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A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation.

Andrea Monteriù1, Mario Rosario Prist2, Emanuele Frontoni3

  • 1Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, Italy. a.monteriu@univpm.it.

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This study developed a smart home sensing system using integrated sensors to monitor elderly users and their environment. Machine learning analyzes data for health and behavior insights, enhancing quality of life and safety at home.

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Area of Science:

  • * Smart Home Technology
  • * Biomedical Engineering
  • * Artificial Intelligence in Healthcare

Background:

  • * Smart homes offer strategic advantages for improving quality of life through intelligent device integration.
  • * Continuous monitoring via sensors enhances resident comfort, well-being, and safety without disrupting daily routines.
  • * Domestic technological solutions are crucial for user and environmental monitoring.

Purpose of the Study:

  • * To develop domestic technological solutions for enhancing citizen quality of life.
  • * To create a smart sensing architecture for monitoring users and their domestic environments.
  • * To derive user behavior and health status information from collected sensor data.

Main Methods:

  • * An integrated sensor network comprising biomedical, wearable, and unobtrusive sensors was deployed.
  • * Home automation sensors collected environmental data, complementing physiological parameter monitoring.
  • * Heterogeneous data was stored locally and in the Cloud for machine learning and data mining analysis.

Main Results:

  • * Machine learning algorithms facilitated user behavior identification and health condition classification.
  • * The system enabled classification of smart home profiles and provided data analytics for community services.
  • * A pilot study successfully tested the developed sensors and services for elderly users.

Conclusions:

  • * The proposed smart sensing architecture effectively monitors users and their environment for improved health and behavior insights.
  • * Integrated sensor networks and data analytics in smart homes can significantly enhance the quality of life for residents, particularly the elderly.
  • * The developed platform demonstrates the potential for implementing advanced services for community well-being.