In sensor design, electromagnetic field numerical simulation techniques are widely used to investigate the working principles of sensors. These analyses help designers understand how sensors detect and respond to external signals during operation. One popular method for electromagnetic field computation is the meshless radial point interpolation method (RPIM), where the number and distribution of nodes are critical to ensuring both accuracy and efficiency. However, traditional RPIM methods often face challenges in achieving stable and precise results, particularly in complex electromagnetic environments. In order to enhance the stability and accuracy of electromagnetic numerical calculations, a node generation and adaptive refinement algorithm for the meshless RPIM is proposed. The proposed approach includes an initial node-generation method designed to optimize the balance between computational accuracy and efficiency, as well as a dynamic error threshold and hybrid node refinement method to precisely identify and adaptively refine areas requiring additional nodes, ensuring high precision in critical regions. The proposed method was validated through its application to electrostatic fields and multi-media magnetic fields, demonstrating significant improvements in both stability and accuracy compared with conventional RPIM approaches. These findings highlight the potential of the proposed algorithm to enhance the reliability and precision of electromagnetic field simulations in sensor design and related applications.