As the Internet of Things and computer technology evolve swiftly, increasing sectors have changed due to the advent of information and intelligence. To effectively administer innovation and entrepreneurship learning materials in higher education institutions, innovation and entrepreneurship education must merge AI and IoT features, incorporating self-initiated innovation and empowerment amidst the new era’s surge, aiding in their adaptation to economic and social advancements. This research applies multi-node IoT technology to construct a multi-node management model of IoT by applying Web services and SOA. Improve the mapping reliability by improving LANDMARK to assist the actual position of the reference anchor point of the IoT node sensor, introduce artificial intelligence into the IoT management system of the IoT innovation and entrepreneurship education resources, and build an IoT node artificial intelligence analysis VGG model, which can realize the Analysis of the IoT management data of innovation and entrepreneurship education and intelligent optimization management of IoT nodes. Simulations and executions of the Internet of Things approach to innovation and managing resources in entrepreneurship education. Results from simulation predictions in assessing teaching effects are produced through the combined mapping of nonlinear action functions. Findings indicate the established neural network system’s predictive accuracy matches the evaluation target, with a correlation coefficient of 0.9094, nearly 1, signifying the model’s scientific and objective nature. Consequently, integrating Internet of Things technology with artificial intelligence algorithms to oversee innovation and entrepreneurial education resources in higher education institutions holds significant practical value in analyzing the operational status and the ideal distribution of resources for innovation and entrepreneurship.