Abstract

This study proposes an approach for wireless sensor power supply voltage early warning using statistical models. Experimental and statistical analysis of electrical parameters and battery discharge characteristics were conducted to establish a reliable evaluation process. A linear regression model was employed to analyze and fit known temperature and voltage data, establishing a relationship model between voltage and temperature and using it to predict unknown voltage threshold data. This solves the problem of the inability to real-time predict the warning voltage threshold of wireless sensors as the actual working temperature changes and ensures their reliability. The results of experiments and statistical analysis demonstrate the effectiveness and accuracy of this method. Compared to the traditional method of using fixed voltage thresholds for warning, the proposed method offers a practical solution that can timely address the issue of low power supply voltage in wireless sensor networks.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call