Embedded systems comprise several safety-critical requirements that significantly escalate the complexity of design and verification activities. Model Driven Architecture (MDA) is a recognized approach that provides a high level of abstraction to simplify the design and verification activities. However, due to the latest technological advancements and growing demands of embedded systems, the simplicity required for design and verification cannot be achieved through MDA alone. This article introduces an Intelligent Model-driven Framework for Embedded Systems design automation (IMFES) to simplify the design and verification process. An additional layer of artificial intelligence is integrated with the MDA process by exploiting the concepts of Natural Language Processing (NLP). This results in the automatic generation of Platform Independent Models (PIMs), representing the design and verification requirements, either using Large Language Models (LLMs) or traditional NLP approaches. The applicability of IMFES is demonstrated through proof-of-concept implementation, where the design model of the Car Collision Avoidance System (CCAS) is automatically generated from the textual requirements, and verification is achieved through Colored Petri Nets (CPN). Furthermore, a comparison between the rule-based NLP approach and LLMs is also performed. The initial results reveal that IMFES is a significant step towards true design automation to meet the productivity demands of current embedded systems.