Optoelectronic equipment-based fault monitoring with 64QAM-OFDM RoF transmission

In the immediate past, the expeditious evolution of transpire technologies, for instance, big data, integrated circuits (IC), 5G communication and artificial intelligence (AI) has noteworthy revamped the potential of optoelectronic paraphernalia. In consequence, the sustentation of these apparatuses has become increasingly labyrinthine. This paper introduces an advanced health evolution and error prediction system for optoelectronic impedimenta, encompasses 5G and AI consolidation. The proffered system intends to convey the uncertainty in health status, life analysis, fault prediction alarms, and ascertainment for optoelectronic machines. By operating a nominal tally of sensors, the system stockpiles different categories of data information and utilizes an exploratory algorithm for inferences for evaluating the system's health. The coalesce for AI, neural networks, fuzzy logic, and gray ideas supplementary amplify the fault prediction potential, producing a research kernel in automation. The put forwarded system tends a concatenation of sustentation assurance assessment, empowering effective prediction and situational maintenance of system failures. This research subscribes to the progress of health assessment technologies and advanced fault prediction for optoelectronic gadgetry, concreting the route for more authentic and coherent systems in the upcoming era.