Abstract #

The emergence of Industry 4.0 has led a significant shift towards the widespread integration of Cyber Physical Systems (CPSs) across diverse industrial domains. Yet, the intricate design and implementation of these systems necessitate adept knowledge and expertise, posing challenges for researchers and engineers. In response, this paper introduces IoT-AID, a Cyber Physical Recommendation System aimed at alleviating these challenges. Leveraging the capabilities of large language models (LLMs) as decision support systems, IoT-AID relies on state-of-the-art techniques such as BERT and Sentence Transformers for semantic understanding and context-aware recommendations. Through a comprehensive exploration and evaluation, this study sheds light on the efficacy and potential of LLM-driven recommendation systems within the realm of CPSs, offering insights crucial for navigating the complexities of Industry 4.0 integration.

Citation #

@INPROCEEDINGS{10708357,
  author={Choaib, Mohammad and Garouani, Moncef and Bouneffa, Mourad and Mohanna, Yasser},
  booktitle={2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)}, 
  title={IoT Sensor Selection in Cyber-Physical Systems: Leveraging Large Language Models as Recommender Systems}, 
  year={2024},
  volume={},
  number={},
  pages={2516-2519},
  doi={10.1109/CoDIT62066.2024.10708357}}