This research project aims to revolutionise warehouse management through the integration of advanced technologies such as Computer Vision and Large Language Models (LLMs). The objectives of this project are multifaceted, including an in-depth examination of current warehouse processes, an exploration of AI-driven solutions for inventory tracking, and an evaluation of the significance of Explainable AI in incident reporting. By leveraging these cutting-edge technologies, the project aims to design an intelligent warehouse system that seamlessly integrates LLM and computer vision algorithms. The primary focus is on improving operational efficiency and minimising losses attributed to package and container mismanagement. Through the implementation of these innovative solutions, the project seeks to address common challenges faced in warehouse operations, such as inventory inaccuracies and delays. The potential applications of this research extend beyond warehouse management, with implications for various industries including logistics, supply chain, and manufacturing. By streamlining operations and enhancing overall efficiency, the outcomes of this project have the potential to benefit businesses and consumers alike, resulting in improved service quality, reduced costs, and increased customer satisfaction.

To combine craft trades and skills with Modern Data collection and Analytics to redefine industry practice through the adoption of Smart Industrial Process Planning systems.