# Artificial Intelligence of Things as New Paradigm in Aviation Health Monitoring Systems
###### Abstract
This research delves into fault prediction and system health management, discussing the application and future trends of PHM in integrated avionics systems to bolster the safety of the aerospace industry. The application and management of AI in the aviation sector, focusing on technology prognosis, applications, and market demand, is discussed in [6]. It aims to enhance our understanding of AI's potential impacts and benefits in aviation, detailing its influence on industry growth and specific uses in areas such as machine learning for manufacturing efficiency. Additionally, the paper addresses concerns among aviation professionals about the increasing reliance on AI, providing a critical examination of this issue through relevant examples. The paper [7] discusses the integration of intelligent assistants (IAs) in aviation, anticipating their deployment across cockpits, air traffic control centers, and airports to potentially enable single-pilot operations and AI-driven air traffic management. While IAs promise significant advancements, concerns arise about their impact on the industry's strong safety culture, traditionally upheld by human oversight. Utilizing a validated safety culture tool, three safety and human-AI teaming experts assess the potential risks and benefits of IAs in aviation, identifying both negative outcomes and opportunities to enhance safety culture. The paper recommends safeguards for various aviation stakeholders to ensure that safety remains a paramount concern as AI technologies are adopted. The role of AI in air traffic management (ATM), analyzing its current adoption and potential to improve safety and complexity management in aviation, is examined in [8]. It reviews a decade of AI research in the ATM domain, identifying trends and extracting key dimensions. Additionally, the paper discusses the necessity for explainable artificial intelligence (XAI) in ATM, presenting the descriptive, predictive, and prescriptive model as a conceptual framework and illustrating its application in a projected 2030 scenario. It concludes that further research and the development of validated XAI methods are crucial for AI acceptance among ATM end-users. The integration of AI and IoT technologies, known as AIoT, has been gaining significant attention in recent years. For example, the paper [9] introduces a cognitive IoT architecture with a new cognitive component for new port management solutions. The results demonstrate improved efficiency in port operations due to more accurate arrival predictions, and the generic nature of the architecture allows for easy adaptation to other domains. The paper [10] presents the development of an innovative unmanned vehicle system designed to operate without the need for additional infrastructure or expensive sensors, addressing manpower shortages. The system features a self-learning, efficient image recognition algorithm that enhances navigation safety and reliability, even with the current limitations of wireless communications and sensor technology. Tested in a factory setting, this system proves capable of supporting multiple unmanned vehicles simultaneously, offering a scalable solution to improve manufacturing efficiency without the high costs and infrastructure demands typically associated with such technologies. The significant advancements in drone technology driven by the integration of AI, highlighting its applications beyond military uses--including logistics, agriculture, construction, and more are discussed in [11]. It discusses how AI has enhanced drone autonomy, enabling them to execute complex missions independently. The study covers the latest developments and applications and considers the ethical and regulatory challenges that could shape the future of drone technology and its impact on the socioeconomic landscape. Air traffic management (ATM) is grappling with increasing complexity and demands improvements to enhance aviation safety, with AI playing a crucial role.