A method of real-time mobile vehicle identification by means of acoustic noise analysis implemented on an embedded device

2013 ◽

Vol 59 (2) ◽

pp. 151-160 ◽

Cited By ~ 6

Author(s):

Sergei Astapov ◽

Andri Riid

Keyword(s):

Real Time ◽

Audio Signals ◽

Event Identification ◽

Embedded Device ◽

Mobile Vehicle ◽

Vehicle Identification ◽

Time Operation ◽

Real Time Operation ◽

Single Sensor ◽

Acoustic Identification

Abstract Mobile vehicle identification has a wide application field for both civilian and military uses. Vehicle identification may be achieved by incorporating single or multiple sensor solutions and through data fusion. This paper considers a single-sensor multistage hierarchical algorithm of acoustic signal analysis and pattern recognition for the identification of mobile vehicles in an open environment. The algorithm applies several standalone techniques to enable complex decision-making during event identification. Computationally inexpensive procedures are specifically chosen in order to provide real-time operation capability. The algorithm is tested on pre-recorded audio signals of civilian vehicles passing the measurement point and shows promising classification accuracy. Implementation on a specific embedded device is also presented and the capability of real-time operation on this device is demonstrated.

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Hybrid Acoustic Noise Analysis Approach of Conventional and Mutually Coupled Switched Reluctance Motors

IEEE Transactions on Energy Conversion ◽

10.1109/tec.2017.2672741 ◽

2017 ◽

Vol 32 (3) ◽

pp. 1042-1051 ◽

Cited By ~ 25

Author(s):

Jianning Dong ◽

James Weisheng Jiang ◽

Brock Howey ◽

Haoding Li ◽

Berker Bilgin ◽

...

Keyword(s):

Acoustic Noise ◽

Noise Analysis ◽

Analysis Approach ◽

Switched Reluctance Motors ◽

Switched Reluctance

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Platform for on-board real-time detection of wet, icy and snowy roads, using tyre/road noise analysis

2015 International Symposium on Consumer Electronics (ISCE) ◽

10.1109/isce.2015.7177776 ◽

2015 ◽

Author(s):

J. Alonso ◽

J.M. Lopez ◽

I. Pavon ◽

C. Asensio ◽

G. Areas

Keyword(s):

Real Time ◽

Noise Analysis ◽

Road Noise ◽

Real Time Detection

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Indoor Positioning Method Based on Infrared Vision and UWB Fusion

Journal of Physics Conference Series ◽

10.1088/1742-6596/2078/1/012070 ◽

2021 ◽

Vol 2078 (1) ◽

pp. 012070

Author(s):

Qianrong Zhang ◽

Yi Li

Keyword(s):

Real Time ◽

Indoor Localization ◽

Low Cost ◽

Ultra Wideband ◽

Coverage Area ◽

Positioning Accuracy ◽

Mobile Vehicle ◽

Positioning Method ◽

Positioning Algorithm ◽

Infrared Vision

Abstract Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.

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