The IoT Whisperer: A Framework for Intelligent IoT Service Composition Through LLMs

Manually configuring Internet of Things (IoT) work-flows often involves intricate and time-consuming processes. This complexity can lead to an increase in development time and difficulty in managing and scaling IoT systems. The challenge lies in creating efficient and deployable workflows that seamlessly integrate diverse IoT devices and services. To address these challenges, we propose an approach that leverages IoT system orchestration, workflow development, and Large Language Models (LLMs) to convert high-level natural language system descriptions into executable workflows. Utilizing the Web of Things (WoT) framework, Node-RED and LLMs, we enabled the automatic generation of workflow components from natural language descriptions, enhancing the accessibility and usability of IoT system development for non-experts. We describe an assessment framework for the evaluation of abstract workflow descriptions and use this to analyze the implementation of our approach over systems within various domains, comparing the automatically generated workflows with those produced manu-ally. Our approach provides a powerful and versatile solution for IoT system development. This approach not only simplifies the process, but also provides a foundation for future innovations in the IoT landscape, paving the way for more adaptable and user-friendly IoT solutions.