The recent development of smart devices—such as smart sensors and actuators—has greatly improved the performance of industrial process such as smart factories, smart farms, and other related systems. Hence, we need to consider the proper use of smart devices, and their networking, in designing and implementing control algorithms for such systems to provide more accurate and energy-efficient solutions.

In general, finding an optimal—or even suboptimal—solution for a complex process with internal or external variation is challenging. Therefore, metaheuristic algorithms, including bioinspired algorithms (e.g., simulated annealing, generic algorithm, and Cuckoo algorithm), artificial intelligence, and machine learning are considered as feasible approaches.

This Special Issue strives to provide a timely opportunity to discuss and summarize the latest developments in this area. We especially welcome research articles on theoretical methodology, metaheuristic algorithms for system optimization, and hardware implementation, particularly for real data applications. In addition, we welcome review articles discussing the current state of the art. We hope that this Special Issue will provide an opportunity to share research ideas related to data networking and process optimization for the use of smart devices and algorithms for these.

Potential topics include but are not limited to the following:

• Smart sensor and actuator application to process control
• Smart device development and application to industrial fields
• Metaheuristic algorithm analysis and applications to system optimization
• Deep learning algorithm application to process control
• Complex system optimization through intelligent algorithms
• Energy Internet with artificial intelligence and machine learning
• Data communication efficiency in large-scale system networks
• Bioinspired algorithm application to smart grids