Motivation The increasing integration of intelligent sensors into autonomous systems, especially in the context of IoT, requires comprehensive and safer solutions, additionally adaptable and reliable. Modelling their dynamic behavior in complex environments remains a challenge. This study fits into these areas and computationally models capacitive and inductive skin sensors to ensure robust functionality and seamless IoT integration. Results This study introduces a robust model of IoT-integrated multi-sensors, demonstrating their ability to convert capacitance changes in the environment into current signals and shape them for control purposes, which is crucial for smart skin sensor systems. Interval calculations were used to optimize the parameters of the integrated sensors. This analysis highlighted their sensitivity to touch and environmental conditions, which is critical for developing safer and more intelligent responses of such systems. It is shown how changes in the sensor-object distance affect the optimization of the integrated sensor behavior, which is essential for managing uncertainty in real-world applications, ensuring reliable and consistent performance. The authors proposed a model for integrating an intelligent skin sensor with an autonomous IoT system. This model shows significant potential for miniaturization, integration with nanogenerators, and scalability, making it particularly suitable for IoT applications. The study confirmed the practical usefulness of these models in designing intelligent and autonomous sensor arrays capable of robust and trouble-free operation in complex, dynamic, and safety-critical IoT-enabled environments.