Statistical Study of User Perception of Smart Homes during Vital Signal Monitoring with an Energy-Saving Algorithm

Area of Science:

• Computer Science
• Gerontology
• Electrical Engineering

Background:

• Sensor networks offer enhanced home comfort, security, and potential for elderly care.
• Existing systems may lack user-centric optimization and adaptive capabilities.

Purpose of the Study:

• To evaluate a home sensor network with an adaptive energy optimization algorithm for users aged 55-75.
• To analyze the impact of sensor networks on user comfort, security perception, and vital signs.
• To optimize algorithm performance based on user behavior and alert accuracy.

Main Methods:

• Implementation of a home sensor network for users aged 55-75.
• Analysis of vital signs to determine comfort and tranquility thresholds.
• Statistical study of perceived security, differentiating by gender.
• Performance evaluation of an adaptive energy optimization algorithm.

Main Results:

• The proposed adaptive algorithm improved sensor network performance by 15% under similar conditions.
• Quantified the usefulness of accurate sensor alerts and their impact on user perception.
• Established correlations between vital signs, user behavior, and comfort/security thresholds.

Conclusions:

• A low-cost, easily implemented home sensor network with an adaptive algorithm enhances elderly care.
• The system improves energy optimization, user comfort, and security, with efficient accident/intruder alerts.
• The study highlights the importance of user-specific algorithms for elderly monitoring and safety.