraction methods in the time domain signal are used in the recognition process. The scheme uses the received energy of the acoustic signals for the target localization. This article details the network architecture, the scheme specification, and its implementation. The results show that the scheme can classify targets with 81.34% accuracy. It requires 3.2 mJ of energy when executed in MICAz, achieving 99% energy savings compared to streaming 3 s of an acoustic signal to a remote server.

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Section: Related Workmentioning

confidence: 99%

Energy-efficient scheme for target recognition and localization in wireless acoustic sensor networks

Algobail

Soudani

Al-Ahmadi

2019

International Journal of Distributed Sensor Networks

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“…On the other hand, acoustic signals are prone to noise pollution, especially in unconfined environments, where ambient noise variance and the nature of different background noises are undetermined. For single-sensor solutions, noise poses a great problem because these solutions are unable to efficiently filter unknown noise types [1]. However, the situation changes radically if the acoustic sensors are used in array configurations.…”

Section: Introductionmentioning

confidence: 99%

Optimized Acoustic Localization with SRP-PHAT for Monitoring in Distributed Sensor Networks

Astapov¹,

Berdnikova²,

Preden³

2013

International Journal of Electronics and Telecommunications

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Abstract-Acoustic localization by means of sensor arrays has a variety of applications, from conference telephony to environment monitoring. Many of these tasks are appealing for implementation on embedded systems, however large dataflows and computational complexity of multi-channel signal processing impede the development of such systems. This paper proposes a method of acoustic localization targeted for distributed systems, such as Wireless Sensor Networks (WSN). The method builds on an optimized localization algorithm of Steered Response Power with Phase Transform (SRP-PHAT) and simplifies it further by reducing the initial search region, in which the sound source is contained. The sensor array is partitioned into sub-blocks, which may be implemented as independent nodes of WSN. For the region reduction two approaches are handled. One is based on Direction of Arrival estimation and the other -on multilateration. Both approaches are tested on real signals for speaker localization and industrial machinery monitoring applications. Experiment results indicate the method's potency in both these tasks.

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“…The emergence and development of vehicle network bring us not only obvious security vulnerabilities, but also the flexibility increase of wireless access. So some inherent characteristics of vehicle network are actually the potential vulnerabilities, which are shown in the table (1).…”

mentioning

confidence: 99%

The application of improved-DAA for the vehicle network node security in single- and multi-trusted domain

Ren¹,

Zhang²,

Lou³

2015

Discrete &Amp; Continuous Dynamical Systems - S

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Similar to network, vehicle-mounted system has its own vulnerability, which can be used by the attackers. Different from the traditional network security technologies, node security is one of the most important technologies of the vehicle network and it is difficult to achieve because of the mobility and flexibility. In this paper, trusted computing and direct anonymous attestation theories are adopted to establish protocol system of trusted vehicle information authentication, thus the security of authentication process for nodes in vehicle network can be improved. First, we use DAA to achieve the identity authentication for the accessor in single-trusted domain. Second, the improved-DAA will be used to try to promote the security situation in multi-trusted domain. It is illustrated that the efficiency of verification can be increased and the possibility of being attacked can be decreased in single-trusted domain. And the execution efficiency in multi-trusted domain can be improved theoretically.

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A Multistage Procedure of Mobile Vehicle Acoustic Identification for Single-Sensor Embedded Device

Cited by 9 publications

References 16 publications

Energy-efficient scheme for target recognition and localization in wireless acoustic sensor networks

Energy-efficient scheme for target recognition and localization in wireless acoustic sensor networks

Optimized Acoustic Localization with SRP-PHAT for Monitoring in Distributed Sensor Networks

The application of improved-DAA for the vehicle network node security in single- and multi-trusted domain

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