Business process management (BPM) is a well-established field dedicated to helping organisations identify, analyse, and improve business processes. The advent of new technologies, such as the Internet of Things (IoT), has resulted in a transformation of traditional BPM, as the IoT can provide valuable contextual information about business processes. So far, most studies have focused on modelling IoT-enhanced processes, with limited attention to converting raw IoT data into meaningful process context data for integration into event logs to support process analysis. This study addresses this gap by proposing a classification for process-relevant IoT contexts developed following a rigorous taxonomy development method. The classification builds on existing context classifications in both the business process and IoT domains, and it is further systematically refined through use cases found in the literature. To evaluate the classification’s usefulness, applicability, and robustness, two real-world use cases were analysed, demonstrating the effectiveness of the classification in representing the business process context captured by IoT data. This work has facilitated the integration of IoT into BPM, enabling the analysis of IoT-enhanced processes and advancing data-driven process analytical capabilities, particularly for context-aware process analytics.