AI-INTEGRATED IOT FRAMEWORK FOR INTELLIGENT SMART HOME AUTOMATION, SECURITY, AND ENERGY MANAGEMENT
AUTHORS:
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P Kalpana Reddy
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Department Of ECE, SVS Group of Institutions, Hanmakonda, Telangana
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Abstract
The rapid advancement of Artificial Intelligence (AI) and the Internet of Things (IoT) has revolutionized the concept of smart homes by enabling intelligent automation, enhanced security, and efficient energy management. Traditional home automation systems primarily focus on remote control functionalities and lack adaptive decision-making capabilities. This paper proposes an AI-Integrated IoT Smart Home Framework that combines intelligent sensors, edge computing, cloud analytics, and machine learning algorithms to create a self-learning residential environment. The proposed system continuously monitors environmental conditions, occupant behavior, energy consumption patterns, and security parameters through interconnected smart devices. Artificial intelligence techniques analyze real-time and historical data to predict user preferences, optimize appliance operations, detect anomalies, and improve resource utilization. The framework incorporates voice-controlled virtual assistants, facial recognition-based access control, and predictive energy management mechanisms. Experimental analysis demonstrates significant improvements in energy efficiency, user comfort, security monitoring, and operational intelligence compared to conventional home automation systems. The proposed architecture contributes toward the realization of sustainable, secure, and intelligent smart living environments.
Keywords
Artificial Intelligence Internet of Things Smart Home Home Automation Edge Computing Machine Learning Smart Security Energy Management Industry 5.0.
Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 7
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Jul 14 2026
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Sandhya, G. & Radhika, A. (2026). AI-Integrated IOT Framework for Intelligent Smart Home Automation, Security, and Energy Management. International Journal of Science, Strategic Management and Technology, 02(7), 1-9. https://doi.org/10.55041/ijsmt.v2i7.065
Sandhya, Gulla, and Abbidi Radhika. "AI-Integrated IOT Framework for Intelligent Smart Home Automation, Security, and Energy Management." International Journal of Science, Strategic Management and Technology, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i7.065.
Sandhya, Gulla, and Abbidi Radhika. "AI-Integrated IOT Framework for Intelligent Smart Home Automation, Security, and Energy Management." International Journal of Science, Strategic Management and Technology 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i7.065.
References
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[3] S. Madakam, R. Ramaswamy, and S. Tripathi, “Internet of Things (IoT): A Literature Review,” Journal of Computer and Communications, vol. 3, no. 5, pp. 164–173, 2015.
[4] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things: A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013.
[5] A. Alamri et al., “A Survey on Sensor-Cloud: Architecture, Applications and Approaches,” International Journal of Distributed Sensor Networks, vol. 9, no. 2, pp. 1–18, 2013.
[6] M. H. Rehmani, A. Davy, B. Jennings, and C. Assi, “Software Defined Networks Based Smart Homes and Smart Cities,” Sustainable Cities and Society, vol. 19, pp. 310–316, 2015.
[7] F. Xia, L. Yang, L. Wang, and A. Vinel, “Internet of Things: A Survey on Technologies, Applications and Future Trends,” International Journal of Communication Systems, vol. 25, no. 9, pp. 1101–1121, 2012.
[8] H. Kim, J. Lee, and K. Lee, “Artificial Intelligence-Based Smart Home Automation Using Deep Learning,” IEEE Access, vol. 9, pp. 84312–84325, 2021.
[9] S. Sharma and V. Kumar, “Machine Learning Approaches for Smart Home Energy Management,” Sensors, vol. 22, no. 4, pp. 1645–1663, 2022.
[10] Y. Zhang, X. Wang, and Z. Chen, “AI-Powered Smart Homes: Recent Advances and Future Opportunities,” IEEE Internet of Things Journal, vol. 10, no. 8, pp. 6721–6739, 2023.
[2] D. Bandyopadhyay and J. Sen, “Internet of Things: Applications and Challenges in Technology and Standardization,” Wireless Personal Communications, vol. 58, no. 1, pp. 49–69, 2011.
[3] S. Madakam, R. Ramaswamy, and S. Tripathi, “Internet of Things (IoT): A Literature Review,” Journal of Computer and Communications, vol. 3, no. 5, pp. 164–173, 2015.
[4] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things: A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013.
[5] A. Alamri et al., “A Survey on Sensor-Cloud: Architecture, Applications and Approaches,” International Journal of Distributed Sensor Networks, vol. 9, no. 2, pp. 1–18, 2013.
[6] M. H. Rehmani, A. Davy, B. Jennings, and C. Assi, “Software Defined Networks Based Smart Homes and Smart Cities,” Sustainable Cities and Society, vol. 19, pp. 310–316, 2015.
[7] F. Xia, L. Yang, L. Wang, and A. Vinel, “Internet of Things: A Survey on Technologies, Applications and Future Trends,” International Journal of Communication Systems, vol. 25, no. 9, pp. 1101–1121, 2012.
[8] H. Kim, J. Lee, and K. Lee, “Artificial Intelligence-Based Smart Home Automation Using Deep Learning,” IEEE Access, vol. 9, pp. 84312–84325, 2021.
[9] S. Sharma and V. Kumar, “Machine Learning Approaches for Smart Home Energy Management,” Sensors, vol. 22, no. 4, pp. 1645–1663, 2022.
[10] Y. Zhang, X. Wang, and Z. Chen, “AI-Powered Smart Homes: Recent Advances and Future Opportunities,” IEEE Internet of Things Journal, vol. 10, no. 8, pp. 6721–6739, 2023.
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