The aerospace industry is expanding at a rapid tempo. The necessity of this investigation is underscored by the growing demand for precision and efficiency in sophisticated detecting technologies. The critical importance of optical metamaterials (OMM) is the subject of this article. The Aerospace systems are also being altered with the addition of artificial intelligence (AI) capabilities, thermal imaging, and infrared (IR) sensors. It gives as a solution to space challenges, which is vital in avionics, environmental monitoring, and structure health evaluation. Thermal imaging and IR sensors combined with metamaterials provide higher sensitivity and accuracy. This is important for night-time operations, distant detection and low visibility circumstances which widens the spectrum of aerospace applications AI boosts the capability of the sensor systems to provide real-time data processing. Predictive maintenance and adaptive control systems play a key role to increase safety and efficiency. AI methods leverage the machine learning algorithm and computer vision to interpret enormous data sets generated by thermal imaging and IR sensors. In comparison, with standard methods of anomaly detection and enables unparalleled levels of precision for AI, metamaterials, and specialized sensors. This convergence permits complicated applications like as autonomous navigation, atmospheric analysis, and with high-resolution 3D positioning, the UAV and satellites to respond to environmental changes in real-time. Apart from the above-discussed elements, this paper also addresses the factors that compound the efficiency of these technologies, including the fabrication of metamaterials and the available computational power for implementing AI as well as the performance of the sensors in very extreme aerospace conditions. It also presents solutions, among them hybrid sensor networks and adaptive AI, that can be deployed to overcome such limitations. Real-time scenarios, largely focused on sustaining lower radar cross-sections, and enhanced infrared imaging for use in the air space are evaluated to demonstrate the improvements from the methodologies under inspection. To sum up, the combination of OMM, thermal cameras, and infrared sensors with that of artificial intelligence gives a framework for putting in place smart, lightweight, and durable aircraft systems. This fusion of technologies is expected to herald a transformation in the methodology of data acquisition, processing, and utilization by the aviation community, thus announcing the arrival of aircraft systems which are fully independent, efficient, and self-contained.