The Rising Trend of Smart Homes and User Behaviour Analysis

  • Authors

    • Dr. Venkatesh Iyer Professor, SRM Institute of Science and Technology, India. Author

    DOI:

    https://doi.org/10.67228/30715636/IJETMR-2023PI6Y4A

    Published 06-05-2023

  • Smart Homes, Internet of Things (IoT), User Behaviour Analysis, Machine Learning, Behavioral Analytics, Home Automation, Predictive Modeling, Energy Optimization, Context-Aware Computing, Artificial Intelligence

    Issue

    Vol. 6 No. 1 (2023)

    Section

    Articles

    How to Cite

    [1]
    V. Iyer, “The Rising Trend of Smart Homes and User Behaviour Analysis”, IJETMR, vol. 6, no. 1, pp. 01–20, Jun. 2023, doi: 10.67228/30715636/IJETMR-2023PI6Y4A.

  • Abstract

    Smart homes use interconnected IoT devices, sensors, AI, and cloud computing to improve comfort, energy efficiency, security, and convenience. Beyond technology, they represent a behavioral shift, as user habits and preferences are increasingly shaped by automated systems. This study analyzes smart home adoption and user behavior patterns using real-time data such as occupancy, energy use, and appliance activity. It applies machine learning techniques—including clustering, supervised and reinforcement learning—to predict behavior, automate services, and detect anomalies. Results show strong performance, with over 85% accuracy in occupancy prediction and 78% efficiency in appliance scheduling, leading to reduced energy consumption. The paper also highlights key adoption factors like usefulness, trust, privacy concerns, cost, and digital literacy. It proposes a framework involving data collection, preprocessing, modeling, and evaluation using metrics like accuracy and F1-score. Overall, the study emphasizes the future of smart homes as adaptive, behavior-aware systems while stressing the importance of ethical and privacy considerations.

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