The Implementation of NGCPS to Integrate AI in Order to Get the Accurate Decision Making

This has ushered in a new era of interconnectivity of Cyber-Physical Systems (CPS), where the physical entities are also networked with the computational systems and henceforth open new opportunities and challenges. This paper presents the development of some of the capabilities of real-time decision-making in artificial intelligence (AI)-based techniques in CPS for improved efficiency, reliability, and adaptability of the concerned system in a given domain. On this, our research builds over and thereby clearly understands the complex interrelationships of the physical processes and computational intelligence in CPS frameworks. We highlight the following specific characteristics of CPS—distribution, heterogeneity, and real-time requirements—that are enforcing novel ways of supporting decisions. Towards the end, we will reinforce the CPS supported by autonomous decision-aid that capitalizes on the use of frontrunner AI technologies, like machine learning, deep learning, and reinforcement learning, to gain agility in responding to dynamic environments and the occurrences of events. For this purpose, the major challenge addressed in the paper is the seamless and easily achievable integration of AI algorithms in CPS architectures, ensuring scalability, robustness, and real-time performance at the same time.