Making of household electronic equipment control using voice recognition sensor based on atmega 328p microcontroller

Yulianto, Dwi (2017) Making of household electronic equipment control using voice recognition sensor based on atmega 328p microcontroller. Diploma thesis, Universitas Al Azhar Indonesia.

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Abstract

Voice recognition at this time its application has not been utilized especially for the physical disabled and the blind. The prototype of electronic equipment controller using the EasyVR2.0 speech recognition sensor based on ATMega328p microcontroller will help ease the operation of electronic equipments for the physical disabled and the blind. ATMega328p microcontroller that can be integrated with speech recognition sensor EasyVR2.0 as it can interact with serial communication and have input output interface. Development is also supported by the library of Arduino is easy to use and supported TFT LCD SPFD5408A. Control of electronic equipment generally use AC voltage so in this research used optocoupler as isolator and voltage conversion and TRIAC as AC power controller supported by zero crossing detector circuit which controlled by ATTiny45 microcontroller and for electronic appliances using infrared remote used infrared transmitter as its control. Performance testing prototype of electronic equipment controller using sensors speech recognition EasyVR2.0 based microcontroller ATMega328p which controlled among others temperature of air conditioner using infrared remote transmitter, rotation speed of fan motor and lamp. The experimental results show that this research prototype can be used to control the fan motor power control circuit with a resistance in 240 Ohm. The 0.6p of ignition angle is 24.96 Watt for the speed of the slow fan motor and the ignition angle value of 0.1p is 96.26 Watt for the speed fast motor fan electronic equipment. The result of experiment that male user as voice command recorder can be detected with high success equal to 96,29%, while for male user success rate equal to 53,7% and for female user success rate equal to 24,07%. So it can be concluded that the prototype of this research can be implemented.

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