Big Data-Driven Cyber-Physical Systems: A Comprehensive Survey of Technologies, Applications, and Challenges

Abstract

The convergence of Big Data analytics and Cyber-Physical Systems (CPS) is transforming the modern technological ecosystems in that it allows autonomous and smart, as well as data-driven processes in various fields of application. CPS produce large amounts of heterogeneous sensor data, which cannot be analyzed using conventional analytical methods to obtain actionable insights and help individuals make real-time decisions making. CPS can be optimized to be efficient, failure prediction, resource efficient, and reliable in operations using technologies of the Big Data, cloud, fog, and edge computing. This survey brings a detailed analysis of the intersection of Big Data and CPS, covering the key concepts, enabling technologies, architectural frameworks, and the major areas of application including smart manufacturing, healthcare, energy systems, intelligent transportation, and smart cities. Security, privacy and trust issues related to Big Data-based CPS are also addressed in the paper, and it is pointed out protection measures and resilient architectures are required. Moreover, emerging trends like AI-driven CPS, digital twins, edge analytics, and next-generation communication technologies are discussed to identify the future research opportunities.