SMART REGULATOR AUTOMATIC ROOM TEMPERATURE MONITORING AND CONTROLLING WITH POWER SAVING APPROACH
Published In: SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRONICS, ELECTRICAL AND COMPUTER ENGINEERING
Author(s): SOUMYA ROY
Abstract: Our main goal is to design a “SMART REGULATOR” which reduces the human effort. This instrument regulates the speed of the fan automatically according to the room temperature and the user defined set point temperature. It will also display the room temperature. If the temperature is less than the set point temperature or exactly equal to the set point temperature then the fan is in off state and when the temperature of the room is greater than the set point temperature then the fan is in on state and the speed of the fan will vary proportionally according to the logic written in the program which depends on the difference between the present room temperature and the set point temperature. This regulator also counts the number of person entering in the room and also leaves from the bidirectional single door room. It will also display that number. If the number is zero that means no person present in that room or the room is empty, then it will disconnect the power supply of the room auto
- Publication Date: 13-Jun-2013
- DOI: 10.15224/978-981-07-6935-2-59
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TEXT INDEPENDENT SPEAKER IDENTIFICATION USING SOFT-COMPUTING TECHNIQUES
Published In: SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRONICS, ELECTRICAL AND COMPUTER ENGINEERING
Author(s): DINESH SHEORAN , PARDEEP SANGWAN
Abstract: Speaker recognition is an emerging and very important technique in this new era of human-machine interaction. It has two main tasks: speaker identification and speaker verification. In the past various models have been proposed for the identification of speakers with the help of statistical techniques like Hidden Markov Model, Gaussian Mixture Model. As the Artificial Neural Networks (ANNs) are the universal classifiers. The present research proposes a novel paradigm which utilizes the strong pattern matching capability of ANNs for identification of speakers. Here ten speech samples are collected from 40 different Mel Frequency Cepstral Coefficients (MFCC) are extracted for all the speakers and these coefficients are used to train ANN and then test signals are validated and verified for ANN as well as for Fuzzy Logic. The results of identification are very encouraging.
- Publication Date: 13-Jun-2013
- DOI: 10.15224/978-981-07-6935-2-60
- Views: 0
- Downloads: 0