Design Of A Voice Controlled Home Automation System Using Deep Learning Convolutional Neural Network (DL-CNN)

2020 ◽  
Vol 8 (1) ◽  
pp. 57-73
Author(s):  
Lery Sakti Ramba
Keyword(s):  
Deep Learning ◽  
Speech Recognition ◽  
Background Noise ◽  
Electronic Devices ◽  
Recognition System ◽  
Background Intensity ◽  
Automation System ◽  
Home Automation ◽  
Speech Recognition System ◽  
Home Automation System

The purpose of this research is to design home automation system that can be controlled using voice commands. This research was conducted by studying other research related to the topics in this research, discussing with competent parties, designing systems, testing systems, and conducting analyzes based on tests that have been done. In this research voice recognition system was designed using Deep Learning Convolutional Neural Networks (DL-CNN). The CNN model that has been designed will then be trained to recognize several kinds of voice commands. The result of this research is a speech recognition system that can be used to control several electronic devices connected to the system. The speech recognition system in this research has a 100% success rate in room conditions with background intensity of 24dB (silent), 67.67% in room conditions with 42dB background noise intensity, and only 51.67% in room conditions with background intensity noise 52dB (noisy). The percentage of the success of the speech recognition system in this research is strongly influenced by the intensity of background noise in a room. Therefore, to obtain optimal results, the speech recognition system in this research is more suitable for use in rooms with low intensity background noise.

scholarly journals Enhanced Intelligent Smart Home Control and Security System Based on Deep Learning Model

2022 ◽  
Vol 2022 ◽  
pp. 1-22
Author(s):  
Olutosin Taiwo ◽  
Absalom E. Ezugwu ◽  
Olaide N. Oyelade ◽  
Mubarak S. Almutairi
Keyword(s):  
Deep Learning ◽  
Smart Home ◽  
Learning Model ◽  
The Internet ◽  
Automation System ◽  
Home Automation ◽  
Home Security ◽  
Automation Systems ◽  
Home Automation System ◽  
Deep Learning Model

Security of lives and properties is highly important for enhanced quality living. Smart home automation and its application have received much progress towards convenience, comfort, safety, and home security. With the advances in technology and the Internet of Things (IoT), the home environment has witnessed an improved remote control of appliances, monitoring, and home security over the internet. Several home automation systems have been developed to monitor movements in the home and report to the user. Existing home automation systems detect motion and have surveillance for home security. However, the logical aspect of averting unnecessary or fake notifications is still a major area of challenge. Intelligent response and monitoring make smart home automation efficient. This work presents an intelligent home automation system for controlling home appliances, monitoring environmental factors, and detecting movement in the home and its surroundings. A deep learning model is proposed for motion recognition and classification based on the detected movement patterns. Using a deep learning model, an algorithm is developed to enhance the smart home automation system for intruder detection and forestall the occurrence of false alarms. A human detected by the surveillance camera is classified as an intruder or home occupant based on his walking pattern. The proposed method’s prototype was implemented using an ESP32 camera for surveillance, a PIR motion sensor, an ESP8266 development board, a 5 V four-channel relay module, and a DHT11 temperature and humidity sensor. The environmental conditions measured were evaluated using a mathematical model for the response time to effectively show the accuracy of the DHT sensor for weather monitoring and future prediction. An experimental analysis of human motion patterns was performed using the CNN model to evaluate the classification for the detection of humans. The CNN classification model gave an accuracy of 99.8%.

scholarly journals Keyword Recognition Device Cloud Based

2021 ◽  
Vol 9 (VIII) ◽  
pp. 87-89
Author(s):  
Apurv Singh Yadav
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Speech Recognition ◽  
Internet Of Things ◽  
Recognition System ◽  
The Internet ◽  
Speech Recognition System ◽  
The Past ◽  
Use Of The Internet ◽  
The Internet Of Things

Over the past few decades speech recognition has been researched and developed tremendously. However in the past few years use of the Internet of things has been significantly increased and with it the essence of efficient speech recognition is beneficial more than ever. With the significant improvement in Machine Learning and Deep learning, speech recognition has become more efficient and applicable. This paper focuses on developing an efficient Speech recognition system using Deep Learning.

Voice Recognition Home Automation System (VRHAS)s

2012 ◽  
Author(s):  
Fauzan Khairi Che Harun ◽  
Choy Meng Onn ◽  
Nor Mohd Ariffanan Mohd Basri
Keyword(s):  
Voice Recognition ◽  
Recognition System ◽  
Physical Contact ◽  
Small Scale ◽  
Automation System ◽  
Home Automation ◽  
Centralized Control ◽  
Switching System ◽  
Home Automation System ◽  
Scale Design

Automasi rumah adalah satu cabang teknologi yang sedang giat diperkembangkan disebabkan kemudahan yang diberikan. Alasan untuk memilih suara adalah kerana ia mudah dihasilkan oleh manusia. Selain itu, penggunaan suara memberikan sistem kawalan yang berkesan dan selesa untuk digunakan. Penerapan sistem ini melibatkan pengubahsuaian sistem suis dari cara tradisional yang merupakan sentuhan fizikal dengan beralih ke cara yang lebih selamat di mana penggunaan suara untuk menggantikan semua sentuhan fizikal. Projek ini melibatkan sistem suis mudah yang menggunakan transistor bersama–sama dengan geganti untuk kesemua sambungan kuasa ke peranti, sistem pengecaman suara yang terdiri daripada cip pengecaman suara HM2007, dan mikro pengawal PIC18F8722 untuk membina sistem. HM2007 berfungsi telinga yang akan mendengar dan mentafsir arahan masukan yang diberikan sementara PIC18F8722 berfungsi sebagai otak dari sistem yang akan menyelaraskan keluaran yang betul dengan arahan masukan yang diberikan. Projek ini boleh mengecam arahan yang dilatih oleh pengguna dan berjaya untuk melaksanakan keluaran yang betul. Projek ini merupakan reka tiga bentuk berskala kecil yang terdiri daripada 8 arahan yang digunakan untuk mengendalikan suis yang berbeza. Arahan ini boleh secara individu untuk menghidupkan dan mematikan suis. Selain itu, arahan juga mampu menghidupkan dan mematikan semua suis pada masa yang sama. Kata kunci: Pengecaman suara; sistem rumah automatik Home automation is currently getting widespread recognition due to the convenience it provides. Home automation may include centralized control of lighting, HVAC (heating, ventilation and air conditioning), appliances, and other systems, to provide improved convenience, comfort, energy efficiency and security. This research is focus on creating a voice recognition system as an aid to home automation. Reason for choosing voice is because it is easily being reproduced by human. Besides that, usage of voice gives a control system that can be effective and convenient to be used. The application of this system involve modifying the switching system from the traditional way which is physical contact with a switch to a safer way where the usage of voice to replace all the physical contact. This project involve a simple switching system that used the transistor along with relay to power the devices, a voice recognition system that consists of voice recognition chip HM2007 and the PIC18F8722 microcontroller. The HM2007 serves as the recognition chip that listens and interpret the command by the given input while the PIC18F8722 serve as the brain of the system that will coordinate the correct output with the input command given. This project able to recognize the command trained by the user and successfully to execute the correct output. This project is a small scale design which consists of 8 commands that used to control three different switches. The command is able to individually switch on and switch off each of the switch. Besides that, the command also able to switch on and off all the switch at the same time. Key words: Voice recognition; home automation system

scholarly journals Internet of Things: Design and Manufacture of Home Automation System with Web Server Based Arduino and Android

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2590-2592
Keyword(s):  
Electronic Devices ◽  
Automated System ◽  
The Internet ◽  
Automation System ◽  
Home Automation ◽  
Android Application ◽  
Ethernet Network ◽  
Arduino Microcontroller ◽  
Home Automation System ◽  
Design And Manufacture

Home automation is an automated system created specifically to facilitate the work of humans, especially at home. Home Automation connects electronic devices to each other in a home that is integrated using the internet network and allows it to be controlled via android smartphone and web client (server). On android smartphone installed applications that have been connected with Arduino microcontroller and Ethernet shield. In this research for controlling or retrieving data via Ethernet network the easiest is Arduino serve as server and we can request and arrange data through web client or android application then data will be sent using protocol User Datagram Protocol (UDP). So to control the electronic devices can be done from a considerable distance as long as connected to the internet.

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