centralized smart home automation through voice recognition pdf

International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) ISSN: 0976-1353 Volume 13 Issue 1 –MARCH 2015.

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CENTRALIZED SMART HOME AUTOMATION THROUGH VOICE RECOGNITION

G.Nancy Jerfia#1, J.Vaishnavi*2 and P.Karthick*3

#Student, Department of Computer Science, Anand Institute of Higher Technology, Chennai, India *Student, Department of Computer Science, Anand Institute of Higher Technology, Chennai, India

*Assistant Professor, Department of Computer Science, Anand Institute of Higher Technology, Chennai, India

Abstract— The wireless communication has accomplished a meteoric growth period and has become an integral part of the modern community. The availability and flexibility offered by mobile communications have made it one of the fastest growing areas of telecommunication. The implementation of the Smart Home Automation Technology using the Global System for mobile communication (GSM) to control the home appliances such as light, fan and to detect flame via Voice to Text messages is presented in this paper. An Arduino microcontroller is the central microcontroller that communicates with an Android application which is used as a user interface and is focused on the functionality of the GSM protocol. This functionality allows the user to control the target automated system away from the user’s residence. The home owners will be able to receive the feedback status of any home appliances under control whether switched on or off remotely from their mobile phones.

Keywords — Home automation; Global System for Mobile

Communication (GSM); Arduino microcontroller

I. INTRODUCTION

Recently, there has been a growing interest among consumers in the smart home automation. It is the automation of the administration or household activity. The acclaim of home automation has been increasing, greatly in the late years because of much higher affordability and integrity through smart phone and tablet connectivity. The concept of IOT (Internet of Things) has tied in minutely with the prominence of home automation. The electrical gadgets in a house are unified with each other. Gadgets may be connected through a home network in order to control it by a personal computer or by android gadgets, and may allow remote access from the internet through the integration of technologies with the home frolic systems. The appliances can communicate in a unified manner which results in amenity. Smart home contains multiple, connected devices such as home bash consoles, security systems, lighting, access control systems surveillance etc., Home automation system represents and reports the status of the connected devices in an user-friendly interface allowing the user to interact and control various devices through the touch of a few buttons and with the recognition of voice. The major communication technologies used by the today’s home automation system includes ZigBee, Bluetooth, WiMAX and Wireless LAN (Wi-Fi) and Global

System for Mobile Communication (GSM). With the rise in number and the requirement of the GSM subscribers, GSM wireless communication system has gathered more and more attention in the field of mobile communication. However, a few limitations for the system include not being able to control multiple appliances simultaneously and the home automation system could not verify the status of all the appliances. Arduino microcontroller is a tool which is used to develop interactive objects, taking inputs from a variety of switches or sensors, and controlling variety of lights, motors and other physical outputs. It is a stand- alone process or it can communicate with the software running on your computer. The microcontroller acts as the bridge between the GSM network and sensors of the home automation system. Another, advantage of using the GSM network in home automation is its high security configuration, which provides maximum reliability whereby other people cannot have the information sent or received. Hence, this work implements voice to text android application based on control for home appliances using the GSM architecture using static IP address.

II. SYSTEM REALIZATION

The design of our proposed smart GSM-based home automation system is given in Fig. a. The architecture consists

Of mobile phone, Arduino microcontroller and GSM board. In the proposed system design, the user gives a voice message where this message is converted to text. The text is now sent as a default GSM module to the arduino web server. The Arduino UNO board has 14 digital I/O pins, 6 of which can produce pulse-width modulated signals, and 6 analog inputs, which can also be used as 6 digital I/O pins where the input and output operates at 0 to +5V. Required actions like light/fan/any device on/off will be done along with the detection of flame. Thus the presence of any smoke/fire will be detected by the camera, sends an alert message to the server and this server immediately sends the alert/notification to the user’s mobile phone. Outgoing message from the system containing the home appliances status is delivered to the mobile phone through GSM modem.


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The digitized audio sample is acquired from a microphone and the filtered raw audio is sent to the Automatic Speech Recognition (ASR) where the raw audio is filtered from noise and automatic speech recognition is done. The Automatic Speech Recognition (ASR) module performs speech to text conversion. It takes as input the utterance with the user’s speech that come from the Voice Activity Detector and sends the resultant text to the Server. The Automatic Speech Recognition is based on the Pocket Sphinx speech recognition library.

Fig a: SYSTEM ARCHITECHURE III. IMPLEMENTATION A.Voice activity detector The Voice Activity Detector’s (VAD) role is to discriminate

the user’s voice frames from those containing noise. This module reads the digitized audio samples acquired from a microphone and sends the filtered raw audio to the Automatic Speech Recognition. The actual implementation of the VAD module is based on the Sphinx Base library, which was modified so it can work with the Open SL ES native audio libraries present on Android.

Fig b: VOICE ACTIVITY DETECTOR B. Automatic speech recognition The signal to the Android application is given. The

Automatic Speech Recognition (ASR) module performs speech to text conversion. ASR perform speech to text conversion process. It takes as input the utterance with the user’s speech that come from the Voice Activity Detector and sends the resultant text to the Server. The ASR module is based on the Pocket Sphinx speech recognition library.

Fig c: AUTOMATIC SPEECH RECOGNITION

C. Server communication

The raw audio is filtered and finds the match with audio base library. The Fig. d given below is the implementation of the android voice to text conversion which is connected to the server by entering the IP address.


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Fig d: ACQUIRING STATIC IP ADDRESS

The Server Engine extracts the meaning of the utterance, manages the dialog flow and produces the actions appropriate for the target domain. It generates a response based on the input, the current state of the conversation and the dialog history. Server communication done by using web services based SOAP protocol. Micro Web-server Arduino Device GET. D. Home gateway application framework

The access to Web services has to be easy, direct, open and

interoperable where the provided communication means and the programming interfaces (APIs) shall be easy to implement on every platform and developing environment. The most open and interoperable way to provide access to remote services or to enable applications to communicate with each other is to utilize the Web services. There are two classes of Web services: Simple Object Access Protocol (SOAP) and Representational State Transfer (REST).

In this approach we have used the SOAP based Web service utilizing standard operation such as GET and POST requests that return JavaScript Object Notation (JSON) responses to communicate between the remote user and the micro Web server. JSON is a lightweight data-interchange format. It is easy for human beings to read and write. It is also simpler for machines to parse and generate messages than using XML. For example, to turn ON the light, an HTTP POST request is sent to the resource of the server as illustrated in Fig e.

Fig e: WORKING OF SOAP PROTOCOL

Fig f: ONE WAY COMMUNICATION FROM AUTOMATIC SPEECH RECOGNITION TO THE CONTROL HARDWARE

E. Control interface

The Control Interface translates the commands said by then user to a format that can be understood by the target applications (home appliances) or services running on the same device or accessible remotely.This module is domain-specific and has to be re implemented or adapted for every new target application.

F. Fire detection The image based flame monitoring for fire detection, fire

evaluation, determination of flame and fire parameters is being implemented. In this method we use vision based flame detection with video camera surveillance system. The key idea consists of exploiting the difference between the fast, fire motion, and the structured, rigid motion of other objects. In the proposed method, fire detectors are introduced by using synthetic fire simulations and they allow for a quantitative investigation into how flame saturation, spatial resolution, frame rate and noise influence detection. It includes the development of optical flow estimators with improved robustness to noise that take into account more than two frames at a time. The edge-detection methods that have been published may be grouped into two categories according to the computation of image gradients, i.e., the first-order or second-order derivatives. The Canny edge-detection algorithm, an improved method using the Sobel operator, is known to be a powerful edge-detection method.


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Fig g: PROCEDURE FOR FIRE DETECTION

IV. CONCLUSION

The project which is presented is about voice to text recognition using the android application and with the help of an arduino microcontroller which holds all the gadgets integrated. In order to improve the system performance, we are using GSM protocol along with static IP address instead of using SIM card. The detection of flame is also being sensed concurrently and the GSM thus makes the notification alert to the user involved. V. FUTURE WORK

In this paper, we have presented a separate webcam for detecting the flame and to send the notification alert to the user’s mobile phone. Further it can be enhanced by integrating the flame detection sensors with the arduino micro controller.

VI. ACKNOWLEDGEMENT This proposed work is done by Nancy Jerfia .G and

Vaishnavi .J under the guidance of Mr.P.Karthick where the necessary facilities were provided by our college Anand Institute Of Higher Technology.

REFERENCES

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[2] Tahmina Begum, Shazzat Hossain, Bashir Uddin and Shaheen Hasan Chowdhury on Design and Development of Activation and Monitoring of Home Automation System via SMS through Microcontroller International Conference on Computers and Devices for Communication(2009).

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[8] C. K. Das, M. Sanaullah, H. M. G. Sarower, and M. M. Hassan, (2009). Development of a Cell Phone based Remote Control System: an Effective Switching System for Controlling Home and Office Appliances. International Journal of Electrical & Computer Sciences, 9(10), pp.23-29.

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centralized smart home automation through voice recognition pdf

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