Home Automation Utilizing Artificial Intelligence & Internet of Things

Abstract

This paper examines the most recent apps of Web of Things (IoT) innovation in residential settings, aiming to make homes more intelligent, automated, and digitally connected. The literature showcases a wide variety of systems, approaches, and practical implementations that demonstrate the effective use of IoT, artificial intelligence (AI), and geographic information systems (GIS) in domestic environments. With rapid technological progress and rising interest in smart homes and energy management, there is a clear need to identify existing gaps, understand the relationships between current methods, and establish a comprehensive framework for smart home design. This study presents a systematic review of journal articles published between 2010 and 2021, drawn primarily from the Scopus database. The selected papers were analyzed from both bibliographic and content perspectives to highlight key systems, best practices, and major contributors. Through systematic selection, coding, and critical evaluation, this review focuses on the smart home systems developed and the core technologies employed. The central question addressed is: What key lessons have we learned from a decade of advancements in smart home systems across various domains? The findings reveal significant gaps, particularly with in the integration of AI and IoT, as well as the constrained utilize of geospatial Informational data in smart home domestic advancement. There is together with a notable shortage of fully integrated solutions for energy efficiency and aged-care applications. This article aims to give scholars and experts a clear understanding of these shortcomings and practical guidance for addressing them. Ultimately, it supports the design of smart homes that enhance occupant achieving thermal comfort while minimizing energy consumption and lowering greenhouse gas emissions. Furthermore, the paper raises important new queries about how IoT and current systems can be further enhanced and integrated.

Introduction

AI-powered home automation integrates Artificial Intelligence and Internet of Things (IoT) technologies to create smart living environments where household devices operate automatically and intelligently. These systems use sensors and AI algorithms to learn user behavior, adapt to daily routines, and control appliances such as lights, fans, security cameras, and kitchen devices. As a result, homes can automatically adjust lighting, temperature, and security settings based on occupancy and user preferences, improving comfort and energy efficiency.

The system also enhances security by integrating cameras, door locks, motion sensors, and alert systems. It can detect unusual activity, recognize known and unknown individuals using AI-based facial recognition, and immediately notify homeowners through mobile or cloud platforms. Health-monitoring features further improve safety by alerting caregivers during emergencies.

From a technical perspective, the system is built using IoT-enabled hardware such as Arduino UNO, Raspberry Pi, ESP8266, and various sensors (temperature, flame, PIR, LDR, gas sensors). These components communicate through wireless networks and cloud services. AI-driven decision-making enables automated responses like turning on appliances, sending alerts, or controlling access based on sensor input and learned patterns.

Conclusion

Home automation powered by artificial intelligence Integrating AI technology into home systems and appliances enables smooth communication with platforms like Google Assistant, Amazon Alexa, and Apple Siri. By leveraging AI, homeowners can enjoy a more efficient, convenient, and adaptive living environment. These intelligent systems rely on interconnected devices and sensors to monitor, analyze, and respond to occupants’ behaviors and preferences. This enables the automatic adjustment and optimization of various functions, including lighting, heating and cooling, security systems, appliances, and entertainment setups. A key component of AI-driven automation is data collection and analysis. Sensors placed throughout the home gather information on factors such as temperature, humidity, occupancy, and energy consumption. This data is processed by AI algorithms that detect usage patterns and make informed decisions accordingly. Voice assistants, a common application of AI in smart homes, allow users to interact with their devices using natural language, eliminating the need for manual controls and simplifying operation. Simple voice commands may be used to do things like playing music, changing lights, or setting reminders thanks to integration with Platform services such as Google Assistant, Amazon Alexa, and Apple Siri.

References

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Copyright

Copyright © 2026 Bhabani Sankar Panda, Dr. Bidush Kumar Sahoo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.