Integration of industrial IoT architectures for dynamic scheduling

Technology advancement in smart sensors, cloud computing, and decision support systems is pressuring the industry to adopt more flexible data-based solutions. One of areas that can benefit from this progress dynamic scheduling, which improve production efficiency by tracking resource availability, job changes, user commands. Challenges include setting triggers through simultaneous integration information cloud-based enterprise databases operational sources Industrial Internet Things (IIoT). This paper proposes an integrated Information - Operational solution scheduling rescheduling operations a personalized environment. It presents implementation real-world application: analytical quality control laboratory pharmaceutical industry. The resulting intelligent sensors business events fog computing architecture allows generation specific online events. focus on definition affecting cloud-fog-edge IIoT used implementation, triggers. optimized reschedule use case shows moving computation closer improves CPU run time for larger instances. However, combined with data exchange querying introduces non-negligible communication delay smaller In situations where fast solutions are required, near edge best approach. On other hand, larger-size instances, recommended