ILeHCSA: an internet of things enabled smart home automation scheme with speech enabled controlling options using machine learning strategy

Abstract

Nowadays, communication schemes and the related automation logics have improved drastically, and people are moving from classical to intelligent applications. This naturally raises the growth ratio of the automation industry and enables researchers to work accordingly. The field of automation is essential in specific unavoidable environments such as hospitals, industrial units, individual residences, disaster areas, etc. In this paper, a novel machine-learning enabled speech-based home automation system is designed, called Intelligent Learning-enabled Home Controlling with Speech Assistance (ILeHCSA). This scheme integrates several latest technologies to control the home intelligently, including machine learning, speech assistance technology, and Internet of Things (IoT) support. Based on these advanced technologies, the logic of smart home automation systems has been designed in this approach, and it provides intellectual home controlling options to people. The following are the devices and sensors which are essential to control the electronic devices embedded into the home environment: Node Microcontroller Unit (MCU) Wi-Fi enabled Microcontroller, Relay Unit, Voice Capture Module with Mic, Speech-to-Text (STT) Converter Module, and Global Positioning System (GPS) to identify the location of the device. The machine-learning logic is utilized to provide a statistical analysis of device usage and to provide a clear summary and traces to maintain the device accordingly. These smart technologies can innovatively change the living atmosphere with sufficient support and comfort. The main intention of this paper is to provide a robust home automation system to support people efficiently, especially the people who are physically suffering from illness and the aged ones. The proposed work provides a 96.5% accuracy ratio when compared with other methods.