International audienceInternet of things (IoT) world is growing at a breathtaking pace. This new paradigm shift affects all the enterprise architecture layers from infrastructure to business. Organizations are nowadays faced with new challenges to keep their quality of service and competitive advantage over other rival organizations. Business Process Management (BPM) is a field among others that will be affected by this new technology. Both IoT and BPM communicate through events, and effective and efficient management of those events ensures a better communication channel between the IoT physical layer and the Business layer. However, the huge amount of those IoT generated events and sometimes the subtle difference between their criticality level, generate uncertainty regarding their priority level determination. In this paper, we propose a fuzzy logic-based event management approach to estimate the criticality level of the incoming IoT events using two fuzzy inference systems (FIS) and to manage the priority of business process instances triggered by those events. A case study is presented and the obtained results from our simulations demonstrate the benefit of our approach and allowed us to confirm the efficiency of our assumptions
