SVM-instance based approach to improve QoS parameters for time critical applications in WSN

Author

Chitra, V. P. Jaya ; Sumalatha, M.R.

Author_Institution

Dept. of Comput. Technol., Anna Univ., Chennai, India

fYear

2012

fDate

13-15 Dec. 2012

Firstpage

1

Lastpage

6

Abstract

The QoS factors such as accuracy and time delay plays a major role in time critical applications. The proposed SVM-instance based algorithm improves the accuracy and reduces the time delay for the recognition of emergency vehicle sound. In this approach, the time delay is reduced by identifying the support vectors which are the data points near the margin of hyper plane and the accuracy is increased by increasing the margin between the classes. The MFCC which is derived from frequency and intensity is used for accurate sound recognition. Thus time delay was reduced and accuracy was improved in recognition of emergency vehicle sound.

Keywords

acoustic signal detection; automated highways; cepstral analysis; delays; emergency services; quality of service; road vehicles; support vector machines; wireless sensor networks; MFCC; Mel frequency cepstral coefficient; QoS factors; QoS parameter improvement; SVM-instance based algorithm; WSN; accuracy improvement; emergency vehicle sound recognition; hyper plane margin; support vector identification; support vector machine; time critical applications; time delay reduction; wireless sensor networks; Accuracy; Delay effects; Feature extraction; Mel frequency cepstral coefficient; Support vector machines; Vehicles; Wireless sensor networks; Accuracy; Mel Frequency Cepstral Coefficient; SVM-Instance; Siren sound; Time delay; Wireless Sensor Networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computing (ICoAC), 2012 Fourth International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4673-5583-4

Type

conf

DOI

10.1109/ICoAC.2012.6416862

Filename

6416862