AI-IoT Solutions for Smart Home Automation

Authors

  • Rishu Raj* * School of Computer Science Engineering, KIIT University, Bhubneshwar, India.

https://doi.org/10.48314/ceti.v1i1.24

Abstract

As smart devices increasingly populate our living spaces, the possibilities for interconnected homes expand. However, conventional Internet of Things (IoT) solutions frequently lack the flexibility and intelligence desired by today’s homeowners. This document presents a novel AI-powered IoT framework aimed at enhancing home automation. Our framework promotes better personalization, efficiency, and security by utilizing machine learning and sophisticated data analytics. Central to the system is predictive maintenance, which examines historical data to foresee appliance failures, thereby minimizing unexpected breakdowns and prolonging device longevity. Furthermore, it personalizes comfort levels by understanding user preferences and adjusting temperature, lighting, and audio to create an ideal living environment that improves well-being. Energy efficiency is emphasized through real-time data analysis that detects usage patterns and recommends energy-saving strategies. This assists homeowners in reducing their ecological footprint and lowering utility bills. Security is another primary concern, with AI-driven anomaly detection that oversees network traffic to protect sensitive data and prevent unauthorized entry. Our AI-powered IoT framework signifies a major progress in smart home automation, providing predictive maintenance, tailored comfort, energy optimization, and strong security for a more intelligent, sustainable, and secure living environment.

Keywords:

AI, IoT, Smart home, Automation, Machine learning, Predictive maintenance, Energy efficiency, Personalized comfort

References

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Published

2024-03-03

Issue

Vol. 1 No. 1 (2024): Computational Engineering and Technology Innovations

Section

Articles

How to Cite

Raj*, R. (2024). AI-IoT Solutions for Smart Home Automation. Computational Engineering and Technology Innovations, 1(1), 37–43. https://doi.org/10.48314/ceti.v1i1.24

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