The field of IoT system dependability and predictive maintenance is moving towards a more integrated and adaptive approach, with a focus on enhancing reliability and efficiency in various applications, including smart microgrids and rail transportation. Recent developments have highlighted the importance of separating management and operation planes, as well as the use of digital twin modeling and AI-enhanced IoT frameworks for predictive maintenance and affordability optimization. Noteworthy papers include:

• One that proposes a framework for separating management and operation planes in IoT systems, achieving near-optimal expressiveness and dependable policy enforcement.
• Another that presents an AI-enhanced IoT framework for predictive maintenance and affordability optimization in smart microgrids, demonstrating improved predictive accuracy and cost savings.