<p>With the increasing global attention to sustainable development, the optimal application of low-carbon energy has become an important goal to promote economic transformation. The combination of mobile edge computing and sensor intelligence systems provides a new solution for the efficient management of low-carbon energy. This study aims to explore how mobile edge computing and sensor intelligence systems can be used to optimize the use of low-carbon energy, thereby improving entrepreneurial performance management and helping enterprises achieve sustainable development. By constructing a low-carbon energy supply chain optimization model and combining with mobile edge computing architecture, an intelligent sensor network is designed for real-time data acquisition and analysis. The system monitors energy usage and optimizes energy distribution through algorithms. In the experimental stage, several enterprises were selected for empirical research to evaluate the performance changes before and after the implementation of the system. The results of the study show that the implementation of mobile edge computing and sensor intelligent systems can improve the energy efficiency of enterprises while greatly reducing carbon emissions. The response speed and decision-making quality of enterprises in operation and management have been significantly improved, and the overall entrepreneurial performance has increased. Therefore, the combination of mobile edge computing and sensor intelligent system not only effectively optimizes the use of low-carbon energy, but also provides a new perspective and method for enterprise performance management, and promotes sustainable enterprise development.</p>