Voice Command Based Home Automation using IOT

Azmeera Sravan; K Pullareddy; Kambde Pragnya; Maggija Mallikarjuna

Voice Command Based Home Automation using IOT

Author(s)	Mr. Azmeera Sravan, Mr. K Pullareddy, Ms. Kambde Pragnya, Mr. Maggija Mallikarjuna
Country	India
Abstract	The primary objective of this project is to design and implement an energy-efficient, reliable, and highly accessible Internet of Things (IoT) based home automation system controlled via real-time voice commands. Traditional smart home architectures often suffer from steep installation costs, high latency, and severe vulnerabilities regarding unauthorized physical or remote device tempering. To address these critical limitations, this system introduces distinct novelty by integrating localized edge-computing preprocessing with multi-language capability and an advanced biometrics-driven speaker verification layer, ensuring that only authorized users can toggle appliances. The methodology involves utilizing a low-power ESP32 microcontroller with an integrated Wi-Fi module as the primary hardware hub, interfaced with a multi-channel relay module to regulate household fixtures like lights, fans, and security locks. Audio input is captured via a localized micro-electro-mechanical system (MEMS) microphone or remotely through an Android smartphone application synchronized with Google Assistant and the Blynk cloud platform. Natural language processing (NLP) pipelines, mapping technologies, and lightweight feature extraction protocols such as Zero-Crossing Rate (ZCR) and Short-Time Energy (STE) are deployed locally on the microcontroller to decipher verbal instructions into serial data instructions with minimal computing resources. Findings from real-world validation testing demonstrate that the prototype operates seamlessly across a wide network range with a minimal command processing latency of less than 50 milliseconds. Furthermore, the localized authentication layer efficiently blocks unauthorized access attempts while maintaining a high voice recognition accuracy of 95.4% across diverse languages. Ultimately, this research presents an affordable, robust, and hands-free smart home framework that significantly optimizes residential electricity consumption while serving as a crucial assistive technology for the elderly and physically disabled.
Keywords	Internet of Things, Natural language processing, Short-Time Energy, Electrical Engineering
Field	Engineering
Published In	Volume 7, Issue 7, July 2026
Published On	2026-07-07

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Voice Command Based Home Automation using IOT

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