Non-conventional Energy Source-Based Home Automation System

2020 ◽  
pp. 419-427
Author(s):  
Rashmi Vashisth ◽  
Rahul Verma ◽  
Lakshay Gupta ◽  
Harsh Bansal ◽  
Vishal Kharbanda
Keyword(s):  
Energy Source ◽  
Automation System ◽  
Home Automation ◽  
Home Automation System

Home Automation Using Bluetooth

2020 ◽  
pp. 675-678
Author(s):  
Mukesh Mahajan ◽  
Astha Dubey ◽  
Samruddhi Desai ◽  
Kaveri Netawate
Keyword(s):  
Temperature Sensor ◽  
Humidity Sensor ◽  
The Other ◽  
Automation System ◽  
Home Automation ◽  
Wireless Devices ◽  
Home Appliances ◽  
Home Automation System ◽  
Condition Systems

This paper reviews basically about Bluetooth based home automation system. It is controlled by PIC microcontroller. Home automation can be defined as the ability to perform tasks automatically and monitor or change status remotely. These include tasks such as turning off lights in the room, locking doors via smartphone, automate air condition systems and appliances which help in the kitchen. Now a days several wireless devices are available such as Bluetooth, Zigbee and GSM. Since Bluetooth is low in cost than the other two and hence is used more. In this paper we have described the methods of automating different home appliances using Bluetooth and pic microcontroller. Different sensors are involved in this system to advance and make it smarter. Sensors such as temperature sensor, liquid sensors, humidity sensor etc. can be used.

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 An IoT-Based Smart Home Automation System

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3784
Author(s):  
Cristina Stolojescu-Crisan ◽  
Calin Crisan ◽  
Bogdan-Petru Butunoi
Keyword(s):  
Application Programming Interface ◽  
Smartphone Application ◽  
Raspberry Pi ◽  
Automation System ◽  
Home Automation ◽  
Network Connection ◽  
Communication Scheme ◽  
Application Programming ◽  
Home Automation System ◽  
User Friendly

Home automation has achieved a lot of popularity in recent years, as day-to-day life is getting simpler due to the rapid growth of technology. Almost everything has become digitalized and automatic. In this paper, a system for interconnecting sensors, actuators, and other data sources with the purpose of multiple home automations is proposed. The system is called qToggle and works by leveraging the power of a flexible and powerful Application Programming Interface (API), which represents the foundation of a simple and common communication scheme. The devices used by qToggle are usually sensors or actuators with an upstream network connection implementing the qToggle API. Most devices used by qToggle are based on ESP8266/ESP8285 chips and/or on Raspberry Pi boards. A smartphone application has been developed that allows users to control a series of home appliances and sensors. The qToggle system is user friendly, flexible, and can be further developed by using different devices and add-ons.

scholarly journals Internet of Things-Based Intelligent Smart Home Control System

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Olutosin Taiwo ◽  
Absalom E. Ezugwu
Keyword(s):  
Machine Learning ◽  
Mobile Application ◽  
Smart Home ◽  
Human Life ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Automation System ◽  
Home Automation ◽  
Area Of Interest ◽  
Home Automation System

The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.

scholarly journals Home Automation Controlled through Wifi-Module and Blynk App

2021 ◽  
Vol 9 (VI) ◽  
pp. 3374-3383
Author(s):  
M. Niharika
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Real Time ◽  
Cell Phone ◽  
Automation System ◽  
Home Automation ◽  
Home Appliances ◽  
Home Automation System ◽  
Electrical Loads

This Home Automation System is based on the ESP8266 wifi module. With the help of this project the electrical loads can be controlled using your android cell phone. For this project we have to connect ESP8266 Wi-fi module and cell phone with the same WIFI network. This project can be used at homes, offices, colleges, universities, and so on. For the Worldwide control system, we can use the Nodemcu ESP8266 Wifi Module. This system is very convenient and economical to use. Major components used in it are: esp8266 wifi modulerelays. With this internet of things we can control four home appliances from the Blynk app, we can also use manual switches to control the appliances with or without internet and we can also monitor real-time feedback. So this is very useful to make our devices smart .In this project we have used four channel relay. In this project we have controlled AC appliances like Lights etc. In this project we used IFTTT with the help of ifttt we can connect all of our apps and devices.

scholarly journals Home Automation with Intruder Detection and Energy Control

2021 ◽  
Vol 9 (VI) ◽  
pp. 3473-3480
Author(s):  
M. Niharika
Keyword(s):  
Light Intensity ◽  
Smart Home ◽  
Security System ◽  
Automation System ◽  
Home Automation ◽  
Energy Control ◽  
Intruder Detection ◽  
Alert Message ◽  
Home Automation System

In previous project we made a home automation system, where we can control our appliances through Blynk app and Google assistant with the help of IFTTT. As an extension we will provide feedback to user whether the appliance is on or off. We will also use sensors like LDR for measuring light intensity in this project to make it smart. We will also include security system where in we have sensors to doors and windows and give buzzer along with an alert message to the user. On a whole we will provide a smart home automation system.

scholarly journals Wireless Home Automation System

IJIREEICE ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 103-104
Author(s):  
Haris Jamal ◽  
Indrasish Banerjee ◽  
Subhankar Bhattacharjee
Keyword(s):  
Automation System ◽  
Home Automation ◽  
Home Automation System
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