Research on the Database Model of Data Acquisition for Smart Wearable Devices Using Conductive Polymers

This paper first analyzes the conductive properties of conductive polymers in smart wearable devices and explores their application potential in the data transmission process. Then, an algorithm based on run-length encoding is designed to optimize data compression and transmission efficiency. The algorithm reduces redundant data and improves the reliability of data acquisition. In the model simulation part, this paper uses MATLAB and other tools to conduct multiple sets of experimental simulations on the proposed algorithm to verify the effectiveness of the system in different data acquisition scenarios. The simulation results show that the proposed system model has high accuracy, the data error rate is reduced by more than 10%, the data transmission efficiency is improved by more than 15%, and it shows good adaptability under different working conditions. Finally, this paper demonstrates the wide application prospects and reliability of the model in data acquisition of smart wearable devices through a detailed analysis of the experimental data. This study provides new ideas for data acquisition and processing of smart wearable devices and has important practical application value.