DescriptionArtificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through Machine Learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. However, users are challenged to understand and trust their increasingly complex and smart devices, sometimes resulting in mistrust, usage hesitation and even rejection. We demonstrate how to create end-user trust in AI-based intelligent systems and solutions as a major part of the AIoT. Trustworthy AI has three components: it should be lawful, it should be ethical, and it should be robust. We focus on robustness and ethics, ensuring our developed systems are resilient, secure, and reliable, while prioritizing the principles of explainability and privacy. For this, we present (1) a Trust Framework integrated with the design process and (2) a Reference Architecture for trustworthy AIoT systems to structure such kind of systems. In addition, we show their application to a selection of 15 industrial AIoT use cases from 9 different industrial domains.