AI-final publication paper.docx

<b>Purpose – </b>This paper aims to explore the transformational potential of Sustainable Artificial Intelligence (SAI) in reimagining modern home automation environments. The study focuses on demonstrating that an IoT-assisted, AI-controlled, renewable energy-based smart living space can be developed where energy is utilized efficiently while maintaining user convenience and comfort.<b>Design/methodology/approach – </b>The study is based on an interdisciplinary methodology using Machine Learning algorithms, IoT sensor networks and renewable green energy system (in this case solar energy). The proposed SAI system adaptively controls in-home functionalities such as the heating, appliance and cleaning scheduling using a monitoring system relying on analyzing real-time and historical user data at the household.<b>Findings</b> – SAI enhances energy efficiency by prioritizing renewable sources, cutting electricity costs, and feeding excess power back to the grid. Adaptive learning ensures optimal task scheduling, improving convenience and sustainability.<b>Research limitations/implications</b> – While theoretically promising, real-world deployment requires further testing across varied housing types, climates, and energy infrastructures.<b>Practical implications</b> – SAI provides homeowners an automated, cost-effective solution to reduce fossil fuel dependence, lower carbon footprints, and simplify daily routines.<b>Social implications</b> – By promoting energy-conscious living, SAI supports global sustainability efforts, encouraging eco-friendly habits and reducing household energy waste.<b>Originality/value</b> – This study uniquely merges AI-driven automation with renewable energy management, offering a novel framework for sustainable smart homes that balances efficiency, comfort, and environmental responsibility.