Signal Processing using Wavelet Transform on Sensor Nodes for Low Power Consumption
J. Hema shubraja1, G. Vijayalakshmy2

1J. Hema Shubraja, Department of Electronics and Communication Engineering, Kamban Engineering College, Tiruvannamalai, (Tamil Nadu), India.
2G. Vijayalakshmy, Department of Electronics and Communication Engineering, Perunthalaivar Kamarajar Institute of Engineering and Technology, India.

Manuscript received on 21 November 2013 | Revised Manuscript received on 28 November 2013 | Manuscript published on 30 November 2013 | PP: 15-21 | Volume-2 Issue-5, November 2013 | Retrieval Number: E0841112513/2013©BEIESP
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Abstract: Power consumption for different sensor interface utilized for wireless sensor is investigated. In that most sensor nodes used MCU to implement the main functionality in software. In other words such a unit consumes great deal of power for unused circuits. We propose the use of wavelet concepts to reduce the power consumption of small sensor node that has various sensors and wireless communication facilities, that were the result of an adaptive function specialization mechanism. Traditional sensor nodes must have had a powerful and multi functional Micro-Controller Unit (MCU) to satisfy the requirements for processing any kinds of application. However, most of these systems only use a part of the functions provided by an MCU. In other words, such a unit often consumes a great deal of power for unused circuits. To avoid this situation, we propose the use of wavelet transform processing technique instead of an MCU because this array dynamically changes the circuit to the optimal one that is just used for the calculation required by an application. Moreover, we implemented a prototype system to do a preliminary evaluation of our proposed mechanism. Here processing time and power consumption using Discrete wavelet transform (DWT) for testing the processing function on sensor nodes is proposed. Here the performance of proposed wavelet technique with the existing FFT model is compared and analysed. The performance in terms of noise and power are analysed. The experimental result shows that proposed mechanism reduces enough power of its sensor nodes to prolong the lifetime of nodes without decreasing the processing time.
Keywords: Wavelet, Images, FFT, Power

Scope of the Article: Image Processing